Using AI analysis on a large scale can be slow and complex, and associated with higher maintenance costs and software upkeep to onboard new AI models and additional hardware. With edge computing capabilities emerging in more remote locations, AI analysis can be placed closer to the sensors, reducing latency and increasing bandwidth.

Red Hat and NTT, in collaboration with NVIDIA and Fujitsu, have jointly developed a solution to enhance and extend the potential for real-time artificial intelligence (AI) data analysis at the edge.

Built on the foundation of Red Hat OpenShift, the solution has received an Innovative Optical and Wireless Network (IOWN) Global Forum's Proof of Concept (PoC) recognition for its real-world viability and use cases.

This solution consists of the IOWN All-Photonics Network (APN) and data pipeline acceleration technologies in IOWN Data-Centric Infrastructure (DCI). NTT’s accelerated data pipeline for AI adopts Remote Direct Memory Access (RDMA) over APN to efficiently collect and process large amounts of sensor data at the edge.

Container orchestration technology from Red Hat OpenShift provides greater flexibility to operate workloads within the accelerated data pipeline across geographically distributed and remote data centres.

NTT and Red Hat have successfully demonstrated that this solution can effectively reduce power consumption while maintaining lower latency for real-time AI analysis at the edge.

Delivering the PoC

The proof of concept evaluated a real-time AI analysis platform with Yokosuka City as the sensor installation base and Musashino City as the remote data centre, both connected via APN. As a result, even when many cameras were accommodated, the latency required to aggregate sensor data for AI analysis was reduced by 60% compared to conventional AI inference workloads.

The IOWN PoC testing also demonstrated that the power consumption required for AI analysis for each camera at the edge could be reduced by 40% from conventional technology. This real-time AI analysis platform allows the GPU to be scaled up to accommodate a larger number of cameras without the CPU becoming a bottleneck.

According to a trial calculation, assuming that 1,000 cameras can be accommodated, it is expected that power consumption can be further reduced by 60%. The highlights of the proof of concept for this solution are as follows:

• Accelerated data pipeline for AI inference, provided by NTT, utilizing RDMA over APN to directly fetch large-scale sensor data from local sites to the memory in an accelerator in a remote data centre, reducing the protocol-handling overheads in the conventional network. It then completes data processing of AI inference within the accelerator with less CPU-controlling overheads, improving the power efficiency in AI inference.
• Large-scale AI data analysis in real-time, powered by Red Hat OpenShift, can support Kubernetes operators5 to minimize the complexity of implementing hardware-based accelerators (GPUs, DPUs, etc.), enabling improved flexibility and easier deployment across disaggregated sites, including remote data centres.
• This PoC uses NVIDIA A100 Tensor Core GPUs and NVIDIA ConnectX-6 NICs for AI inference.
• This solution helps set the stage for intelligent AI-enabled technologies that will help businesses sustainably scale. With this solution, organisations can benefit from:
• Reduced overhead associated with collecting large amounts of data;
• Enhanced data collection that can be shared between metropolitan areas and remote data centres for quicker AI analysis;
• The ability to utilize locally available and potentially renewable energy, such as solar or wind;
• Increased area management security with video cameras acting as sensor devices.

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Juniper Research forecasts a substantial growth of 182% in the number of smart parking spaces within cities; from 5.8 million in 2024.

Importance of dynamic pricing

The report urges city municipalities to seriously consider investing in and implementing smart parking initiatives within highly congested cities. The advantages surrounding dynamic pricing in smart parking can not only be used to strategically increase revenue but also ease ongoing congestion issues. This is achieved by lowering prices in less congested parking areas; making them more attractive to drivers.

“With more data than ever available and the low latency that 5G provides, parking solutions have become highly responsive,” says Cara Malone. “In cities where on-street parking is a major issue, dynamic signage can be deployed to utilise available parking more efficiently at quieter times; significantly reducing congestion.”

Optimise transit routes using data analytics

Juniper Research recommends smart parking vendors offer data analytics services to municipalities and governments as a priority. This data is critical to analysing parking and occupancy patterns, which can be used to optimise transit routes and development; helping shift citizens to public transport and providing significant value for cities.

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These use cases require various degrees of high throughput, low latency and geographical coverage. Therefore, to maximise networks’ efficiency and reduce operational expenditure, the report urged operators to accelerate the incorporation of AI into core networks.

AI investment critical for network performance & security

The report found that, as operators expand established 5G networks and build future 6G networks, AI must play an essential role. It identified performance optimisation and network security as the most important use cases; accounting for over 50% of global operator spend on AI by 2028.

Additionally, the ever-increasing virtualisation of network functions and demand for cellular data will drive operators to implement AI to decrease operational costs. It predicted that the ability to automate real-time network analysis and adjust network conditions accordingly will be crucial to minimising the costs associated with network management and service provision.

Research author Frederick Savage commented: “As operators compete on the quality of their networks, AI will be essential to maximising the value of using a cellular network for connectivity. High-spending users will gravitate to those networks that can provide the best service conditions.”

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“Advances in GenAI and shifting customer preferences are pushing service and support leaders to reimagine what’s possible for their organisation in 2024,” said Kim Hedlin, a senior principal of research, in the Gartner Customer Service & Support practice. “Leaders are focused on how they can leverage technology to accomplish their top priorities, including improving customer experience and optimizing their operations.”

Pilot employee-facing GenAI underway

About 79% of service and support leaders surveyed were knowledgeable about their enterprise’s plans for GenAI adoption. Of these leaders, 83% said their enterprises either have plans to invest in GenAI or have done so already.

While much of the hype around GenAI in customer service has focused on customer-facing chatbots, many service and support leaders plan to invest in employee-facing GenAI assistants who will support reps in the next 12-18 months. Of leaders whose organisation is planning to make GenAI investments, 94% report they are at least “exploring” employee-facing virtual assistants.

“Many leaders see employee-facing GenAI as an experimental step on the way to deploying customer-facing virtual assistants,” said J.J. Moncus, principal of research, in the Gartner Customer Service & Support practice. “Respondents indicated it’s an important way to learn the risks of GenAI while still having a human in the loop, before moving on to riskier customer-facing deployments.”

The future of self-service

To meet younger generations of customers’ growing preference for self-service, many service and support leaders will experiment with new self-service capabilities in 2024.

However, these service and support leaders face implementation challenges. Among the service and support leaders who cited self-service adoption as a priority in the survey, 51% also named it a significant challenge for 2024.

Interviews with service and support leaders revealed multiple reasons why self-service implementation is challenging, ranging from organisational resistance to data disorganisation. However, early experiments with GenAI have helped leaders to envision new possibilities within self-service.

“The GenAI hype is providing momentum for leaders’ self-service investments,” said Hedlin. “Leaders have seen glimmers of a future in which conversational interfaces powered by GenAI could handle more complex interactions than a traditional chatbot. That vision is helping shape leaders’ self-service strategy in 2024.”

Understand customer journeys holistically

The study revealed that 56% of service and support leaders surveyed say they plan to invest in the customer journey analytics (CJA) market in the next 12-18 months. CJA enables leaders to analyse customers’ interactions with their organisation over time and across channels.

Of those who say they’ll be investing in CJA, 45% indicate that they’ll be investing in this market for the first time.

Moncus says customer service and support leaders are using CJA to gain a more holistic understanding of what customers need.

“Customers’ and executive leaders’ expectations for service interactions will only continue to rise. Service and support leaders need to identify and understand significant customer touchpoints to deliver a better experience.”

J J Moncus

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Nearly 60% of executives say that they have moved beyond ideation and brainstorming to building out use cases, with 55% reporting they expect to have multiple proof-of-concept or minimum-viable product builds by the end of 2023.

“Over the next six to twelve months, leading companies will move from cultivating isolated pilots to scaling for results,” said Eric Berger, a partner in Bain & Company’s Healthcare & Life Sciences practice.

He added that as leadership teams move beyond experimentation into pilots and launches, they are thinking carefully about when and how to communicate their AI journeys to investors.

“Those that can signal a structured, scalable enterprise-wide program, rather than a smattering of standalone initiatives, will reap the rewards in the next phase of AI.”

Eric Berger

Data science and machine learning are not new to pharma executives who have been investing in productivity enhancements for years, primarily in the drug discovery space. Bain research shows that 54% of pharma companies have automated biomedical literature review solutions, and 46% are using AI as part of their process to find potential disease targets.

Old purpose; New drive

GenAI is broadening the aperture of use cases with new opportunities across the value chain. Biomedical literature review and preclinical research remain among the most popular use case areas, although we’re also seeing high investment in IT and competitive intelligence.

Within these top areas, more than 60% of executives say they have at least a proof of concept in development, and around 10% have already rolled out tools. These early adopters have moved swiftly, often reaching a working pilot within about eight weeks. Already, many are seeing tangible value.

Strategies beyond top of mind

GenAI is top of mind for most pharma companies, with 75% citing it as a C-suite and board priority. And investors are watching closely to differentiate the pioneers from the followers. If pharma companies want to generate value from GenAI as fast as the technology allows, they need to ensure the organisation is ready.

Approach to scaling GenAI

Bain suggests taking a three-tiered approach to prime their operating model for GenAI at scale.

Determine your strategic posture. Leading organisations will establish decision-making and funding models that prioritize high-return use cases, ensuring that those use cases fit within their investment themes around bold bets for the future of the business.

Lead through change. GenAI at scale requires strong internal leadership and cross-functional alignment. The best companies will establish an organisational centre of gravity with several executives who act as generative AI champions.

Build the foundations. In addition to the right technology, data, and models, generative AI at scale requires reorienting the organisation to support big visions. This includes recruiting aggressively for data scientists to work on AI initiatives, building strategic partnerships with external vendors for support, and thoughtfully engaging on ethics and regulation by going a step further with a companywide risk management approach.

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ABI Research says manufacturers can expect significant announcements and releases of AI functionality for QMS software in 2024, with deployments commencing in 2025.

“Major impactful AI applications for QMS will include advanced analytics and risk management, Corrective and Preventive Actions (CAPA) automation, Failure Mode and Effects Analysis (FMEA) authoring and AI-powered statistical process control,” explains James Prestwood, industrial and manufacturing technologies industry analyst at ABI Research.

QMS software vendors such as ComplianceQuest, Intellect, and Dot Compliance are first movers by adding AI directly into their solutions. Larger vendors such as ETQ, PTC, Rockwell Automation, and Siemens are also developing AI applications to ensure that strategic manufacturing challenges have been addressed, alongside doing significant backroom testing.

The transformative effect of AI on QMS software will close the loop on quality management by driving continuous improvement in both the product and the production process. Prestwood concludes that due to an entrenched resistance to change in operations, quality workers will be slower to develop an affinity for AI functionality, aside from background data analytics processes.

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At the top of Marr’s list of IoT trends is security. He posits that these billions of connected IoT devices represent a cybersecurity risk, putting security and privacy at the top of the totem pole of trends.

Another trend he sees is AI-augmented IoT. “IoT devices are not just connected they're becoming smarter. Imagine smart gadgets that communicate efficiently with each other preventing digital chaos,” predicts Marr.

He predicts that the smartwatch will become our new personal assistant thanks to generative AI in wearables – possibly spelling the end of AI assistants like Siri and Alexa.

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“The Asia/Pacific healthcare sector is at a seminal moment, defined by a patient-centric care model combined with an ‘AI Everywhere’ approach says Manoj Vallikkat, senior research manager for Healthcare Insights at IDC Asia/Pacific.

“With the advent of GenAI and the need for consumerisation of care, the next five years are set to be the defining period for the healthcare sector, and we are currently at the starting point of this exciting journey.”

Manoj Vallikkat

AI-driven predictions for the healthcare sector

GenAI PX: By the end of 2027, driven by the demand to scale hyper-personalised patient experiences, improve collaboration, and foster equity, 60% of Asia/Pacific healthcare organisations will double GenAI investments.

AI Diagnostics: Driven by the need for improved diagnostic accuracy, speed, and workflow efficiency, care providers in Asia/Pacific will see a 60% increase in AI solution adoption by 2026.

AI Care Anywhere: By 2027, 50% of the healthcare industry in Asia/Pacific will leverage GenAI to address data and workflow fragmentation across care settings to improve diagnosis and patient safety to scale care anywhere.

Other healthcare predictions

Special attention has been given towards optimising technology investments, with a particular emphasis on enhancing operational efficiency and elevating patient outcomes.

Industry Clouds: Driven by the perceived value of purpose-built functionalities for healthcare, 40% of healthcare organisations in Asia/Pacific will adopt industry clouds by 2025.

Payvider Financing: By 2026, 45% of Asia/Pacific private health insurance companies and 75% of U.S. health systems will be "payviders" to improve risk management and address the rising cost of care.

H@H: By 2026, a doubling of hospital-at-home patients will propel a 55% growth in investments in tech-enabled integrated care initiatives to address patient safety, workforce, and care access concerns in Asia/Pacific. 

Techquity: By 2028, 60% of the healthcare industry in Asia/Pacific will prioritise tech partnerships that champion “techquity,” reducing the digital divide and recognising social determinants of health as vital influencers.

Integrated Platforms: Personalised health data platforms will support 50% of covered patients in advanced economies by 2028 while building more accurate patient journey simulations for providers and life science companies in Asia/Pacific.

Future of Hospitals: By 2029, hospital investments in sustainability and modernisation will increase by 50%, driven by the need to reduce costs, improve quality of care, and enhance organisational resiliency in Asia/Pacific.

“Equitable healthcare has always been a big headache for the healthcare sector, but the evolution of technology, such as AI, will provide viable means to reduce the gaps in digital healthcare,” says Louise Francis, head of public sector research with IDC Asia/Pacific.

She opined that the emergence of the concept of ‘techquity’ highlights how technology will provide the bridge to enabling equitable access to healthcare services over the next five years.

“Healthcare providers in the region tend to prioritise investments in data management, AI, and automation, targeting decentralised care and patient outcome, supported by enhanced clinician efficiency. In the healthcare sector, the unique risks associated with AI are significant, which necessitates a greater focus on explainability and data security,” Manoj concluded.

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"Generative AI can increase the overall productivity of ITOps teams by streamlining ITOps workflows, lowering operational expenses, and increasing system dependability," says Dhiraj Badgujar, senior research manager for digital innovation practice and xOps program, IDC Asia/Pacific.

He cautions that any GenAI success will only come if properly implemented to ensure that they correspond with enterprise goals and that adequate guardrails are in place to manage unanticipated events. The advice is not limited to the IT department.

FutureIoT spoke to Jim Chappell, global head of AI and advanced analytics at AVEVA, for his view on how organisations can better realise the gains of GenAI.

What does real generative AI (GenAI) adoption look like in enterprises in Asia?

Jim Chappell: The Asia Pacific region is at a crucial juncture in embracing Generative AI. Singapore is emerging as one of the most rapid adopters in the area, with 53% of executives currently experimenting with Generative AI.

As Generative AI is anticipated to enhance productivity and operational resilience across various functions, we can anticipate a growing number of organisations in the region to emulate the early pioneers, integrating the power of artificial intelligence (AI) into their transformation endeavours to drive business outcomes.

What are the early mistakes enterprises make while adopting GenAI?

One prevalent error that enterprises often commit is hastily joining the Generative AI trend without a strategic plan. As with all technologies, organisations should first assess where its implementation can yield the most significant impact. They can also start with smaller projects before scaling them across the entire enterprise. 

Organisations should not adopt Generative AI merely for the sake of it; they should first identify a real-world business need and then address it using Generative AI, if applicable.

What technologies/tools in the workplace will GenAI replace?

Jim Chappell: With the ongoing advancements in large language models, Generative AI continues to offer more and more sophisticated capabilities.  In the industrial setting, Generative AI is set to revolutionise mundane tasks, embraced by 67% of enterprises in their AI strategy.

With AI transitioning to technology leadership, recent projections envision a 60% surge in workers adopting personal AI tools, driving a BYOAI trend. Advanced machine learning and robotics will optimise processes, boost efficiency, and manage repetitive tasks, empowering human workers to concentrate on intricate problem-solving, decision-making, and creative endeavours.

To maximise the benefit of GenAI, what new skills should employees take on?

Jim Chappell: Employees should first acquire a fundamental understanding of what AI is, including areas of machine learning and predictive analytics. This involves skills such as interpreting AI-driven insights, adapting to predictive asset optimisation tools, and mastering grey-box modelling. A crucial part of this evolution includes expertise in data management, cybersecurity, and seamless AI integration into existing workflows.

Leveraging that foundation, they should then learn what differentiates Generative AI and what it can provide in a business context. Likewise, employees should understand what Generative AI does not provide, to manage real-world expectations and leverage the technology for maximum real-world value such as data contextualisation and problem-solving.

What will be future themes across GenAI in 2024/2025?

Jim Chappell: The convergence of profitability and environmental sustainability is accelerating as Generative AI becomes a driving force in addressing the climate crisis. Industries are increasingly adopting AI technologies to transition to greener operations.

Various types of AI, including Generative AI applications, predictive analytics, asset optimisation, and grey-box modelling, are aiding companies in achieving net-zero targets and reducing environmental impact. The marriage of sustainability and profitability is now a tangible reality, with AI optimising processes and fostering eco-friendly practices.

What is your advice for leaders managing the integration of GenAI in the enterprise?

Jim Chappell: To guarantee the successful realisation of Generative AI benefits within organisations, business leaders must shift their focus beyond the technology itself. Instead, they should undertake a transformation of how employees work, collaborate, address challenges, and contribute value.

Emphasising a people-centric approach becomes paramount, involving substantial initiatives to upskill and reskill employees and ensuring their ethical and responsible deployment of the tools. Cultivating a culture of experimentation is also valuable, commencing with smaller projects in areas conducive to Generative AI adoption.

Overall, real-world goals and business value should be emphasised over the technology itself.  Generative AI can provide amazing assistance when humans have a clear vision of what they want to ultimately achieve.

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Dedicated structural engineering software helps structural engineers perform their duties like Bentley’s Structural Analysis and Design software (STAAD), which “helps structural engineers perform 3D structural analysis and design for steel and concrete structures”.

Hyundai Engineering & Construction Co., Ltd  (Hyundai E&C) won Bentley Systems’ 2023 Year in Infrastructure and Going Digital Awards in the Structural Engineering domain by using STAAD and Artificial Intelligence (AI) to automate shelter and pipe rack designs. 

“The result was an error-prone resistant, integrated solution of 3D modelling with intelligent digital workflows that provided accurate design information and accelerated front-end engineering design by at least 30%. A database of 1,680 scenarios was created, generating 27 million prediction models, that can automatically convert design information into a 3D model for real-time synchronisation of maintenance prediction and improvement work of buildings in similar projects in the future, ” reports The Structural Engineer.  

Deciding to use STAAD

According to Dongwon Kim, the general manager of Hyundai E&C South Korea, they decided to use STAAD to carry out modelling automation. 

“The modelling program has to provide Application Programming Interface (API) because we can use that API to customise. It provides countless APIs. That is the core factor why we leverage STAAD very well,” he explains. 

Kim claims that without the software, it will be impossible to carry out structural designs. 

“Without STAAD, you have to come up with other modelling programs. Using STAAD without automation, working on modelling may take three days. If you use automation, you can complete your job within a day and save time by 30% to 60%,” the Hyundai E&C executive adds. 

STAAD, automation, AI

Kim says using STAAD and automation has worked miracles for them but they are still looking for ways to step up the game. 

“To further ourselves to the level of AI, we had to take one step ahead by accumulating good data,” he explains. 

He adds that enhancing the prediction accuracy of AI requires an excellent database. 

“Maybe, for now, our AI is not perfect yet, but accumulating a good database will enhance prediction accuracy. Even if it does not reach a 100% level, as long as that prediction is better or higher than humans, it is better.” 

Benefits of STAAD

Kim says the main advantage of STAAD is its various functions. 

“There is a variety of APIs available from modelling to analysis, geometry modelling loading, input setting, boundary condition, design parameter, and analysis,” he lists.

Bentley notes that STAAD “can design, analyse, and document structural projects – anywhere in the world, with any material. It also offers a flexible solution to cover all structural engineering needs from the foundation up. STAAD is a comprehensive structural finite element analysis and design application that allows users to analyse any structure exposed to static, dynamic, wind, earthquake, thermal, and moving loads. 

Kim adds that STAAD supports various coding languages. According to Bentley Communities, C, C++, VB, VBA, FORTRAN, Java, and Delphi “can tap into STAAD’s database and seamlessly link input and output data to third-party applications.”

“The developers who can converse in different languages can use its programming benefits,” Kim says. 

The future of STAAD and automation 

In the future, Kim hopes to collaborate more with Bentley to discuss plans and innovations at Hyundai E&C. 

“We want to extend automation into a variety of structures. We need to collaborate to make our designs and how we can automate. We have to develop a lot of ideas. We can work on them to be better.”

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“We are not only making 5G networks smarter, simpler, and more secure for our customers’ IT departments. We are also allowing our customers’ security organisations to take control over how their employees leverage generative AI tools, protecting them from misuse that could lead to a damaging data leak or a malware infection,” said Donna Johnson, CMO at Cradlepoint.

AI capabilities include:

NetCloud AIOps Dashboard – Simplifies the ongoing operations of enterprise networks leveraging 5G SASE capabilities. The NetCloud AI model aggregates learning into a single dashboard that identifies areas of performance degradation, isolates the cause of the issue, and pinpoints the affected sites, users, and applications. With a unique focus on cellular networking, NetCloud AIOps will turn cellular signal quality indicators, such as proximity to cell tower, signal quality, and signal strength into actionable insights to enhance performance.  

AI-based NetCloud Assistant (“ANA”) – Uses natural language processing to assist NetCloud users with everyday queries about the operation of their network. From providing recommendations on cellular endpoints for specific use cases, to effectively troubleshooting network performance issues, ANA will be an invaluable assistant to simplify day-to-day operations.

Network Traffic Analysis – Provides centralised flow-level visibility for traffic analysis and forensics. This service will evolve later this year to leverage AI to establish a baseline of normal traffic patterns for the most common 5G use cases (distributed IoT, vehicles, sites) and flag any anomalies indicating the signs of a breach. 

GenAI Data Loss Prevention – With 79% of organisations reporting generative AI adoption without established policies, this solution applies access policies to block confidential data, personally identifiable information, or other sensitive data from being submitted to the generative AI site which can be potentially exposed in future responses. Ericom’s remote browser isolation technology also protects against weaponised responses infecting employee assets.   

“As a provider of turn-key car wash solutions, our customer success model requires highly reliable and efficient car wash operations,” said Ian Beason, director of Technology and Innovation at Motor City Wash Works.

He added that Cradlepoint’s new AIOps capabilities will allow our lean IT team to scale with our growing customer base and manage our network more effectively while providing an enhanced level of service to our customers.

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Trained on seven years of insights and data science development, Juniper’s AI-Native Networking Platform was designed from the ground up to assure that every connection is reliable, measurable and secure for every device, user, application and asset.

Unique to the industry, Juniper’s AI-Native Networking Platform unifies all campus, branch and data centre networking solutions with a common AI engine and Marvis Virtual Network Assistant (VNA).

This enables end-to-end AI for IT Operations (AIOps) to be used for deep insight, automated troubleshooting and seamless end-to-end networking assurance, which elevates IT teams’ focus from maintaining basic network connectivity to delivering exceptional and secure end-to-end experiences for students, staff, patients, guests, customers and employees.

The Juniper AI-Native Networking Platform provides the simplest and most assured Day 0/1/2+ operations, resulting in up to 85% lower operational expenditures than traditional solutions, demonstrates the elimination of up to 90% of network trouble tickets, 85% of IT onsite visits and up to 50% reduction in network incident resolution times.

“AI is the biggest technology inflexion point since the internet itself, and its ongoing impact on networking cannot be understated,” said Rami Rahim, Juniper Networks CEO.

He added that Juniper’s AI-Native Networking Platform represents a bold new direction for Juniper and for our industry. “By extending AIOps from the end user to the application, and across every network domain in between, we are taking a big step toward making network outages, trouble tickets and application downtime things of the past,” said

Within the new AI-Native Networking Platform, Juniper is introducing several new products that advance the experience-first mission, from more predictable, reliable and measurable IT operations using AI, to simpler high-performance data centre networks specifically designed for AI training and inference.

Networking for AI

Juniper is expanding its AI data centre solution, which is the fastest and most flexible way to deploy high-performing AI training and inference clusters, and the simplest to operate with limited IT resources.

The Juniper solution consists of a spine-leaf data centre architecture with a foundation of QFX switches and PTX routers operated by Juniper Apstra. With unique intent-based operations, the new Marvis VNA for data centres and validated AI designs, Juniper takes much of the complexity out of AI Data Centre networking design, deployment and troubleshooting, allowing customers to do more with fewer IT resources.

The solution also delivers unsurpassed flexibility to customers, avoiding vendor lock-in with silicon diversity, multivendor switch management and a commitment to open, standards-based Ethernet fabrics.

New products and capabilities to drive even more speed, efficiency and scale: 

• Juniper Apstra has been expanded to provide faster and more efficient processing of AI/ML traffic over Ethernet, including congestion management, load balancing and flow control.
• New Express 5 silicon-based PTX routers and line cards with the promise of industry-leading performance and energy-efficient sustainability to enable the necessary massive scale with high-density 800GE capacity. 
• A new QFX switch provides 2X the capacity of the previous generation and is the first announced data centre switch from an Original Equipment Manufacturer using the most advanced Broadcom Tomahawk 5 silicon for 800GE.

Both the new PTX and QFX platforms support high 800GE port density and the necessary AI infrastructure protocols, including RDMA over Ethernet (RoCE v2) for power-efficient and scalable AI Data Centre networking.

Sustainability considerations

The AI-Native Networking Platform exceeds sustainability requirements without sacrificing performance and security. Its AIOps enable fast and remote troubleshooting, significantly cutting inter-site travel by 85% in certain instances. It also features power-efficient hardware which minimizes energy consumption and is modularly built to make repairs easier and prolong product life.

“Juniper’s AI-Native Platform provides comprehensive solutions for organisations seeking to transition from reactive to proactive and even predictive network troubleshooting and management, said Bob Laliberte, principal analyst with the Enterprise Strategy Group.

He explained that the combination of proven AIOps and the addition of synthetic testing enables highly available and optimized network environments. He added that Juniper is extending its AI capabilities to the data centre by coupling Marvis VNA with Apstra so it can provide end-to-end context and simplified use leveraging conversational AI interfaces.

“Additionally, Juniper’s AI-native solutions and switches can be applied to power back-end GenAI network infrastructure. Organisations can take advantage of Juniper’s validated solutions to accelerate adoption and time to value of these GenAI environments,” he continued.

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“CSCOs see GenAI as supportive of their broader digital transformation objectives,” said Noha Tohamy, distinguished VP analyst in Gartner’s supply chain practice.

"Many supply chain leaders were already leveraging supply chain technologies and advanced analytics, and it’s clear from this data that the majority also see the value in GenAI to enhance productivity, improve business agility and reduce costs."

Noha Tohamy

“The challenge for many of these organisations over the next 12 months will be in scaling their pilot projects to broader adoption,” she continued.

Gartner surveyed 127 supply chain leaders in November 2023 on their plans to utilize GenAI within their function for 2024. Nearly two-thirds of respondents plan to, or are already in the process of, implementing the technology, with just 2% of respondents having no plans to do so over the next year (see Figure 1).

Figure 1: Supply chain leaders’ GenAI utilization plans

Tohamy noted, however, that the survey responses show that the supply chain lags behind other enterprise functions, like marketing and sales, in adoption. This could present an opportunity for supply chain organisations to be “fast followers” by capitalizing on early learnings and technology investments from other functional partners.

The survey data showed that the most impactful supply chain use cases for GenAI include areas such as code augmentation, providing more insights into supply chain key performance indicators and staff assistance chatbots.

The survey also showed that supply chain leaders are backing up their implementation plans with significant budget allocations. Supply chain leaders will allocate 5.8% of their budgets to the technology, as well as incremental employee spend to deploy GenAI. Sixty-five per cent of respondents said they will hire dedicated staff and experts to help deploy the technology in 2024.

Tohamy said that the projected budget data shows that supply chain leaders are serious about making progress on GenAI solutions this year and that they also recognize the need for additional resources to successfully move beyond small-scale pilots.

“CSCOs may also be factoring in impacts on employee roles required of their staff as they shift to higher value-add activities, while lower-level tasks are increasingly automated,” concluded Tohamy.

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Manufacturers face significant challenges in navigating a dynamic and fiercely competitive market. Issues such as supply chain disruptions, escalating inflation, growing cyber threats, workforce shortages, and mandatory sustainability compliances are compelling organisations to reassess and reshape their business strategies.

In the IDC FutureScape: Worldwide Manufacturing 2024 Predictions — Asia/Pacific (Excluding Japan) Implications, IDC predicts that by 2027, 60% of Asia/Pacific-based organisations will augment operational roles with automation technology, elevating employee engagement and unlocking a 50% increase in worker efficiency.

IDC’s predictions highlight that AI will drive greater automation that reduces human intervention, creating an autonomous environment, and improving decision-making that drives higher operational efficiencies. The introduction of GenAI has spurred manufacturers to reconsider their approach and reimagine the next level of use cases.

2024 predictions

• Use of AI/ML for high-mix, low-volume production: By 2025, to promote personalized products as added-value, 40% of Asia-based 2000 (A2000) manufacturers will fully utilize AI/ML for high-mix, low-volume production.

• Generative AI integration into operational systems: By 2025, 40% of Asia/Pacific-based companies will be integrating operational systems with GenAI to better ingest data, identify issues, and provide real-time context to operators improving efficiency by 5%.

• Use of AI/ML in robotics and automation: By 2028, the integration of AI/ML into robotic and automation routines within industrial operations will increase by 30%, driving higher efficiencies and a 10% reduction in downtime.

In the near term (2024-2026), the focus will be on the integration of AI to augment operational roles and improve product personalization, and on the integration of GenAI into operational workflow. Meanwhile, the long-term (2027-2029) focus will be on the adoption of AI-powered robotics and automation for higher efficiencies and better productivity performance.

"Manufacturers in the Asia/Pacific region are adopting a digital business model with a primary focus on increasing revenue streams, enhancing operational efficiency, managing risks, and fortifying operational resilience," says Dr Wai Yee Lee, research manager for IDC Manufacturing Insights Asia/Pacific.

She notes that technologies such as automation, robotics, cloud computing, edge computing, artificial intelligence, GenAI, and digital twin are pivotal enablers for organisations to cultivate operational excellence, business agility, and resilience.

“These technologies play a crucial role in achieving both short- and long-term goals, thereby opening up new avenues of opportunity for businesses,” she opined.

The post What APAC manufacturers can expect in 2024 appeared first on FutureIoT.

Generative AI emerges as a game-changer for organisational advancement, weaving a seamless tapestry across three key fronts: intelligent document processing (IDP), generative automation, and knowledge sharing.

• Smarter Document Handling: By 2026, businesses that link GenAI to smart document handling will discover 20% more ways to use it, boosting productivity, scalability, and delivering better customer experiences.

• Generative Automation: Business teams using code generation copilots will achieve 70% success rate in streamlining jobs with task/workflow automation, replacing low-code and IT-supported development by 2024.

• Efficient Knowledge Sharing: In 2025, GenAI tools will enable senior leaders to double the productive use of unstructured data by discovering untapped insights and knowledge, driving 20% growth in sustainable business benefits.

Expanding its influence

As GenAI takes centre stage, its adaptive capabilities are set to streamline processes, automate tasks, and redefine the skillsets required for various roles. While this evolution brings forth unprecedented opportunities for upskilling and reskilling, it also underscores the imperative for organisations to adapt to this paradigm shift, ensuring the alignment of talent with the dynamic demands of the future workplace.

This prediction not only foretells a redefined professional landscape but also emphasizes the pivotal role of GenAI in driving organisational agility and competitiveness. In this dynamic environment, the significance of skill development cannot be overstated, as it becomes the essence of staying competitive and relevant.

GenAI is not just a technological advancement but a catalyst for change in the skill landscape. The imperative for skill development is no longer a choice but a necessity in a landscape where GenAI is reshaping how we work.

• Job evolution: By 2027, 40% of current job roles will be redefined or eliminated across A2000 organisations accelerated by GenAI adoption.

• Tailored skills boost: Enterprises will leverage personalized technology skills development to drive $1 trillion in productivity gains by 2027, enabled by GenAI and automation everywhere.

• Tech skill support: By 2027, 80% of A1000 organisations will mitigate technical skills shortages using digital adoption platforms.

• AR/VR engineering and training: By 2028, half of large businesses will use prompt engineering to prototype AR/VR simulations, reducing development time from weeks to hours and creating precision training.

Simultaneously, digital twins and sustainable office design are capturing attention, reflecting a growing focus on environmental consciousness in the region. Organisations are recalibrating priorities to balance technological innovation with a commitment to sustainability, showcasing a harmonious approach where cutting-edge technology aligns with ecological stewardship in APEJ's business narrative.

• Digital twin maturity: By 2028, digital twin technologies will enhance virtual and physical office user experiences, driving a 30%+ improvement in retention of workers in A1000 companies.

• Green offices: By 2028, half of the biggest companies are set to invest in what we call "Climate Heavens" for their offices. This means using things like assets and renewable energy to cover 30% of their ongoing operating costs, making workplaces more eco-friendly.

"As the benefits and applicable use cases of GenAI unfold, organisations are exploring the outcomes that GenAI can potentially bring to business operations and innovation. The focus on skill development becomes a necessity and a strategic imperative, as GenAI enables personalized development. Simultaneously, the reimagination of workplaces, with digital twins and sustainability stand out as key foci for companies," says Dr Lily Phan, research director for Future of Work at IDC Asia/Pacific.

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ABI Research says the market is facing a period of significant evolution due to the growing presence of Artificial Intelligence (AI) solutions acting as an enabling technology, which will fuel growth in the quality control machine vision market to reach US$7.2 billion by 2028, up from US$2.3 billion in 2023.

“AI is accelerating and improving the efficiency of the MV market. It increases inspection speeds and enables the movement of quality upstream, and AI systems are more adaptable than traditional software,” explains James Prestwood, industrial and manufacturing industry analyst at ABI Research.

“Although many AI solutions can easily integrate with existing MV hardware and software, making it a low-hanging fruit for manufacturers to leverage, its lack of explainability can be challenging. Without this functionality, AI could struggle to make traction in high-regulation markets.” James Prestwood

“While some AI vendors are making great strides to support their software with explainability functionality, such as Neurala, it is not a standard feature on all solutions yet,” said Prestwood. 

The MV ecosystem comprises a wide range of vendors, with many specializing in providing best-of-breed components, such as Neurala, Intel, Google, Landing AI, Instrumental for AI, and Sony, Teledyne, and Nikon for cameras. Other vendors focus on providing robust end-to-end MV solutions, including Aqrose Technology, Cognex, Basler, Keyence, SICK, Omron, and Elementary Robotics.

“For most manufacturers, budget and build complexity will be the defining factor for choosing off-the-shelf solutions and build-your-own with best-of-breed component deployments. Smaller manufacturers will likely find the greatest use for off-the-shelf solutions due to their lower cost and simpler requirements,” Prestwood concludes.

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Below are Seagate’s predictions for data storage in the AI era

As generative AI becomes more democratized, data storage will drive AI success.

Businesses will be saving more operational data to teach AI, machine learning, and deep learning models moving forward; more companies will train models on both external and internal data so they can benefit from their proprietary information.

Hyperscale tech giants are expected to accelerate investment into cloud capacity to support AI program maturation. AI will also drive increased IT spending and data storage demand in the enterprise, as businesses seek a competitive edge through improvements to productivity and efficiency.

Data centre refreshes will benefit from leaps forward in hard drive areal density.

With nearly 90% of data in cloud data centres residing on hard drives, there is an opportunity to replace fleets of lower-capacity hard drives with higher-capacity drives, as and when refresh cycles come.

This includes the use of heat-resisted magnetic recording (HAMR) in high-density drives, which will mean significant power and space savings and massive TCO efficiencies—including CPU, RAM, and floor space. Not to mention help reduce carbon footprint with more durable and energy-efficient storage.

Flash and hard drive technology will continue to coexist in the data centre in 2024.

The exponential data growth will drive demand for mass-capacity hard drives, whose synergy with flash storage will continue to support modern workloads. Hard drives will remain the most cost-effective option for most capacity-centric storage tasks.

Seagate claims hard drive storage will offer mass data storage at less than one-fifth the cost of comparable all-flash solutions on a per bit basis, and that the value gap will not come close to closing next year—or over the next decade.

Data storage will shape three major applications of the future.

Edge computing and Internet of Things (IoT): The integration of edge computing with IoT technologies is pushing the boundaries of data storage, demanding unprecedented scalability, latency, and operational flexibility to correlate real-time data with vast historical datasets for immediate analysis and forecasting.

Quantum computing and data processing: The rise of quantum computing demands new data storage architectures to prevent data loss due to the volatile nature of qubits. This will require quantum-safe cryptographic solutions.

Genomic data and precision medicine: A single human genome requires up to 200GB of storage space. As this data accumulates across millions of individuals, healthcare systems face logistical hurdles and ethical and privacy concerns.

Advanced analytics tools using machine learning algorithms are also being fine-tuned to analyse this vast amount of data swiftly and accurately. This evolving data infrastructure aims to pave the way for a future in healthcare where genomic profiles guide everything from preventive measures to targeted therapies, thereby enhancing patient outcomes and healthcare efficiency.

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“When we look at the backdrop for 2024, we are still seeing many of the 2023 trends impacting fortunes,” says Stuart Carlaw, chief research officer at ABI Research. “High inflation, cost pressures, and reduced demand continue. Major markets like the US, Germany, and China face extended manufacturing recessions. Monetary policy's focus on curbing inflation hampers tech funding. Yet, there are signs of hope: inflation is dropping, central bank policies might change, and job markets recover. The global political landscape is the one outlier not on the trajectory to positive movement. That withstanding, 2024 could be a watershed year as we collectively turn a corner. It won’t be smooth, and it won’t be linear, but 2024 holds the promise of technology providing the acceleration engine to move us out of the past few years in the doldrums.”

What won’t happen in 2024?

Enterprise 5G

5G will fail to attract enterprise interest in 2024 – just like in 2023. In deciding about investments in connectivity technologies, enterprises are much more interested in use cases and outcomes than in the name of the connectivity technology—especially because the implementing enterprises are not connectivity technology experts.

Mainstream foldable devices

Thinner and lighter designs, better hinges, crease-free displays, fold and flip form factors, and larger cover screens—these features are convincing consumers to switch to foldable devices.

This is not for lack of trying, as the roster of competitor foldable devices is impressive, including flip and fold variants.

Network APIs

Despite the efforts of GSMA's Open Gateway and CAMARA initiatives, Network APIs will not likely create significant business opportunity. And will suffer the very same fate as GSMA’s OneAPI project in 2012, which was abandoned soon after it was launched.

It is true that the telco operators desperately need enterprise revenue and use cases in 2024, but the same problems that faced network Application Programming Interfaces (APIs) a decade ago remain today: application developers are already addressing their needs through either aggregators or hyperscalers. Releasing fancy new network API initiatives will not automatically attract developer attention.

Generative AI at the edge

Enterprises will deploy generative AI in the cloud but not at the edge. The challenge with running generative AI at the enterprise edge will be in terms of selecting a good use case, deploying the correct generative AI framework/model, and balancing Return on Investment (ROI) expectations.

Robotaxis

Don’t expect robotaxi operations in 2024. The complexity of unsupervised autonomous driving in the real world is becoming increasingly apparent, particularly in interactions with more vulnerable road users.

What you can expect is greater scrutiny following the Cruise robotaxi accident.

“ABI Research is privileged to sit in a powerful position between the tech innovator communities and those companies looking to utilize technology in their operations. Our goal is to provide the key decision tools businesses need to act with speed, appropriateness, and efficiency. 2024 will be challenging, but it also holds great promise and opportunity,” Carlaw concludes.

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Digital technology and cloud capabilities are essential components in data-driven operations (DDO). IDC’s 2023 Worldwide Future of Operations Survey shows that cloud is one of the top technology priorities for organisations in Asia/Pacific excluding Japan (APeJ), with 77% of respondents in the region saying that cloud is essential or very important to their organisation’s operations.

Other key technologies needed to achieve efficient, resilient, and optimized operations include AI, robotics, mixed reality tools, edge computing, 5G and cybersecurity.

"Organisations in Asia/Pacific recognize the importance of investing in essential technologies for data-driven operations," states Rakesh Patni, associate research director for Future of Operations Asia Pacific.

Looking to the future

Generative AI (GenAI) will be essential to driving greater insights from operational data: 57% of APEJ respondents said GenAI tools (such as ChatGPT) will be one of the top 3 analytic tools and techniques their organisation plans to make significant new investments in to analyse operational data.

GenAI, employing both unsupervised and semi-supervised algorithms to produce new content based on existing text, audio, video, images, and code, represents a pivotal technology heralding the advent of a novel computing age - the Era of AI Everywhere.

AI: A Cornerstone of the Future of Operations

GenAI Data Discovery: By 2027, 30% of A2000 will utilize generative AI to produce ad-hoc operational performance reports, saving 10% of operations labour costs from manual data aggregation

AI-driven Industrial Automation: By 2026 20% of industrial operations in Asia will use AI/ML for vision-based systems and robotic and automation processes to achieve higher efficiencies, reduce downtime, and improve worker safety

Cybersecurity Impact of AI: By 2026, 50% of organisations in Asia will leverage AI-enabled advanced threat detection, to mitigate growing risks from GenAI cybercrime tools (WormGPT) used in phishing and ransomware attacks

Between 2024-2025, the focus will be on addressing the cybersecurity impact of GenAI cybercrime tools being used to launch ever more sophisticated ransomware attacks and investments in AI/ML vision-based systems and robotics to accelerate AI-driven industrial automation to improve operational efficiency and reduce downtime.

Longer term (2027 onwards) organisations will leverage GenAI to produce ad-hoc operational performance reports, saving on operations labour costs from manual data aggregation and increasing the speed of internal and administrative tasks.

While the current emphasis has been on AI, IDC also emphasizes the necessity of adopting an integrated approach, encompassing both a variety of technological and strategic facets, to adeptly manoeuvre through the era of digital business transformation.

IDC's Future of Operations Predictions for 2023

Talent development investment: Driven by rising digital talent shortages, over 40% of A2000 will need to increase talent development spending substantially to execute digital operations roadmaps and achieve ROI targets by 2024

Sustainability-driven OpEx: By 2027, 25% of industrial organisations in Asia will leverage real-time data capture and integration investments for sustainability initiatives to boost operational performance and visibility

Unified partnership transformation strategy: By 2027, 25% of A2000 companies will spend 15% of their digital technology budgets with third-party IT and engineering services partners to simultaneously transform multiple operations functions

Private Ops Networks: By 2028, 25% of industrial organisations in Asia will have deployed Private LTE or 5G networks to at least 30% of their operational sites to reduce up-front costs and improve data collection

Edge-native app data: By 2026, organisations in Asia that have embraced edge-native platforms will extract 2x more value from data, and deploy projects 3x faster than those with traditional core, edge, and cloud resources

Cloud data repatriation: By 2025, 30% of A2000 will undergo initiatives to pull data back from the public cloud, shifting operational data that does not require intensive processing locally, reducing OpEx costs by up to 10%

Human augmentation through technology: By 2027, 60% of Asia/Pacific-based organisations will augment operational roles with automation technology, elevating employee engagement and unlocking a 50% increase in worker efficiency

Patni suggests that organisations establish core technologies such as cloud, artificial intelligence and advanced connectivity and acquire new digital capabilities to improve their ability to contextualize high-quality data and drive greater insights into their operations.

He cautioned, however, that they also focus on talent development through new hires, forming partnerships with service providers, or by enhancing the skills of their current workforce.

“The combination of skilled talent and appropriate technology, aligned with a strategic approach, is crucial for optimized and efficient operations. The Future of Operations predictions provide insights and guidance to help organisations in Asia Pacific navigate their digital transformation journey," concluded Patni.

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IDC’s 2023 Future Enterprise Resiliency and Spending (FERS) Survey, Wave 6, highlights that almost half (43%) of organisations surveyed are currently exploring potential GenAI use cases, with 55% of financial organisations and telecom firms investing in GenAI technology in 2023.

"Generative AI can increase the overall productivity of ITOps teams by streamlining ITOps workflows, lowering operational expenses, and increasing system dependability. However, GenAI systems must be properly implemented to ensure that they correspond with enterprise goals and that adequate guardrails are in place to manage unanticipated events," says Dhiraj Badgujar, senior research manager for digital innovation practice and xOps program, IDC Asia/Pacific.

With the digital-first mindset gaining momentum in Asia/Pacific, businesses are seeking innovative solutions to enhance operations. GenAI stands out as a pivotal technology, offering companies the means to mitigate risks, boost efficiency, and improve overall productivity.

Generative AI is gaining popularity in IT operations and IT service management, particularly in cost-sensitive Asia/Pacific environments. This technology offers automation of ITOps tasks, reducing operational costs and optimizing resources.

The region, which includes mature economies like Australia, Japan, and Singapore, and rapidly growing markets like India and China, has diverse IT requirements and issues. In growing economies, generative AI plays a vital role in facilitating scalable ITOps.

ITOps trends influenced by GenAI

Rise of AIOps: AIOps solutions are becoming more popular in Asia/Pacific. ML and AI algorithms are being used by enterprises across the region to automate IT processes, monitor performance, and forecast and avoid IT disasters.

Predictive analytics: AI-driven predictive analytics in ITOps helps enterprises anticipate IT issues and prevent disruptions.

Hybrid cloud and multi-cloud management: As enterprises in the region embrace hybrid cloud and multi-cloud settings, GenAI will be used to manage these complex infrastructures.

Continuous improvement: GenAI models will evolve in complexity and quality, likely integrating with IoT and edge computing to enhance data collection and analysis.

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“I&O leaders have little time, skills and budget to track emerging trends and the full impact of those on I&O,” said Jeffrey Hewitt, vice president analyst at Gartner. “I&O leaders should use the top trends impacting I&O for 2024 to identify which are most likely to impact their organisation and implement effective tactics to respond.”

Top trends impacting I&O in 2024

Trend No. 1: Machine customers

Machine customers are nonhuman economic actors that obtain goods or services in exchange for payment, such as virtual personal assistants, smart appliances and connected cars. Gartner expects the number of machine customers to rise over time and that by 2027, 50% of people in advanced economies will have AI personal assistants working for them every day.

Hewitt posits that there are strong upsides to machine customers that are driving interest and adoption in them, however, they come with challenges such as requiring a reworking of operating and business models.

“I&O leaders should identify appropriate machine customer use cases, the technology processes and skills required, and build capabilities around digital commerce and generative AI to align optimally,” he continued.

Trend No. 2: AI trust, risk and security management (AI TRiSM)

AI TRiSM supports AI model governance, trustworthiness, fairness, reliability, robustness, efficacy and data protection. I&O must implement and support the new forms of risk and security management that AI require. Gartner predicts that by 2026, organisations that operationalize AI TRiSM will see their AI models achieve a 50% improvement in terms of adoption, business goals and user acceptance.

“AI TRiSM improves AI implementation efficiencies and helps prevent the financial, regulatory, societal and ethical consequences of potential issues with AI,” said Hewitt.

Trend No. 3: Augmented-connected workforce

Augmented-connected workforce is the intentional management, deployment, and customization of technology services and applications to support the workforce’s experience, well-being and ability to develop their skills. It accelerates onboarding and drives business results which has a positive impact on key stakeholders.

Hewitt opines that this is a relatively new way of thinking for I&O which requires new skills and workflow views. “It also requires collaboration outside of I&O and IT which takes specific focus, and sometimes executive involvement, outside of IT to achieve that engagement,” he added.

Trend No. 4: Continuous Threat Exposure Management (CTEM)

A CTEM program is an integrated, iterative approach to prioritising potential threats and continually refining security posture improvements. Technology growth requires a new approach to dealing with potential threats.

This expands the attack surface and broadens exposure beyond the average IT environment. CTEM is a new approach that prioritizes exposures rather than centring on fixing all vulnerabilities.

According to Hewitt, CTEM produces a shift from a preventative-only approach to more mature, strategy-augmenting-preventative controls with detection and response capabilities. He recommends organisations establish a CTEM team within I&O to cover on-premises infrastructure as well as cloud and edge vulnerabilities.

Trend No. 5: Democratized generative AI (GenAI)

GenAI enables the democratization of knowledge and skills by enabling the use of conversation and natural language. A Gartner poll of 1,400 executive leaders in September 2023 found that 55% of organisations are in piloting or production mode with GenAI.

GenAI products are democratizing due to the confluence of cloud and open source. GenAI for I&O has two main aspects – the use of GenAI within I&O and the impact of GenAI on I&O.

Hewitt says democratized GenAI offers a new working paradigm and can present agility, adaptability and composability improvements for I&O. “If it is overused or used unnecessarily, it can generate unacceptable costs and negative environmental impacts,” he added.

Trend No. 6: Nationalism versus globalism

Nationalism versus globalism consists of country-led initiatives to reduce dependencies on foreign products, talent and services. International conflicts create a focus on more nationalistic views that push a more domestic approach to technologies which will put pressure on I&O teams to seek solutions that keep more technologies, resources and talent in their own country.

“There are many initiatives in place today that impact the focus of IT resources from a more global view to a more nationalist approach. Shifts in these initiatives can produce new risks for countries that are currently using providers outside their country,” said Hewitt.

He suggests that I&O leaders should identify dependencies and their risks and lead in the creation of action plans to deal with the potential impactful shifts that may occur in national regulations and policies that affect I&O.

The post Gartner outlines the top trends impacting I&O for 2024 appeared first on FutureIoT.

That’s a big number!

It’s especially large when you consider that most organizations are trying to stabilize, pilot or get approval to change their planning tools.

Proportion of Supply Chain Transformation Benefits Achieved

When trying to think about what is missing, or why so many are failing to adopt new technology, the main theme that comes up is that most organizations are trying to implement a solution based on current processes and ways of working. Technology enables a transformation of your operating model that includes processes and organization. But shouldn’t your mindset evolve as well?

When I started working in planning, the first thing I learned was that if our company’s plans were precise everything would work out. I just needed the magic number that would make everything flow.

If only life would be so easy.

The reality is that even when you set a magic number, plans always deviate. Things are dynamic. You most likely don`t have exact plans in other areas of life. Then why do you keep focusing on a single number that will make — or, more likely, break — your supply chain plans?

As companies invest in technology, they should invest in changing the mindsets within their organizations from the obsession with a single forecast to using a range of possibilities.

Range of Possibilities

Assuming that all you need is a single plan that will make everything work is like assuming that the exact optimal circumstances will always occur. But that’s not true. The exact internal and external dynamics will rarely come together in the exact right way. By assuming all you need is a single plan, a single number, organizations make their supply chains fragile. Anything that goes above or below that number will register as a surprise.

And from that point, you know the story. … You rush in with emergency teams, firefighting these new situations as they impact your business results. Let’s face it, anytime you expedite deliveries or steer inventory due to the plan going awry it will impact your cost to serve. In fact, organizations report that they suffer a 4% increase in the cost to serve for every disruption. And they have at least five disruptions per year. So, at minimum, you’re talking about a 20% hit to the P&L.

By changing your mindset to plan for a range of possibilities and probabilities you’ll be better prepared for what will most likely occur. You can’t rely on being precise. There is a range of options from variability of lead time to variability of product mix to variability in order placement. In fact, by abandoning the idea that you must be precise, you can plan for most of the possible options you might face. 

Even if you do plan for a range of possibilities, will all of them be right? Of course not. Only one option will be correct. The rest of them will be wrong. Embrace the idea that you will be wrong most of the time. Think of it this way: you have to be wrong to be right.

Now, I know that nobody likes being wrong. Because everybody wants to avoid errors, they avoid taking risks. But if you avoid risk, then how are you going to win? From Gartner’s most recent survey of supply chain technology user wants and needs, we found that 38% of those surveyed are not encouraged to take risks. Within that group, 12% are actively discouraged from taking risks.

As supply chain planning leaders, you must actively work with your teams to change this point of view.

Just like you’re investing in processes and technology, you need to make an investment in change management — you must embrace a new mindset. You can’t adopt a different operating model and new tools but continue to be stuck in your old way of thinking. If you are planning to transform your supply chain — or even if you’re in the middle of such a transformation — change your planning approach and you will be more than halfway there.

First published on Gartner Supply Chain Insights

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Building on these findings, LambdaTest’s new research, Future of Quality Assurance 2023, has shown that companies are working to respond to the need for greater software reliability with 72% of organisations involving testers in “sprint” planning sessions, signalling a substantial shift towards software quality being considered earlier in the software development lifecycle.

The survey shows that there has been rapid adoption of AI technologies. Uses of AI reported by software testers have included automating the creation of test data (51%), writing code for automated tests (45%), test result analysis and reporting (36%), and formulating test cases (46%). Additionally, 89% of organisations are automating the deployment and running of tests through CI/CD (Continuous Integration and Continuous Delivery) tools.

Persistent gaps

The research has also highlighted that gaps continue to exist in software testing. Teams are spending 10% of their time on setting up and maintaining test environments and a further 8% of time is spent fixing flaky tests. 74% of teams lacked a structured prioritization system, potentially overlooking factors like risk levels and customer feedback when running automated tests.

Finally, many teams lack data-driven insights to measure software reliability – 29% lacked Test Intelligence infrastructure to provide insights on how automated tests are running and 12% lacked reporting systems.

Asad Khan, CEO and co-founder of LambdaTest, pointed out that the study highlights the need to address bottlenecks affecting productivity like brittle tests alongside the set-up and maintenance of test environments. “This presents us with an opportunity as well as a challenge – to develop and implement tools that will efficiently address these bottlenecks to keep driving software quality forward,” he continued.

Commenting on the study, Dr Ali noted that organisations are attempting to close the gap between the market’s expectations of software reliability and the current state. Artificial Intelligence has seen rapid adoption amongst software testers; however, efficiency challenges remain key to improving the cost, speed and effectiveness of software testing.

“Software testers and QA staff face great pressure in the software development lifecycle, whilst practices in the industry like engaging them earlier in the process is a step forward, new tools offer a significant opportunity to help close the gap.”

Dr Junade Ali

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Schneider Electric will integrate Hailo Technologies’ advanced processors within Schneider Electric solutions. By integrating the Hailo-8 AI processor within its industrial automation solutions, Schneider Electric will unlock new intelligence at the edge and drive innovation for its customers, with significant and immediate improvements across several common manufacturing tasks.

Anticipated benefits because of the integration

• Pick and place: achieving object detection tasks six times faster than central processing units (CPUs)
• Quality control: running classification processes 20 times faster than a CPU
• Yield optimization: improving output and throughput, reducing waste by 15% on average

Hailo Technologies is leading the AI chip industry for edge devices, with

Hailo makes technology that enables new computing possibilities for sectors like automotive, security, retail, and manufacturing. Its Hailo-8 processor is an efficient and compact AI processor with low power consumption, enabling real-time, high-accuracy data analysis at the edge.

“We are always looking to partner with companies that can help us deliver the most cutting-edge solution available on the market,” said Aurelien LeSant, senior vice president of innovation & technology and chief technology officer for industrial automation at Schneider Electric.

He explained that the Hailo collaboration reinforces our commitment to innovation and next-generation technology. It signifies an important step in delivering intelligent, energy-efficient solutions that will shape the future of industries.

“We are proud to work with Schneider Electric, an industry pioneer that has recognized the transformative potential of integrating AI capabilities into its industrial automation solutions,” said Eyal Barnea, VP of business development at Hailo Technologies. “Our technology will empower its customers to create new powerful, cost-efficient, and smart AI-based solutions quickly and easily.”

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ABI Research forecasts a steady increase in uptake for cloud-driven digital twin solutions, driven by advancements in AI/ ML, edge computing, multi and hybrid cloud deployments, 5G networks, and smart connectivity.

“We are seeing the emergence of cloud computing in operational technology (OT). The deployment and integration of cloud solutions with OT solutions in areas such as asset performance monitoring and product lifecycle management provide compelling benefits such as performance reliability, increase in computational power, and seamless AI/ ML processing,” explains Yih-Khai Wong, distributed and edge computing senior analyst at ABI Research.

Cloud hyperscalers such as AWS, Microsoft Azure, and Google Cloud provide tools and packaged solutions to build digital twin solutions. Customers can also leverage contextual data from public datasets and funnel this information to optimize their digital twin platforms.

Benefits of cloud-driven digital twin solutions

Scalability: Provides flexibility for businesses to scale up or down according to current business needs, ensuring optimal performance of the digital twin solution.

Computational Power: Complex simulations can be processed on the cloud using solutions such as Virtual Machines (VMs) and containers. The availability of various cloud computational components ensures that businesses can match resources according to specific digital twin platforms.

AI/ML Processing: Cloud computing platforms often provide data analytics tools to help process AI/ML workloads. These tools range from the infrastructure compute power components such as the Central Processing Unit (CPU) and Graphics Processing Unit (GPU) to industry-specific application software that can analyse, predict, and make recommendations based on data processed by a digital twin.

“The convergence of IT and OT is gathering pace, and digital twin is a great example of how this convergence can elevate existing scenarios into achieving greater possibilities and ultimately increase the value, productivity, and competitive advantage of enterprises,” Wong concludes.

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Warehousing today, of course, is much more convenient with innovations around track and trace, robot automation, wearables and warehouse management systems (WMS) coming together under hybrid, multi-cloud to facilitate improved optimisation of assets.

The Zebra Technologies paper, Warehousing Vision Study 2023, reports that warehouse leaders are investing in technology and intelligent automation to increase inventory visibility and resiliency.

State of warehousing in ASEAN

Vivien Tay, vertical solutions marketing lead with Zebra Technologies Asia Pacific, observes that while warehouses in the ASEAN market are growing, growth rates have slowed when compared to during the COVID-19 pandemic.

She recalls that during the pandemic when people stayed home, there was a sharp increase in online shopping. Businesses responded by stocking up on inventory and building more warehouses. Post-pandemic, fewer new warehouses are being built.

“The ASEAN market is very diverse. On one hand, we have the developed markets like Singapore, which are more advanced in their modernisation plans, compared to a less developed market like Vietnam, where most businesses we speak to have a general understanding of modernisation but are unclear of where and how to begin,” said Tay.

She cited the example of Alpro Pharmacy, a diversified community pharmacy chain in Malaysia, that saw the limits of pen and paper to manage inventory movements. Increased demand promoted the chain to deploy mobile computers and RFID. The modernisation increased the operational efficiency of order fulfilment in the e-commerce division by 80% and allowed them to meet the increase in orders without additional workers.

Challenges to modernising

The path to modernisation is not going to be easy. Tay noted that even in mature markets like Singapore, there remain industries that hold on to their legacy warehouse management systems. These do not integrate well with modern devices in the warehouse.

She opined that employees are the most important asset of a warehouse. “For many warehouses, associates have often been working for a long time and are used to manual operations, which may cause them to be averse towards adopting new technology on short notice,” she continued.

“The barriers to entry are often not as high as they’d think, as there are some devices in the warehouse that are specifically designed to be user-friendly, such as the Android devices which use the same operating system as many smartphones out there.”

Vivien Tay

She posits that adopting a phased approach is the key to implementing modernisation plans smoothly. “Warehouses that want to kickstart the digitalisation process can start with basic scanners before moving on to sensor-based technologies like RFID,” she suggested.

Automation and robotics in ASEAN

Mordor Intelligence estimates the warehouse robotics market at US$6.74 billion in 2023 and forecasts this to more than double to US$15.22 billion by 2028.

The analyst cites the emergence of industrial Internet of Things (IIoT) and the advent of a network of connected systems as helping industries perform a multitude of tasks, such as material batching, picking, ordering, packaging, warehouse security, and inspection, as well as improve the operational efficiency by huge margins.

Tay says for operators who have not begun their automation journey, the main challenge they might face is the integration of hardware devices and software solutions.

She opined that empowering employees is also a key aspect to consider. She adds that once operators receive the buy-in of their associates and begin upskilling them with smart devices, associates can move on to engage in higher-value tasks in the warehouse.

“The other challenge I foresee is related to the e-commerce boom. While the e-commerce boom is slowing down due to growing competition in the space, many businesses are struggling with returns management. Efficient handling of returns management is key to managing evolving consumer demands,” she continues.

In terms of robotics, she comments that while markets like China are ahead of the curve and deploying robots beyond the warehouse, such as in consumer-facing roles in shopping malls and restaurants, it is not as prevalent in ASEAN yet.

“The main obstacle to the widespread adoption of robotics in ASEAN is typically the cost in investment and lack of knowledge in the implementation and integration with existing systems,” says Tay.

Sustainability and warehouse modernisation

According to Tay, sustainability has emerged as one of the top priorities for warehouse decision-makers in the upcoming years, led by recent government regulations and sustainability directives, such as the EU’s Corporate Sustainability Reporting Directive (CSRD), and Net Zero by 2050 commitments.

Southeast Asia is beginning to catch up on sustainable warehouse operations, says Tay, deploying technologies like solar panels, efficient lighting, and connecting to energy monitoring software to maximise efficiency.

Warehousing in 2024 and beyond

A central theme of Zebra’s 2023 Warehousing Vision Study is supply chain agility and resilience. The study found that decision-makers are accelerating modernisation projects to meet evolving consumer demands and reduce operational challenges.

Tay explains that returns management is one of the top challenges that businesses face, especially for e-commerce. “Interestingly, research has shown that return rates for e-commerce sales are between 15 and 20%, more than twice the median return rate for all sales categories,” she comments. “Decision-makers recognise they are under pressure to improve performance in returns management, inventory management, and warehouse productivity and output while adjusting to shifting consumer e-commerce demands.”

According to Tay, the warehousing landscape will continue to expand over the next five years. A slowing e-commerce boom notwithstanding warehousing will continue to experience an upward trend.

She predicts that businesses will build more warehouses closer to the consumers, moving away from a large, centralised warehouse system to multiple smaller distribution centres. “Another trend we see in last-mile delivery is the availability of drop-off options for consumers,” she continued.

On the topic of automation, businesses are beginning to empower their employees with automation and technology. The study concurs with this – as it found that employees are happier when they are equipped with technology.

RFID will continue to be a key technology in the warehouse, helping to increase inventory visibility and reduce out-of-stocks. Robots will also increasingly have a larger role to play in the warehouse alongside humans, taking over simple tasks in the picking process to free up associate’s time to move up the value chain.

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To adapt to this changing environment, organisations need a new modern data centre architecture that delivers reliability through automated data centre operations, scalable performance to support the most stringent workloads (e.g., AI model training) and comprehensive data security, regardless of where the data resides.

"Data centre infrastructures are getting more complex and distributed. Traditional firewalls need to become more easily extensible to dynamically align with how the infrastructure is evolving. Juniper’s new security fabric meets market demands by allowing customers to integrate existing routers and firewalls," said Mauricio Sanchez, Sr. research director, enterprise networking and security at Dell’Oro Group. 

The new Juniper Connected Security Distributed Services Architecture integrates Juniper’s unified security management paradigm with (claimed) best-in-class routing and AI-predictive threat prevention to bring much-needed operational simplicity and scale to data centre security.

In addition, four new high-performance firewall platforms deliver unmatched performance in a compact footprint that minimizes cost, space and power consumption. 

The vendor claims its Connected Security portfolio provides a secure bridge for customers to facilitate their transition to a modern data centre, at their own pace.

This is achieved via the following unique innovations:

Juniper Connected Security Distributed Services Architecture: Juniper is the first in the industry to deliver an architecture design that fully decouples the forwarding and security services layers that have traditionally been combined in a single firewall appliance.

By decoupling these layers, customers can utilise their existing Juniper MX series routers as intelligent forwarding engines and load balancers. This unique design gives customers independent scaling flexibility without chassis limitations, multi-path resiliency and cost efficiency.

When coupled with Juniper Security Director Cloud, the operational experience is as simple as managing one logical element, regardless of the quantities and form factors of any additional firewall engines added to the architecture.

AI-predictive threat prevention: Building on Juniper’s Adaptive Threat Profiling and Encrypted Traffic Insights, AI-predictive threat prevention automatically generates custom signatures unique to the customer’s environment through a proxy-less architecture. Coupled with AI, customers gain even more effective malware prevention at line rate.

Additionally, the enhanced URL filtering solution provides more granular control, with more than 200 categories to choose from and support for up to 200 languages, as well as a new portal for better insights on web content and easy recategorization.

The AI-powered security solution enables customers and partners to predict and find real threats faster, leaving human experts to focus on more strategic security tasks.

Four new best-in-class high-performance firewalls: The new Juniper Networks SRX firewalls (SRX1600, SRX2300, SRX4300, SRX4700) are 1RU in size, scale up to 1.4 Tbps and include built-in Zero Trust capabilities, delivering the industry’s highest firewall throughput performance per rack unit.

The new platforms feature wire-speed MACsec along with natively embedded TPM 2.0 chips and cryptographically signed device IDs that allow security administrators and network operators to easily verify the trust posture of devices remotely and mitigate the risks of supply chain attacks.

These new firewalls, like the whole SRX family, support industry-standard EVPN-VXLAN Type 5 integration, providing full fabric awareness to security operators and allowing them to respond to threats faster.

“A new modern data centre architecture is needed that delivers reliable automated operations and high-performing connectivity, all without sacrificing security within and between data centre locations,” said Praveen Jain, SVP and GM, AI clusters and cloud-ready data centre, Juniper Networks.

When combined with Juniper’s Connected Security Distributed Services Architecture, these additions to the Juniper SRX series family offer customers even more options to build and expand their data centre architectures securely and with sustainability objectives top of mind.

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From idling times to fuel economy comparisons, vehicle usage, cost savings, and beyond, Project G aims to deliver comprehensive, digestible information with ease.

By harnessing the power of natural language models, Project G reduces the time to insight for customers and transforms the process of analysing fleet data into a simple and intuitive experience. Project G is built on privacy-by-design principles and keeps all customer telematics data within Geotab’s environment, never shared with any Large Language Model (LLM).

In explaining the application of generative AI in the connected transportation landscape, Mike Branch, vice president of data & analytics at Geotab says the company's experience presents it with a unique opportunity to analyse vast amounts of fleet data, identify patterns, and generate invaluable recommendations to optimise operational efficiency and performance.

For his part, David Brown, assistant VP for APAC at Geotab says Project G opens doors to actionable insights, leveraging Generative AI to enhance vehicle performance, operational efficiency, and sustainability, ultimately shaping the future of connected transportation in SEA.

Over the past year, Generative AI has become a significant area of focus and organisations worldwide are exploring its potential to drive customer and performance business efficiencies. According to Statista, the value of Generative AI is expected to show an annual growth rate (CAGR 2023-2030) of 27.33%, resulting in a market volume of US$8bn by 2030 in SEA.

The region has also seen an extraordinary boost in AI adoption in 2023 with 76% of businesses now using AI in 2023 in a study done by IDC.

“The beta project is an exciting collaboration with select customers. We are able to align real-world requirements and challenges with data science expertise to learn, adapt and evolve capabilities. The possibilities are limitless, and we're committed to delivering cutting-edge solutions that make data easily accessible for our customers."

Mike Branch

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Nick Jones, distinguished VP analyst at Gartner said, “All five of these technologies are potentially transformational and should be investigated now due to their wide scope and ability to enable new business models or significant new capabilities.

“Everyone's definition of disruptive is different, however, so evaluate them from your organisation’s unique perspective and their potential impact. Then consider new business opportunities enabled by individual technologies, as well as combinations of them." (See Figure 1)

Figure 1: Five Technologies That Will Transform Your Digital Future

1. Satellite Communications

Increasing interest in low earth orbit (LEO) satellite communications is being driven by the democratisation and commercialisation of space. Low latency makes LEO an important technology for enterprises to revolutionise communications with people and things.

According to Gartner, LEO will deliver broadband with global coverage and low enough latency for a wide range of tasks; direct satellite connection for small IoT devices to provide affordable global coverage without involving SIMs, telco providers and roaming complications; and voice and data services from a satellite to an unmodified 4G smartphone to extend coverage to remote locations.

“The industry remains nascent, with a lot of evolution expected, so take a cautious approach to adopting LEO early as this is an emergent technology in a complex market,” said Jones.

2. Tiny Ambient IoT

Tiny ambient IoT enables tagging, tracking and sensing of anything without the complexity or cost of battery-powered devices. The result is the ability to unobtrusively sense more information, about more things, in more ways, at a lower cost than in the past.

This will enable new ecosystems; new business models based on knowing the location or behavior of objects; smarter products with new behaviors; and a much lower cost of tracking and monitoring. Tiny ambient IoT will expand opportunities for a wide range of businesses, but Gartner recommends assessing potential social and regulatory issues before adoption.

3. Secure Computation

Secure computation is becoming vitally important as things become increasingly connected and as ecosystems access more personal information. It enables data to be exploited without compromising privacy.

While many of the principles of secure computation are already established, implementation is challenging for reasons of cost, skills, performance and availability. To help overcome these, Gartner suggests emerging technologies such as optical accelerators will be important to enable deployment.

4. Digital Humans

Digital humans are interactive, AI-driven representations that imitate some characteristics, personality, knowledge and mindset of a human. They range from physical (e.g. humanoid robots) to virtual (e.g. virtual pop stars); or human-driven (e.g. mimicking aspects of a human) AI-driven where they do not need to be human-like in all aspects (e.g. a digital twin or chatbot).

Despite their potential, digital humans pose many challenges, including unethical applications; inappropriate behaviour; creation of bias and stereotypes; lack of regulation; risk of social backlash; varying cultural attitudes; and more. Gartner recommends assessing potential social and regulatory issues before adoption.

5. Adaptive Autonomic Drones and Robots

Autonomic systems are self-managing physical or software systems, performing tasks that exhibit autonomy, learning and agency (sense of own personal purpose). Systems that learn and adapt autonomously will be essential if technologies like robots are scaled to achieve their full potential.

However, a multitude of challenges exist as it may not be obvious what a robot or AI system has learned or what it can (or cannot) do. Gartner recommends piloting them in complex and rapidly changing environments, where early adoption will deliver agility and performance benefits. Manage risk by analysing the business, legal and ethical consequences.

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ABI Research says manufacturers can tie investments in GenAI to additional revenues with a significant spike of US$4.4 billion from 2026 to 2029. By 2033, revenue added from the use of generative AI in manufacturing will reach US$10.5 billion.

“Generative AI has growth that will derive from functionality and use cases across market verticals. The deployment of generative AI will come in three waves as the technology matures, with manufacturing seeing the largest revenue growth during the second and third waves,” explains James Iversen, manufacturing and industrial industry analyst at ABI Research.

He further posits that during the second and third waves of adoption, generative AI will be deployed into four domains of manufacturing: design, engineering, production, and operations.

Design will see the fastest mainstream deployment with use cases such as generative design and MBOM (manufacturing bill of materials) and EBOM (electrical bill of materials) reductions already having existing solution offerings from companies such as Siemens and Microsoft.

Engineering, production, and operations use cases will take longer and require further maturity from GenAI providers due to the complexity of the tasks and required model training.

Use cases for generative AI in manufacturing can be compared by looking at expected TTV (time to value) and ROI (return on investment). For the four domains, the top performers are:

Design: Generative design, part consolidation

Engineering: Tool path optimisation, part nesting

Production: Product quality root cause analysis, correction of bugged software code

Operations: Inventory stock and purchasing period management, employee work path optimisation

Both manufacturers and manufacturing software providers should prioritise top-performing use cases as they yield the highest returns and can be easily built out with existing GenAI capabilities.

Iversen opines that starting from the ground up, implementing these use cases will lay the groundwork for more extensive use cases.

"It is important not to jump the gun and develop high-functioning use cases that will see little implementation as trust in generative AI will need to be built up before overhauling significant portions of current manufacturing operations." James Iversen

James Iversen

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Under its ‘emerging technology testbed’ initiative, the City of Melbourne worked with Nokia to leverage an existing network of installed cameras as Internet of Things (IoT) sensors to monitor one of the compactors.

The Nokia Scene Analytics solution employs an AI-powered algorithm to filter and collate data from the cameras, while also combining other data sources, such as operational data on the compactor itself, to create real-time alerts and produce reports.

Initial tests show

Initial trial results demonstrate that Scene Analytics can support the City’s objectives for better, safer citizen experiences while simultaneously lowering maintenance and downtime costs for waste management services.

Lord Mayor Sally Capp, City of Melbourne, says the solution is a great example of using new technology to help remove illegal waste more quickly, make our city cleaner and protect the environment.

"This innovative project will help to avoid hazards and make our streets even cleaner by allowing our waste services to better understand behaviour trends related to the illegal and dangerous dumping of waste,” she continued. 

How the technology works

The trial allowed for real-time monitoring and detection of activity in the vicinity of the compactor using a virtual tripwire. Object detection and object counting was used to identify and count items to show how the compactor was impacted by items incorrectly placed within it, while also identifying potentially dangerous items.

Anomaly detection identified unusual movements, such as illegal waste dumping during the night, while face and license plate blurring maintained individual privacy during the trial.

Using these reports, the City of Melbourne can better understand the correlation between illegal waste-dumping activities and compactor downtime, to keep maintenance teams better informed and minimize issues.

It also allows them to swiftly address waste dumping activities before they become a hazard, viewing locations in real-time to observe any obstructions to service vehicle access, and adapting their schedule to reduce unnecessary visits and minimize their carbon footprint.

By understanding patterns of compactor usage and waste dumping activities, the city of Melbourne is also able to patrol the area more effectively, while developing an ongoing campaign to better inform and educate the community.

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A few data points from Gartner’s 2022 Supply Chain Technology User Wants and Needs Survey back up our findings. Before looking at some of the data, a key point to note is this study is cross-industry, cross-company size and cross-geography.

When asked if they were investing, or were planning to invest, in any form of cyber-physical automation, 97% of respondents said they were.

Of the respondents, 30% said that labour and talent issues were one of their top two internal challenges and 59% said that labour availability issues were leading them to consider automation.

When specifically asked about robotics, a staggering 96% said they were investing or were planning to invest, in robotics over the next two years, with 36% either fully deployed (7%) or actively deploying currently (29%).

Also, 93% of current robot users said that they planned to expand the fleet size of their existing robot platforms, with 94% saying they were pursuing additional use cases for robotics in their operations.

All this combined is why we believe the ISR market will continue to grow so rapidly. Because of this rapid growth, we also believe that 40% of large enterprises will have heterogeneous fleets of ISRs in their warehouse operations within the next five years.

So, the good news is lots of companies will begin to leverage ISRs in their operations. But this creates challenges for companies. Namely, how do they integrate with, and orchestrate the work of, a heterogeneous fleet of robots?

As companies deploy heterogeneous fleets of robots from different vendors performing various tasks, integrating with, and orchestrating the work of, this varied fleet of robots will require standardised software that can easily unite a variety of agents and robot platforms. Gartner refers to this emerging software as multiagent orchestration platforms.

These solutions act like intelligent middleware that integrates and orchestrates work between various business applications, heterogenous fleets of operational robots and other automated agents like doors or elevators.

These solutions will assign work to the right robots based on the characteristics of immediate tasks and will orchestrate communication between different robot platforms and other types of automation agents.

When companies invest in their first ISR platform, they will typically just create a one-off connection between their business applications — such as a warehouse management system — and their robot provider’s fleet management system.

This, while not optimal, works for one robot. However, as a company’s fleet of robots grows, simple point-to-point API integration will not be enough. Companies will need an orchestration capability that can assign work to the right robots based on near-real-time information that takes into consideration the characteristics of the activity and the capabilities of various automation agents.

This will reduce the time, effort and cost to onboard new robots and will reduce support costs, ultimately making organisations more efficient because work will be assigned to the robot best suited for the task.

Consequently, companies will need a platform that can help integrate with and orchestrate the work across their fleets of robots. Because of this, we believe that by 2026, more than 50% of companies deploying intralogistics robots will adopt a multiagent orchestration platform.

To achieve this, companies should start by analysing the integration requirements as the robot fleet expands beyond a single vendor. Along with that, they should study how work will be assigned to the various robots and other automation agents, like doors or elevators, and determine what orchestration logic will be needed to support this simultaneously.

First published on Gartner Blog Network

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Drivers of growth

With few alterations to the market structure, factory automation has developed gradually. However, due to technological disruptions, macro trends including reshoring, a worldwide shortage of trained workers, and environmental, social, and governance (ESG) initiatives, the rate of change is quickening.

Over the course of the projection period, it is predicted that the factory automation market will grow significantly because of the increased need for automation for reliable and high-quality production.

Additionally, industry participants are focusing on improving the manufacturing process efficiency to produce goods that are both affordable and of high quality, which has a big impact on the size of the factory automation market.

Factors influencing factory automation

The demand for factory automation solutions is driven by the development of 5G wireless technology and the adoption of Industry 4.0 in several industries, including fibre & textiles, infrastructure, plastics, pharmaceuticals, and others.

Industrial IoT, digital twin, and digitization The rise of teach-less robots, soft programmable logic controllers (PLCs), and digital twins are predicted to be the three major trends in the factory automation sector. This factor is expected to drive the Factory Automation Market.

Factories with fully functional automation systems will unquestionably outperform businesses with fewer or no robotics. Theoretically, those with the most advanced automation systems may generate more than three times as much as their rivals.

Systems that automate tasks can also operate for longer periods of time. Even if factories with fully developed automation systems must produce more complex items, this helps to boost the volume of output.

Additionally, since machines are programmed to operate with extreme precision and exceptional efficiency, automation systems guarantee that there is little room for human error throughout manufacturing. It is also known that one robot can produce at a rate comparable to three to five workers. This factor is expected to drive the Factory Automation Market.

Modern automation makes it possible for factories to run considerably more cheaply. Nowadays, a few individuals and a few robots produce goods instead of hundreds of workers on an assembly line.

Gaining a profit and a return on investment (ROI) will be simpler for businesses. Payroll, benefits, insurance, and sick leave costs can all be decreased by using more robots and fewer workers. This factor is expected to drive the Factory Automation Market.

The automation systems in factories can now be upgraded continuously to work in a more environmentally responsible manner. Modern systems are known to have a smaller environmental impact.

Modern machinery is more accurate and controlled, uses less power, and produces less waste heat. Machines can also be mounted on walls, which are typically underused in traditional factories and can be placed in tight corners to save even more floor space.

Additionally, it permits businesses to add more machines inside the plant. Additionally, robotics' accuracy reduces the amount of scrap produced during production. This factor is expected to drive the Factory Automation Market.

Not only will manufacturing be more affordable because of robots, but it will also be much safer. The days of factory workers accidentally hurting themselves while the product was being made are long gone. Humans are still required, but only to manage and supervise production, apply the finishing touches, and check and guarantee the quality of the final items. This factor is expected to drive the Factory Automation Market.

Market segmentation

The factory automation market is segmented by component (sensors, controllers, switches and relays, industrial robots, drives, others), control and safety system (distributed control system (DCS), supervisory control and data acquisition system (SCADA), manufacturing execution system (MES), systems instrumented system (SIS), programmable logic controller (PLC), human-machine interface (HMI)), and by industry verticals (automotive manufacturing, food and beverage, oil and gas processing, mining, others).

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A new ABI Research report forecasts this market will rapidly expand by 2030 at a CAGR of 162%, offering nearly US$60 billion in revenue for supply chain stakeholders.

“Capturing the enterprise commercial opportunity is essential as stakeholders continue to struggle beneath a significant cost crisis driven by the consumer segment. Building data sets, deploying infrastructure, training, and running large language models like Claude, LLaMa, Titan, or GPT-3.5 has a sizeable cost burden that will be challenging to reduce,” explains Reece Hayden, Senior Analyst at ABI Research.

He added that popular public applications like ChatGPT cost at least US$500,000 per day to operate. That cost will only rise as usage increases.

"So far, stakeholders have relied on external funding to support free access through venture capital investment or internal subsidies. This cannot continue forever, and stakeholders must identify strategies to start generating revenue in the consumer and enterprise segments,” he continued.

Given their high customer acquisition cost, stakeholders are primarily stuck in ‘freemium revenue models that are largely unsustainable in the consumer segment. “These models are also mostly unfit for purpose in the enterprise market,” Hayden points out. “Although moving on from this model will be challenging, the good thing is that plenty of monetisation opportunities have applicability across the supply chain.”

Stakeholders can look to implement advertising models like those used by search engines, revenue share models which have proven successful in adjacent areas like cloud marketplaces or even look to productise open-sourced LLMs with closed-source enterprise functions. But it is vital that stakeholders carefully align their capabilities with a revenue model as some may not be fit for purpose.

The most successful revenue generation strategies over the foreseeable future will look to support enterprise adoption directly. Most enterprises lack Machine Learning (ML) skills/tools, operational expertise, and strategic legal/governance frameworks to support generative AI development and implementation effectively.

For this reason, Hayden recommends, “Supply chain stakeholders should look to provide consultancy services or build low/no-code platforms that support development, deployment, fine-tuning, optimisation, operational change management, and day two operations.”

Business consultants like Bain, McKinsey, and BCG have joined system integrator incumbents through partnerships with foundation model owners like OpenAI. Moving forward, the enterprise service part of the supply chain could be worth more than US$15 billion by 2030.

Other factors are at play in this market, most notably the increasing focus on data privacy, which will trigger increasing interest in data service providers. Enforcement of copyright regulation for training data and enterprise demand for fine-tuning will create sustained interest in companies able to curate enterprise datasets or generate synthetic databases.

“Recent fundraising rounds indicate more significant interest in ML data companies. For example, Mostly AI, a synthetic data generator, has just raised US$25 million, while Snorkel AI recently raised US$85 million at a valuation of US$1 billion," Hayden says.

“The supply chain has plenty of opportunities to offset their cost burden with revenue models, and some are already looking to do so,” concludes Hayden.

“Beyond simply identifying new revenue models, stakeholders should look to build strong partnerships across the supply chain, build products/services that target B2B deployment and scale, and develop a leading position in responsible AI development.”

Reece Hayden

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Globally, automation will account for 25% of capital spending, and companies expect to reap rewards in terms of output quality, efficiency, and uptime. In Asia alone, the warehouse automation market is estimated to be worth US$10.76 billion and will reach US$23.89 billion by 2028. However, there are questions that need to be addressed when it comes to adoption, especially in terms of costs and level of understanding.

The survey highlighted another key challenge - the implementation of new technologies in setups consisting of legacy technologies and different interfaces. 42% of surveyed noted that they face challenges in (i) getting access to end-to-end solution providers capable of customising solutions to their needs.

There are concerns regarding the (ii) seamless integration of robotics into existing spaces and manned operations, and (iii) compatibility between machines and products. These concerns are compounded by (iv) the expected return on investments and (vi) the lack of implementation experience.

Overcoming barriers to automation adoption

This article details the potential solutions to enable companies in reaping the rewards of automated solutions.

In response to the lack of access to customisable solutions that support traditional warehouses, more global OEMs are establishing partnerships with robotics startups to offer innovative solutions. Their goal is to offer hardware and software solutions while providing a seamless operational experience and faster deployment in the warehouse.

To address the challenge of integrating robotics and automation into existing spaces and manned operations, companies could explore brownfield-friendly solutions that require minimal reconfiguration.

Essential features like real-time obstacle avoidance should be included in the chosen autonomous solution to enable safe operation within a hybrid environment of both manned and unmanned operations, optimising productivity while maintaining a safe and harmonious coexistence between human and machine-driven tasks.

Companies could also adopt intelligent warehouse control systems to ensure compatibility and interoperability between machines and products. By integrating diverse warehouse sub-systems and equipment into the control system, companies can then facilitate seamless coordination of workflows without manual intervention, thus resulting in increased productivity and throughput.

When it comes to costs associated with automation, there are two schools of thought. From a traditional ROI perspective, the upfront investment needed to automate processes might seem greater than traditional methods solely based on capital expenses.

However, an increasing number of companies acknowledge that the ultimate cost implications of not implementing automation can surpass the required initial investment. Through automation, businesses can enhance efficiency, mitigate risks related to labour scarcity, and ultimately attain long-term cost reductions.

Lastly, to address the challenge of a lack of implementation experience, companies could seek collaboration with experienced automation firms that have a good track record.

Starting with pilot and small-scale automation projects will allow companies to identify potential issues before scaling up. This process allows for a controlled environment where companies can learn, iterate, and fine-tune the implementation process for larger and more complex automation endeavours.

Enhancing scalability and adaptability through automation

Automation, driven by artificial intelligence (AI), machine learning algorithms, and integrated advanced sensors, optimises production schedules, allocates resources efficiently, and allows companies to swiftly respond to market conditions and unexpected disruptions, ultimately driving higher levels of productivity and output.

Without automation, companies risk relying on error-prone manual processes, leading to higher costs, extended production cycles, and difficulties in responding to changes in customer preferences or disruptions in the supply chain.

Embracing automation can be challenging, but partnering with like-minded intelligent solutions providers can pave the way for a successful business model, especially in today’s evolving business landscape.

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ABI Research forecasts that automated storage & retrieval system (AS/RS) revenues are expected to surpass US$15 billion globally by 2030, and warehouse management system (WMS) revenues are expected to exceed US$10 billion by the same period.

"Global supply chain challenges over the last three years have highlighted the need for digitalisation and a deeper restructuring of inventory management. Labour constraints, geopolitical trade shifts, and inventory gluts continue to pressure warehouse operations, and the most impacted organisations continue to be those with lower focus on digital transformations," states Ryan Wiggin, supply chain management & logistics industry analyst at ABI Research.

The present and future competitive landscape

AS/RS vendors, including AutoStore, Ocado, and Swisslog, as well as autonomous mobile robot (AMR) vendors such as inVia Robotics, Locus Robotics, and Vecna Robotics, are leading the structural automation charge.

Established and emerging WMS vendors such as Blue Yonder, Manhattan Associates, and Snapfulfil continue to add new functionalities to orchestrate and optimise both manual and automated workflows.

In addition to the growth in automation and management systems, high investment in hardware and devices is expected to increase worker productivity, as manual worker involvement remains necessary alongside the adoption of automated equipment. Global shipments of handheld devices for warehouse workers will grow at a CAGR of 20% to 2030, led by market leaders such as Zebra and Honeywell.

The new warehouse building is expected to drop by as much as 35% in 2023 compared to 2022. It is creating an even greater incentive to invest in the automation of current facilities to ease operational constraints.

Disruption to new developments will be short-lived, with steady growth in warehouse construction expected to 2030, led by a much greater CAGR in global e-commerce fulfilment centre development at 18%.

"Successful deployments by Tier One organisations continue to spur the adoption of technologies within small-medium enterprises. Solutions providers must continue to offer accessible adoption through as-a-service models and scalable structures, and exploring partnerships with complementary technology will be key to deploying market-leading end-to-end solutions," concludes Wiggin.

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IoT connectivity plays a crucial role in the efficient functioning of smart homes, smart cities, and various industry verticals, including healthcare, manufacturing, and transportation. ResearchandMarkets forecasts the IoT connectivity market to reach US$720.37 billion by 2028, growing at a CAGR of 20.6% between 2023 and 2028.

With the continued deployment of IoT devices and sensors, bandwidth will become a major challenge for organisations. IDC estimates that total data generated by IoT will reach 175 zettabytes (ZB) by 2025, potentially straining networks that serve consumers, businesses and governments, and now machines.

Soracom launched three new services designed to help IoT deployments take advantage of the power and promise of generative AI (GenAI). The three services can work together or separately to analyse IoT device data on the fly or connect devices to the powerful AI/ML capabilities now available through leading hyperscale platforms.

Soracom Relay lets customers use any existing RTSP/RTP-compatible camera to acquire and securely transmit audio and video data to Soracom’s Harvest Files for storage or to a cloud destination, such as AWS S3 or Amazon Kinesis Video Streams, for computer vision and video analytics.

Soracom Query lets customers use SQL queries from BI tools or CLI to mine IoT device data with no need to set up their own servers or storage. This managed data warehouse capability with automatic data loading makes it easy to run complex analytical queries on large IoT datasets and feed the results to machine learning (ML) projects.

Soracom Harvest Data Intelligence enhances Soracom’s existing serverless data storage and visualization capability with the ability to apply GenAI to analyse time series data and identify trends, patterns, outliers, and abnormalities. It can also use the data provided to perform further analysis.

For example, a municipality can use Soracom Relay to monitor road traffic while Harvest Data Intelligence analyses the data stored and Soracom Query can guide decisions on the best times to schedule road repairs, or to predict how changes in traffic patterns will impact existing infrastructure.

Soracom has also established an IoT x GenAI Lab with Matsuo Institute, which conducts research and development projects in AI sharing the vision of Matsuo Lab, University of Tokyo. The IoT x GenAI Lab will explore the potential to gain new insights from diverse IoT data using Gen AI, develop new products, and provide professional services specialising in the area of Generative AI, including IoT and Large Language Models (LLMs).

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The focus of this partnership will be delivering asset health and energy efficiency insights to a broader audience of industrial players. Its initial target industries are oil and gas and water and wastewater sectors in key global markets, including the US and Australia.

Samotics’ SAM4 technology supports global industrial players to monitor the performance and efficiency of critical assets. SAM4 is a proven, scalable solution, already helping over 100 customers on five continents to make data-driven decisions and improve performance.

It solves a significant challenge for industrial organizations, including those in water, steel and chemicals, by enabling the remote capture of high-quality performance and efficiency data for assets in hard-to-reach, submerged and hazardous locations.

According to Peter Mann, a director at Partners in Performance, the partnership will allow it to help its global clients improve asset performance while accelerating their energy transitions since they have a safe and effective way of identifying energy-inefficient equipment.

"With their (Samotics) machine learning algorithms in our arsenal, we can help increase operational efficiency, reduce maintenance costs, all the while creating safer working environments for people by identifying potential issues before they can become a hazard,” he continued. 

This makes it an attractive offering for Partners in Performance industrial client base, who are looking for an end-to-end solution to support their digital transformation and energy transition efforts.

Jasper Hoogeweegen, CEO at Samotics said: “Our SAM4 technology is already delivering significant value to industries, helping to identify developing faults and meet carbon reduction goals. With our joint commitment to solving reliability and energy efficiency challenges, Partners in Performance is a great partner to help scale global adoption of our proven technology and bring these benefits to more organizations around the world.”

Two unique solutions from SAM4

SAM4 Health analyses current and voltage signals of electric-driven equipment such as motors and pumps to detect electrical and mechanical faults.

Using electrical signature analysis (ESA) and machine learning, SAM4 Health offers superior fault detection accuracy, detecting over 90% of failures up to five months in advance.

Used to continuously monitor industrial equipment efficiency, SAM4 Energy provides detailed performance and efficiency insights to identify where energy consumption, cost and efficiency losses are largest and implement data-driven recommendations.

The post Partnership to tackle industrial DX and energy transition efforts appeared first on FutureIoT.

The process will mean partnering with government agencies and academic institutions to grow their A.I. research & development team.

Through its partnership with the Singapore government, Praveen Penmetsa, co-founder & CEO of Monarch Tractor, says the company can provide more job opportunities and "propel our mission for a greener future. More than ever, farmers, government bodies and consumers are looking for more viable options to sustain our planet."

Building upon Singapore's early success in developing the MK-V's driverless capabilities, Monarch's expansion and development of new talent will work to create automation capabilities that extend to entire farm operations leading to the enablement of profitable and sustainable agricultural practices within the region and globally.

As almost 25% of global GHG emissions result from agriculture, this strategic expansion will champion and enable large-scale emissions reductions that support Singapore's Green Plan 2030, including the country's aspiration to become net zero by 2050.

Monarch is currently hiring talent throughout Singapore to support and develop cutting-edge A.I. robotics technology - creating a smarter, greener and safer farming industry.

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State of Metaverse interest

The metaverse at work study shows that companies believe in the power of the metaverse and that metaverse technologies are here to stay. Only 2% of respondents see the metaverse as a buzzword or a fad, while 58% of companies with future metaverse plans have already deployed or piloted at least one metaverse-related use case. Among those who have yet to begin their metaverse journey, 94% plan to do so in the next two years.

Companies also say the industrial metaverse is creating substantial business value. On average, 80% of those who have already implemented metaverse use cases believe they will have a significant or transformational impact on the way they do business.

The study notes that 96% of respondents see how, by mixing physical and virtual use cases, the metaverse brings additional innovative capabilities that will allow them to accelerate the deployment, adoption and monetization of Industry 4.0 for their business.

In terms of geography, the US (65%), UK (64%) and Brazil (63%) are currently leading the way when it comes to having deployed or piloted at least one industrial or enterprise metaverse use case. The average in Germany was 53% while Asia Pacific is less advanced (Japan, 49%; South Korea, 49%).

Use cases

When asked which use cases they most expect to deliver transformative value, enterprises saw the highest potential in the use of extended reality for training to onboard and upskill the workforce, while three out of the four industries surveyed chose the use of virtual R&D to enhance product design and processes.

When deploying metaverse use cases, companies clearly appreciate the need for sufficient infrastructure and robust analytical capabilities. Respondents placed the highest importance on the key technical enablers that are truly foundational to meeting the demands of such use cases – cloud computing (72%), AI/ML (70%) and network connectivity (68-70%). Given the need for further technical expertise in-house, at this stage enterprises are relying on a range of partners to close capability gaps and deploy use cases.

Vincent Douin, executive director of business consulting and business transformation with Ernst & Young says the industrial and enterprise metaverses are here, this study shows the clear appetite for these technologies such as extended reality and digital twins to achieve business goals.

"We are already seeing many organisations going above and beyond the planning stages and recognising tangible benefits from their initial implementations,” he claims.

For his part, Thierry E. Klein, president of Bell Labs Solutions Research, Nokia notes that the metaverse interest in the private sector strongly aligns with the company's vision that sees the Industrial Metaverse as an extension of Industry 4.0.

"Consequently, those who have already implemented mission-critical communications networks for Industry 4.0 are now well placed to experience the benefits of the Metaverse that clearly some companies are already seeing,” he concluded.

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Putting your thoughts into paper is not easy, especially if this is your first time. Fortunately, technologies like Generative AI, or in this case, ChatGPT, are providing to be easy to use tools to help generate that business plan.

In this video, Sunder Somasundaram, SVP for Fleet & Industrial Verticals, IoT Solutions at KORE WIreless, uses ChatGPT to ideate an IoT business.

The post Use ChatGPT to build a business case for IoT appeared first on FutureIoT.

Organisations have set up their digitalisation departments and created positions such as the Chief Digital Transformation Officer. For guidance, many rely on consulting firms, which happily charge high hourly rates to develop “strategic digitalisation frameworks.”

Many companies start their digital transformation by buying software: Laboratory Information Management (LIMs) systems for R&D, for example, or manufacturing execution systems for factories, plus various types of customer service software.

But what does all this software do? Captures data from business practices, sure. Makes it all permanent, accessible, and sharable – yes.

But will it fundamentally change business practices? Will it, as the consultants like to say, add value to the final product or service?

Too often, digital transformation is an easy sell that does little (or nothing) to change the status quo.

What are we trying to transform?

Digital transformation is frequently confused with digitisation, but they’re not the same thing.

Digitisation is simply converting information into a digital format. This has value: it makes information easier to share, trace, and analyse.

But digitalisation shouldn’t just be about going paperless. It’s a trajectory or path.

That path starts with getting different elements of the business interconnected so that data becomes easier to collect. It culminates in the organisation’s acquiring better decision-making capabilities because of analysing the data it has collected.

We believe that less than 5% of “digital solution companies” can deliver actual digital transformation. Most offer plain digitisation.

So, what does the real thing look like?

The strategic use of real-time data and wireless connectivity is key to transforming the way a warehouse is run. For example, Thingple’s electronic warehouse management system (E-WMS system), doesn’t just digitise warehouse stock data. It simplifies and replaces previous operational processes to track goods flowing into and out of a busy warehouse.

Instead of physically searching for space in a large warehouse, operators need only view the 3D digital twin of a constantly updated stockpile in the warehouse to find vacant slots.

With real-time data on hand, an artificial intelligence (AI) system directs forklift operators to pick the right goods every time – and advises on the timely movement of goods to avoid expiry.
Real digital transformation, in short, should lead to increased efficiency and productivity, fewer manpower requirements, less waste, and less human error.

Digitalisation is about changing how business gets done

Ironically, digital transformation isn’t really about technology. Rather, according to the MIT Sloan Management Review, it’s about “how technology changes the conditions under which business is done, in ways that change the expectations of customers, partners, and employees.”

And here’s the cruel truth: most digitalisation efforts fail – 84% of them, according to one estimate.

Weighed down by the need for copious data entry, and hobbled by a lack of interoperability across platforms, most digitalisation projects don’t deliver the hoped-for transformative results.

For that reason, we need to look at digitisation differently.

Start with a clean slate and ask what’s the best digital tool for revolutionising your business operations. Can you leverage advances in sensor technologies, computing, automation, or AI to improve your operations – in ways that change the expectations of your customers?

Since digital transformation’s purpose is to help improve businesses in meaningful ways, DX companies with deep industry insights/experience tend to offer better, more targeted solutions. Cloud infrastructure providers like Amazon Cloud or Huawei Cloud, for example, can partner with industry-specific solution providers to offer insightful value to industrial clients.

The question should not be, “How do I digitise my company’s operations?” but, “How can I improve operations through technology? How to use tech to enhance efficiency, output, and added value?”

So if you want to digitalise, start by figuring out how technology can help you do those things.

Avoid digitisation – the mere conversion of paper into bits and bytes – and the adoption of digital technology for its own sake.

First published on Transform by Huawei Technologies

The post Digital transformation, not digital duplication appeared first on FutureIoT.

IoT architects often focus on IoT infrastructure (e.g., IoT endpoints, gateways and platforms) and defer consideration of how they will integrate ML inference into their design. They may not be familiar with ML well enough to know when it could help them solve their business problems. That means they neglect the opportunity to use ML when it would be useful. They also lack sufficient knowledge of data science technology and terminology to understand how to deal with the challenge of ML integration.

Data scientists often focus on building ML models (e.g., data preparation, training and algorithms) and neglect consideration of how the models should be integrated with operational systems. They often lack sufficient knowledge of IoT technology and design to understand how the integration of ML will impact IoT architecture.

Role of The Machine Learning Inference Server

An important development in machine learning is the emergence of ML inference servers (aka inference engines and inference servers). The ML inference server executes the model algorithm and returns the inference output (see Figure).

The ML inference server accepts input data from IoT devices, passes the data to a trained ML model, executes the model and returns the inference output.

The ML inference server requires that your ML model creation tools export the model in a specific file format that the server understands. For instance, the Apple Core ML inference server can only understand models that are stored in the .mlmodel file format. Perhaps you plan to deploy a model to the Apple Core ML inference server, but your data science team used TensorFlow to create the model. In that case, you will need to use the TensorFlow conversion tool to convert the model to the .mlmodel file format.

The Open Neural Network Exchange Format (ONNX) will help to improve file format interoperability between ML inference servers and model training environments. ONNX is an open format to represent deep-learning models. There will be greater portability of models between tools and ML inference servers as vendors increasingly support ONNX.

New Gartner Research

New research from Gartner helps technical professionals overcome the challenge of integrating ML with IoT.  It analyses four reference architectures and ML inference server technologies. IoT architects and data scientists can use this research to improve cross-domain collaboration, analyse ML integration trade-offs and accelerate system design. Each reference architecture can be used as the basis of a high-level design or can be combined to form a hybrid design.

First published on Gartner Blog Network

The post Driving hyper-automation in manufacturing appeared first on FutureIoT.

“Global robot installations grew tremendously throughout 2021 and have continued to do so in 2022, reaching record levels for industrial and collaborative robots,” explains ABI research director Lian Jye Su. He concedes that this recent boom is expected to fade a bit in 2023 due to the ongoing war in Ukraine and inflation.

In this PodChats for FutureIoT, Su discusses the latest trends in industrial automation, artificial intelligence and robotics in Asia.

1. Describe the state of industrial automation in Asia in 2023?
2. How has robotics technology evolved in recent years? (types and applications)
3. Beyond Korea and Japan, how are other markets in Asia adopting/deploying robotics?
4. Most “hardware” robotics use cases are designed to perform a single specific task (for example moving goods or welding components). As AI and machine learning matures, do you ever see robotics taking on more sophisticated functions?
5. Are cobots a sign of things to come?
6. In IT, we’ve seen the rise of “as-a-service”, what will robotics-as-a-service look like?
7. The terms industrial IoT, industry 4.0 and robotics – how are all these connected?
8. Where are the hurdles in the evolution of robots or robotics in industrial applications?
9. What is your advice for organisations looking to integrate advances in robotics into operations further?

The post PodChats for FutureIoT: Industrial automation trends in Asia appeared first on FutureIoT.

This new capability leverages the ecosystem of Siemens Xcelerator, an open digital business platform that enables customers to accelerate their digital transformation easier, faster, and at scale.

NXpower Monitor enables the visualisation and monitoring of electrical assets within electrical networks, providing health status, KPI calculation, energy monitoring, and monitoring of operational data from assets.

This asset monitoring system enhances efficiency and risk management across the entire energy distribution network through continuous health monitoring, while simultaneously minimising CO2 emissions and OPEX.

By integrating AI-powered ESA technology, Siemens broadens its application to include the monitoring of AC motors and rotating equipment, all accessible through a single pane of glass.

“The digitalisation of energy distribution, automation systems, and networks brings many advantages," says Stephan May, CEO of electrification and automation at Siemens Smart Infrastructure.

He added that not only does it lead to substantial savings in terms of time and money, it also significantly boosts efficiency and reliability.

"By adding Samotics to Siemens Xcelerator, our open ecosystem of certified partners, customers can benefit from an expanded offering. This reflects our continued innovation efforts, including the integration of advanced low voltage analysis into our digital caretaker NXpower Monitor,” said May.

The integration of ESA technology enables NXpower Monitor to conduct real-time analysis of high-quality current and voltage data, enabling the detection of electrical and mechanical faults up to five months before downtime happens. The system is also able to deliver comprehensive performance and efficiency insights, pinpointing areas with the highest electricity consumption, cost, and efficiency losses.

By implementing data-driven recommendations, organisations can optimise operational processes, significantly reducing energy waste and cutting CO2 emissions by up to 15%.

Samotics CEO Jasper Hoogeweegen says: "Unplanned downtime and energy waste are among the most expensive problems in the industry. Traditional monitoring technologies do not adequately address these issues.

He explains that through partnerships with forward-thinking organisations such as Siemens, customers are benefiting from ESA technology that delivers real-time, actionable information about the condition, performance, and energy efficiency of critical rotating equipment. "This helps our clients to effectively improve the performance and energy efficiency of their critical assets,” he continues. 

The post NXpower Monitor gets AI-driven ESA from Samotics appeared first on FutureIoT.

As retailers deploy Micro-Fulfilment Centres (MFCs) to augment their distribution networks, automated picking solutions provide the speed and space maximization necessary for e-commerce efficiency and profitability.

ABI Research says Automated Storage & Retrieval System (AS/RS) revenue within MFCs is expected to reach US$1.2 billion by 2027, with uptake primarily seen in the grocery and fast-moving consumer goods (FMCG) industries.

“The need for high-density storage and fast fulfilment capabilities allows technologies to scale down and enable a flexible, bespoke frontline distribution network,” said Ryan Wiggin, supply chain management & logistics industry analyst at ABI Research.

He added that in addition to automated high-density storage systems, retailers are also looking to enhance manual picking operations to deliver micro-fulfilment solutions using handheld devices and Goods-to-Person (G2P) mobile robots.

"With over 2/3 of MFCs currently deployed in or alongside existing stores, micro-fulfilment solutions are helping retailers re-imagine how they utilize their current infrastructure to support online delivery."

Ryan Wiggin

Delivery times are getting faster, down to a matter of hours for certain products. As demand for alternative shopping experiences like click-and-collect increases, customer attraction and retention rests heavily on effective inventory management and localized delivery capabilities.

A few critical solutions vendors have emerged offering dedicated micro-fulfilment packages, including Alert Innovation, Dematic, Swisslog, and Takeoff Technologies, while companies like Ocado Group are offering MFCs as an additional arm to their existing warehouse automation solutions. Most solutions are underpinned by cube or shuttle-based AS/RS, orchestrated by management systems increasingly incorporating artificial intelligence (AI) capabilities.

Store and warehouse workers are being equipped with more sophisticated handheld devices from companies like Zebra as retailers look to deploy manually operated MFCs within existing stores or facilities and help optimize online order picking. And Autonomous Mobile Robots (AMRs) inVia Robotics, 6 River Systems, and Locus Robotics are seeing deployment in MFCs as an alternative to stationary G2P automation.

Wiggin commented that in industries where online delivery has notoriously been an unprofitable venture, localised, automated MFCs are greatly helping to reduce both cost and picking time.

U.S.-based industry giants like Nordstrom, H-E-B, and Walgreens are leading in MFC solutions adoption. In Asia-Pacific and Europe, MFC solutions vendors are gaining traction signalling wider implementation of automated micro-fulfilment.

"End users must assess current network requirements and understand where micro-fulfilment solutions could offer significant value. Technology vendors must ensure that solutions can be scaled and be adaptable to retailer’s requirements,” concluded Wiggin.

* Editor's note: Comments and stats provided by ABI Research.

The post Retailers deploying micro-fulfilment centres to meet customer demand appeared first on FutureIoT.

Wireless networks are a key foundation for businesses and essential to the IT infrastructure of their systems. But they’ve been mistaken as mere operational technologies for too long. Today, they’re enabling real-time insights and changing the connectivity game.

Usage is growing exponentially, and in Asia-Pacific, industries including manufacturing, logistics and transportation and healthcare will present the biggest opportunities for private 5G networks. According to some reports, out of all the potential deployments, these three industries are expected to account for over 60% in 2025.

For those still considering a private network option, untapped potential awaits. Private wireless networks offer greater control and security, while also acting as conduits for data that enables AI and ML.

This technology provides high-speed coverage across large industrial settings, boosts worker safety and productivity, increases business efficiencies, and enables a wide range of new capabilities including augmented reality applications, autonomously guided vehicles, precision robotics, and the ability to generate real-time actionable data to make better-informed business decisions. 

And when it comes to the future of private wireless networks, the opportunities to create value are just beginning.

The potential of private networks

Traditional Wi-Fi for connectivity was largely reliant on collaboration with service providers. A private network, on the other hand, is one built on spectrum frequencies reserved exclusively for a customer environment that uses technology leased from a carrier or another spectrum owner, such as a government.

Private networks allow businesses to gain independence from telecom service providers and take full control over managing their networks. They can determine exactly what can connect to the network and how. It’s even possible to set usage policies around what a device can access once it’s on a private network.

Going down this route not only gives companies the control they need to adapt their network for their individual use but is also a cost-effective solution. When it comes to savings, the total cost of ownership (TCO) of private networks is considerably lower than traditional wireless networks and enables enterprises to better prioritise operational costs and remain agile with faster deployment of applications.

Private networks can be especially useful for industrial environments where Wi-Fi connectivity may be spotty and difficult to deploy. They help solve the problem of black spots, for example, where the signal is too weak or unstable to maintain connectivity.

Black spots can be caused by interference, physical obstruction, and distance — all issues private networks seek to alleviate. As such, they can be extremely valuable specifically around industrial settings that have highly reflective environments or sites that are difficult to reach with traditional networking infrastructures.

Private networks also provide substantial security benefits. They allow organisations to apply more advanced measures, including SIM-based authentication methods and strong air interface ciphering. They enable the allocation of security roles by devices, making it easier for businesses to control their systems and stay secure.

These wireless environments and the devices they control represent critical functions. Therefore, any attempt from malicious actors to interfere or sabotage needs to be dealt with with a robust security system, which can only be attained through a private wireless network.

Private networks in action

When it comes to application, some of the customers we’ve worked with have demonstrated the benefits of implementing private networks. For example, Dow Chemical, a multinational materials science company with multiple presences in ASEAN, recently undertook its journey to deploy a private network.

The organisation has been digitally transforming its manufacturing operations for more than a decade, and one of the primary issues this transformation aimed to solve was improving and streamlining the process of operations and maintenance tasks.

Dow Chemical wanted to ensure that the necessary information was available and at the fingertips of the front-line professionals, for them to interact, collaborate, and solve problems with precision and promptly. Ultimately the goal was to enable operations teams to work more efficiently and safely, whilst increasing plant productivity and reliability.

Initially starting with a proof-of-concept, in 12 months, Dow worked together with Kyndryl and Nokia to fully deploy and scale a private wireless and edge network at the largest integrated chemical manufacturing complex in the Western Hemisphere, spanning over one million square feet.

The real-time digital transformation enabled augmented reality applications, remote audio and video collaboration, real-time smart procedures, on-site personnel tracking, better worker safety, and vehicle telematics.

Given ASEAN’s status as one of the world’s top suppliers of raw mineral and metal products, this makes it a prime candidate for the implementation of 5G networks. The high bandwidth and low latency of 5G will enable the delivery of new services that were previously unattainable.

Similar to Dow’s experience, 5G has the potential to open up a new level of automation, operational efficiencies, and sustainable growth for ASEAN’s organisations by unleashing the untapped power of AI, data analytics, IoT and cloud computing.

Partnership for success

Despite the benefits private networks can provide, technology leaders are sometimes reluctant to adopt private 5G networks. Some misconceptions installing private 5G networks will require an overhaul of a company’s existing digital infrastructure, disrupt operations, or there may be a knowledge gap about the availability of spectrums and the benefits of 5G private networks.

To ensure wider and seamless adoption across industries, enterprises must understand the spectrum they’re going to use and match it to the technologies they’re going to deploy. They should select a partner who understands how to secure the spectrum in the country, as well as how to integrate with the local area network, wide area network and the public cloud, so the data can be transferred and analysed.

Select a trusted and informed partner to help secure the right spectrum, as industries are often unaware of what’s available to them. A good partner will guide the organisation in finding what is available and works for them.

The future of intelligent networking

While there are certainly challenges associated with deploying wireless solutions, it’s a critical technology for driving digital transformation and a catalyst for business growth. As advanced wireless technologies such as Wi-Fi 6 continue to develop, we should also expect a rise in hybrid approaches to connectivity. A one-size-fits-all solution just won't work.

As the number of connected devices in the industrial environment continues to increase, it will be paramount for ASEAN organisations to deploy private 5G networks to drive insights from their vast amount of data.

Private wireless networks will prevail across industries and become an integral part of enterprise infrastructure. In the next five years, as organisations look back and reflect, they’ll realise the gains from tapping into the potential of private wireless networks.

The post The transformational potential of private 5G wireless networks appeared first on FutureIoT.

This 44% growth reflects how smart meters are becoming critical to increasing the efficiency of energy grids via analytics; central to lowering costs to customers during the energy price crisis.

A smart meter records energy usage and leverages onboard connectivity to upload this data to energy suppliers.

Hong Kong is in the top 5 of most smart metre rolled outs

By 2027, the research forecasts Italy will have the highest household penetration rate of smart meters globally, at almost 100%. Italy has had mandatory smart meter installations since 2006, setting an example for the wider market. The top five countries were ranked as follows:

Italy (99.6%)

UK (98.7%)

Saudi Arabia (98.4%)

Hong Kong (98.4%)

UAE (97.4%)

The research recommends utility companies focus on educating consumers on the benefits of smart metering, as these benefits are often unclear to them. Utility companies should focus on the potential for saving energy, with evidence-based use cases to catalyse adoption.

Key opportunity for IoT

The smart grid network encompasses local area networks, home-area networks, access networks, clusters of connected LANs and HANs called NANs, and wide-area networks.

The research found that, with over 1.8 billion smart meter connections forecast to be in use by 2027 globally, smart meter connectivity represents an important opportunity for cellular networks and low-power IoT connectivity. The low data usage of smart meters lends itself naturally to low-power IoT, but as cellular networks are the only networks capable of providing ubiquitous access in some markets, they clearly still have a role.

Report co-author Nick Maynard explained: “While smart meters have come a long way in deployment terms, they are only as good as the connectivity they leverage. Utility companies must aim to aggregate the best networks for their locations, or they will fail to obtain the benefits smart meters can readily provide.”

The Juniper Research paper, Combating the Energy Crisis with Smart Grids, concludes that investing in smart grid deployment yields significant benefits for the environment and society. These benefits are summarised below.

The post Data analytics critical to lowering power consumption appeared first on FutureIoT.

Frost & Sullivan’s Sensor Technologies Impacting the Physical and Digital Security Market predicts that by 2025, there will be a significant increase in the use of contactless sensing technologies for physical and digital security applications, including cameras, LiDAR, and terahertz (THz) image sensing.

Critical assets like personal identity and biometrics are protected by security sensors integrated with other emerging sensor technologies, like LiDAR and THz.

“Sensor technologies, drones, robotics, and internet of things (IoT)-enabled devices will fuel the adoption of security systems, offering safety and security advantages,” said Varun Babu, TechVision industry analyst at Frost & Sullivan.

“Additionally, security sensors integrated with other emerging sensor technologies, such as LiDAR and THz sensors, provide highly safe and sophisticated security to critical assets like personal identity and biometrics.” Varun Babu

He added that sensor technology providers must work closely with security software solution providers to build a robust, user-friendly security management system.

“Further, they should build strong partnerships and jointly develop video surveillance management systems to overcome internal technology development barriers in the next two or three years,” he predicted.

Opportunities ahead

Frost outlines vertical markets that are wide open to the adoption of sensors, particularly in security applications such as:

Artificial Intelligence (AI): With AI, security professionals can pre-emptively spot defective equipment like security cameras and analyze alarms from defective devices. It helps lower the chances of cyberattacks.

Machine learning (ML): Physical and digital security manufacturers and service providers can create security and video monitoring systems that dynamically notify users of abnormal activity using ML.

Robotics and drones: Mobile drone surveillance can monitor criminals on the road and help avoid or reduce deadly pursuits. Drones are also safer and offer a significant investment return over traditional surveillance.

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This growth of 91% will be driven by the advancement of both ADAS (Advanced Driver Assistance Systems) and increasing the capabilities of in-vehicle infotainment systems. The research identified 5G’s high speed and low-latency capabilities as transformative to these goals, requiring effective collaborations between automotive OEMs and operators to realise.

Connected vehicles are equipped with communication technologies that allow the exchange of information between the various elements of the transport system and third-party services.

The research found that operators are critical to unlocking new use cases, such as autonomous driving and data-heavy infotainment via 5G; representing a US$3.6 billion opportunity for providing 5G connectivity enablement in 2027 globally.

Research co-author Nick Maynard explained that 5G can allow automotive OEMs to upgrade the in-vehicle experience. In a vehicle market transitioning to electric vehicles, improving the user experience is key.

“Operators hold the critical role in enabling this in a reliable way, making them the partners of choice as their 5G networks rapidly expand.”

Nick Maynard

Commercial use cases lagging behind

The research predicts that by 2027, commercial vehicles will only account for 20% of connected vehicles worldwide, representing a small increase from 16% by the end of 2023.

The research found that commercial vehicle design is not leveraging connectivity beyond simple emergency call features and basic connected infotainment systems, although this is changing, as businesses prioritise tracking and logistics capabilities.

The research recommended that automotive OEMs prioritise integrations with common fleet tracking systems out of the factory to maximise the benefits of connectivity, and to enable commercial fleet owners to maximise efficiency in their processes.

The post Operators critical to unlocking the connected vehicle future appeared first on FutureIoT.

But while electric vehicles have been heralded as one of the key innovations of our times to support efforts to curve the effects of continued use of fossil fuels on the environment (aka climate change), the challenge for road warriors and operators of public transport services, including taxis, is the lack of enough charging stations to keep vehicles moving.

With the anticipated rollout of more electric vehicles (EV) in the coming years, HERE Technologies announced a new service that predicts the likelihood of an electric vehicle (EV) public charge point is available in the future.

The charge point prediction feature is novel in its capacity to incorporate both EV infrastructure supply and real-world user demand while factoring in variables such as weather, time, and day. This addition supplements HERE EV Charge Points offering that has been deployed globally with many automakers.

HERE EV Charge Points’ prediction capability uses an applied machine learning (ML) algorithm that weighs GPS probes, and vehicle sensor data and correlates historical time/day, weather, and traffic pattern data. This enables HERE to have a granular view of EV charge point user patterns and surrounding traffic conditions. The volume of real-world data provides a virtuous loop of ML training data for HERE to continually improve the prediction service.

“EV drivers are navigating a patchwork of infrastructure, with various plug types, pricing, and little understanding of when a charge point is occupied,” said Chris Handley, vice president of dynamic spatial content at HERE Technologies. “This feature is focused on delivering a much-needed tool for EV drivers to more confidently plan their day and waste less time on charging.”

With the new charge point availability prediction, drivers will have greater visibility into whether the charge point will be available by the time they arrive for a charge up.

The post HERE to make it easy to find the nearest EV charging points appeared first on FutureIoT.

The Deloitte report, 2023 manufacturing industry outlook, predicts that manufacturers will likely continue progressing toward smart factory transformations, as these initiatives drive future competitiveness.

Many manufacturers are making investments in laying the technology foundation for their smart factories. One in five manufacturers is already experimenting with underlying solutions or actively developing a metaverse platform for their products and services.

Trends influencing ASEAN’s manufacturers

According to Euromonitor International’s Voice of the Industry: Digital survey, around 62% of companies globally plan to increase their investment in cloud computing over the next five years, while around 50% of companies plan to invest in Artificial Intelligence, the Internet of Things and production automation tools.

Pavan Mahajan, VP of solutions delivery for APAC at Belden observes that the adoption of Industry 4.0 technologies gaining momentum among manufacturing companies in the region. He attributes this trend to manufacturers seeking to accelerate their journey towards full digital transformation.

Boston Consulting Group observes that harnessing Industry 4.0 will be key in helping the ASEAN manufacturing sector become more competitive and move up the value chain, with Singapore, Malaysia and Vietnam among countries that are already investing in smart manufacturing solutions such as smart factories, industrial IoT, advanced robotics, and cloud computing.

“Customers are beginning to embrace the desire for digital transformation and are looking to transform their manufacturing ecosystem with industrial automation and smart solutions,” added Mahajan.

Industry 4.0 investment priorities

According to Justinas Liuima, insights manager, industrial with Euromonitor International, says to partly solve the problem and compensate for rapid wage growth, companies are forecast to accelerate their investment in production automation tools in 2023.

“Production automation in many cases could be the only viable option for companies to ensure productivity growth,” opined Liuima.

Mahajan says among Belden’s customers in the Asia-Pacific (APAC) region, a key investment area is IT/OT convergence.

IDC predicts that by 2024, 50% of industrial organisations will be integrating data from edge OT systems with cloud-based reporting and analytics, moving from single-asset views to sitewide operational awareness. The IT/OT convergence market in APAC is estimated to develop at the highest CAGR of 7.1% from 2022 to 2027, from US$49,195 million in 2021 to US$73,523 million in 2027.

“As data becomes increasingly crucial for manufacturing companies to solve business challenges and achieve greater operational efficiency, performance, safety, and profitability, having access to an optimised, convergent network is key,” noted Mahajan.

With both IT and OT data available, he opined that companies could collect, move, integrate, and analyse data to automate processes and make better, more informed business decisions. “The additional capabilities in an IT/OT converged network, such as edge computing and analytics, will also usher in even greater opportunities for productivity and problem-solving,” he added.

Mahajan said that another key area of investment for manufacturers is in edge-to-cloud environments, especially edge technologies. We are seeing a higher level of acceptance and readiness among our manufacturing customers to invest in industrial edge solutions, with an increasing adoption rate over the past two years.

This is happening worldwide as well as in APAC, with GlobalData predicting that the global edge computing market will reach US$17.8 billion by 2025, with APAC sales accounting for 26.4%.

“As Industrial IoT (IIoT) and Industry 4.0 continue to gain momentum, investing in industrial edge capabilities will be key in enabling fully connected operational systems, reducing latency and cost of data processing while maintaining security and communication with the cloud,” concluded Mahajan.

Core competencies needed to benefit from Industry 4.0 innovations

Katarzyna Grzybowska and Anna Łupicka, authors of the report, Key competencies for Industry 4.0, noted that the demand for special skills will drive the shift of job creation within Industry 4.0 requiring more qualified managers.

For his part, Mahajan believes that to benefit from industry 4.0 manufacturers will need to have skills in network security, and data management and governance.

“The expanded, highly connected networks with more data transmission points, which are characteristic of Industry 4.0, create a greater need for security. This only grows with the integration of cloud computing, edge computing and the presence of older devices on an industrial network that can be more vulnerable,” he explained.

“Manufacturers need to have proper security measures in place to ensure network security, including the implementation of advanced network access control systems, industrial cybersecurity firewalls, and other hardware components to secure network infrastructures.”

Pavan Mahajan

He added that manufacturers also need to place more emphasis on industrial data management and governance. “With the adoption of smart technologies and IIoT, more and more devices are getting networked and connected. Organisations need to have a strong data governance policy that outlines how data needs to be stored, managed, accessed, and analysed and by whom to ensure data isn’t lost, stolen, or misused,” concluded Mahajan.

Top recommendations for ASEAN manufacturers

According to Mahajan, the pandemic has shown that digitisation which leads to digitalisation and usage of advanced technologies is key to staying resilient and agile in the face of major disruptions.

“As we move into a 2023 full of uncertainties, manufacturers in ASEAN need to further accelerate their digital transformation journey, prioritising the adoption of technologies such as warehouse automation and connected manufacturing,” he opined.

Mahajan posited that moving towards full automation for warehouses will help boost productivity and operational efficiency for manufacturers at the material handling level.

“Beyond being able to streamline workflows, eliminate waste and maximise output, smart automated warehouses will also be flexible and robust enough to support future technologies and processes, effectively futureproofing network infrastructures against changes and disruptions,” he continued.

“Depending on their focus and goals, manufacturers could also consider making the leap towards connected manufacturing, which harnesses the power of data to transform operations as well as customer and employee experience. With many uncertainties and challenges facing manufacturers now, it can be difficult for them to focus on the future,” he cautioned.

“Transitioning to connected manufacturing will ultimately enable manufacturers to stay ahead of the curve with significant long-term benefits such as boosting efficiency, reducing costs, and enhancing communication across all stages of manufacturing.”

Pavan Mahajan

“As the threat landscape is becoming more sophisticated than ever, manufacturers should look to reinforce their network security. Security should be taken into account at the initial stage of network design for a more holistic and effective approach to securing modern industrial networks.

“At the same time, security best practices such as implementing firewalls and continuous monitoring of potential threats should be applied in day-to-day operations to minimise security risks,” he concluded.

The post IoT’s influence on Asia’s manufacturing sector in 2023 appeared first on FutureIoT.

"In many phase one projects enterprises focused on a single use case and on acquiring the data streams from single sources but as the organisations gain a deeper data-driven understanding of their operations, they can start to use other data sources (such as geolocation, machine maintenance data, weather, transactions activity, vehicular telemetric traffic data, and so on) to improve their analytics and expand beyond the original use case," he continued.

That’s the good news. The bad news is that any device that is connected to the internet is susceptible to some form of cyberattack. The Mirai Botnet and Stuxnet are two infamous attacks against targets that caused massive disruptions.  

Any device that is connected to the internet is susceptible to some form of cyberattack. Apart from the fact that IoT devices inherently have very little built-in security, and that patch management can be difficult because of their physical nature, the interconnectedness of these devices and the subsequent complex environments they are implemented pose grave security threats across entire networks.

Monitoring is a vital part of every security strategy, ensuring that all classic security tools like firewalls, unusual detection systems or privileged access management (PAM)-tools work flawlessly.  

Suitable monitoring solutions can ensure physical security by integrating door-locking systems, security cameras, smoke detectors or temperature sensors into central monitoring. And businesses in APAC should be prioritising this in 2023 to reduce their risk of cyber-attacks and data breaches.

In describing the state of IoT security or lack of it, David Montoya, the global head of IoT at Paessler, noted that it is not just the lack of security features in the IoT devices themselves that is the challenge, but where these devices are located.

“When you think about cybersecurity from the IT perspective, everything is central. You might have the perimeter and then you have all the endpoints in the middle. But here (with IoT) we might be talking about having a device, which is sending out information about the flow of water, or temperature or humidity of the soil, for example, in the farming context,” he explained.

“It is important to look at different security problems or challenges because we are not only talking about the security of the information. We are, in several cases, even talking about the security of the device itself.”

David Montoya

“People are creating vulnerabilities out of IoT, and they are willing to get a device, open it up and figure out how to reverse engineer it.  They will then try to figure out how it works and then install it again with some malware, which can then make the network vulnerable,” he continued.

Why IoT continues to be vulnerable

Montoya comments that despite more regulations and security practice context within the vendors, it is very costly or inconvenient for them to put extra resources, like computing resources into these tiny little IoT devices in use to be able to deal with patches and updates.

“For companies creating IoT devices, there is not a lot of value in needing to put more resources there,” he surmised.

He argued that device manufacturers are incentivised to create small devices that cost as little as possible. The other issue is the variety of devices and vendors. “Even though there are more regulations, there are still no standard practices put in place as to how the information should be stored,” he commented.

Twin standards to consider

Montoya clarifies that there are two standards they consider when it comes to IoT – security and communication. One is related to a standard for protocols and the way those devices connect to different cloud-based systems monitoring systems. These central consoles ensure all the devices are on and reporting data, etc. In such a heterogeneous environment the lack of standards is creating chaos in the IoT world.

“Every vendor with a specific device for a specific reason created specific ways of communication that led to multiple protocols nowadays,” he continued. “When you have different players, each looking at their market niche, what ends up happening is a lack of communication standards and protocols.”

“This (situation) opens the same vulnerabilities that have happened for operational technology (OT) before now happening for IoT as well. Stronger standards are one way things can get better in terms of how to secure all these kinds of devices.”

David Montoya

Monitoring tools can help improve the security of IoT

According to Montoya, monitoring tools help visualise the data, including receiving alerts about the data. And while IoT vendors may provide tools to monitor their solution, the variety of vendors and the specificity of their use cases, suggest that a user may have a collection of monitoring applications that track a specific kind of device.

And because these may not come from the same vendor, it is likely that these do not use the same standard and may not be able to communicate with each other.

In addition, Montoya believes that users will not likely stay with one vendor for the same use case throughout the entire life of the process. “It is very normal that you have a certain IoT device from a certain vendor today and maybe two, or three years later you need to go for another technology and another vendor,” he explained.

The result is complexity on the part of the user trying to make decisions on the entire system or process. “You will have multiple different visualisation tools with different databases where the data is stored. And whenever you are trying to retrieve the data from multiple sources, you will take more time to know what is going on, how to use the data, how to bring the data into a central location, how to use that central location to provide central visualisation,” elaborated Montoya.

Ideally, you will want a central location from which to manage all these different proprietary technologies, standards and protocols, something Montoya says is what Paessler does.

“We keep up with all these new technologies to provide a single pane of glass. So that multiple vendors for IoT devices can share the information with our visualisation tool and monitoring solution. So that the users can see everything in one place and can handle everything from a single location, we provide a central database, and they can also get centralised alerts,” he explained.

Where do we go from here?

IDC market analyst for Asia-Pacific, Sharad Kotagi, says enterprises no longer think IoT value is only limited to achieving operational efficacy and improved productivity.

“They see IoT as an enabler in the evolution of enterprises' requirements and challenges in an ever-changing business environment. Many organisations are willing to invest in digital technologies such as IoT, and AI to fully leverage the new expansive role of data in emerging digital business models.”

Sharad Kotagi

But in the race to Industry 4.0 and the promise of smarter IoT-enabled enterprises, businesses and operations should not forget that behind the facade of benefits such a transformation promises, lies a myriad of security threats and vulnerabilities that must be addressed not for the lifecycle of the IoT but the use cases it is trying to enable.

Click on the PodChat player and hear Montoya talk about the challenges organisations face as they integrate IoT into their operations, and why monitoring may be the best path forward to securing IoT as the converged future of IT, OT and IoT.

1. Paint us a picture of the security landscape where it involves IoT.
2. Technologies like IoT, security practices and regulations have evolved, why do IoT continue to be vulnerable?
3. Is the lack of standards around IoT protocol a problem for securing IoT?
4. Will this wide range of protocols also hinder the effective use of monitoring tools and services?
5. As IoT start to connect – be part of the enterprise, how should the CIO, CISO and the COO or head of operations work together to better secure IoT as these connect to the enterprise?
6. Your thoughts for 2023?

The post PodChats for FutureIoT: Why monitoring is essential in IoT adoption appeared first on FutureIoT.

IoT Analytics forecasts that globally the number of connected IoT devices will grow at 9% annually, reaching 27 billion IoT connections by 2025. Riding on this growth of connected devices is an increased need for security.

ResearchandMarkets forecasts the global IoT security market to grow from US$3.86 billion in 2021 to US$5.09 billion in 2022. The firm attributes this growth due to the companies stabilizing their output after catering to the demand that grew exponentially during the COVID-19 pandemic in 2021.

While 64% of respondents to the Kaspersky study, Pushing the limits: How to address specific cybersecurity demands and protect IoT, use IoT solutions, as much as 43% do not protect them completely.

The National Institute of Standards and Technology (NIST) paper, Recommended Criteria for Cybersecurity Labelling for Consumer Internet of Things (IoT) Products, posits that to reduce IoT product vulnerabilities, it is important to understand already exploited vulnerabilities in IoT products and ensure that consumer IoT product labelling programmes consider these incidents in its criteria to help improve the cybersecurity of the IoT ecosystem.

Dr Dorit Dor, chief product officer with Check Point Software Technologies, explains that there are many levels to IoT leaving to misunderstanding and potential risks of exposure to threats from within and outside the organisation.

“Even the lowest cost IoT device could be a starting point for an attack. You have to understand the connectivity of the IoT device to the internal and outside world. The fact that it bridges the two things without having the right IoT controlling them is the biggest evidence of this,” she explained.

“People use IoT to do massive attacks (DDoS massive attacks) by taking over IoTs in many locations and doing denial of service or other destruction for the world. These are less focused attacks and more widespread attacks.”

Dorit Dor

More common than you think

Dr Dor cautions that attacks that stem from unprotected IoT are not always targeted at specific industries. She calls back understanding that cybercriminals are often looking for the least protected targets.

That is not to say that there are attacks that are specifically directed at certain industries or organisations.

“It is less of a sectorial issue. It's more of a general issue of IoT devices being spread around and kind of hindering the security architecture of the organisation. By creating all these hidden links, the IoT itself could be served as a jump point for the intended target,” she cautioned.

Common misconceptions and challenges

Dr Dor noted that one of the biggest misconceptions when it comes to IoT security is the perception among enterprises that they do not have any IoT devices in the workplace. And if they did, the other misconception is that these devices are not connected to the internal network (without their knowledge).

Another misconception, she added, is enterprises think they are protected when they are not.

“People don’t always have the right personnel to perform the security sections required,” she posited.

Advanced technologies to the rescue?

Asked whether any advanced technologies help solve some of the challenges she presented, Dr Dor is confident that tools are available to help in the process of understanding the challenges.

She cited the use of artificial intelligence (AI) as helping map the devices that are seen on the network of IoT devices and mapping their behaviour.

“But to do this, you need to have a lot of data on similar IoT devices that exist,” she cautioned.

“So as an organisation, you may not have enough data to secure your IoT devices. However, you probably have enough data on different uses and usages of this IoT device that could help you sanction or create sectioning policies for the IoT device.”

Dorit Dor

Bringing about greater security of IoT devices in the enterprise

Dr Dor suggests reducing the access atmosphere of the IoT device to the least limited or a zoning-based approach. The other step is to understand what the IoT does and see that it behaves like a legitimate IoT device.

She recommended organisations buy IoT devices that have some security and stability built in.

Click on the PodChat player and hear in greater detail Dr Dor’s observations and recommendations for securing IoT for the enterprise.

1. What are the IoT cyber security threats faced by enterprises?
2. How common are these threats?
3. What are common misconceptions and challenges encountered today when enterprises try to secure IoT devices?
4. Can advanced technology such as AI, machine learning and deep learning solve these problems?
5. What are the roles of AI, machine learning and deep learning in IoT security?
6. What are your recommendations to bring about greater security of IT devices in the enterprise?

The post PodChats for FutureIoT: Understanding the fundamentals of secure IoT appeared first on FutureIoT.

Sensible 4 released its first product DAWN earlier this year. The automated driving software platform enables different types of vehicles to operate autonomously in any weather. The company is rolling out DAWN to the industrial segment where commercial viability can be realised today. The automated software platform will be utilised in vehicles that operate in industrial-type environments, such as mines, factories, refineries, wood processing plants, ports and logistic centres.

“We know that the legislation and technology needed for automated vehicles to operate autonomously on public roads, without a safety driver on board, will still take time to establish”, says Harri Santamala, CEO of Sensible.

“The key benefit of the industrial site is that it’s a closed environment, so customers can realise the benefit of our technology today. DAWN is ideally suited to the challenges of the industrial environment, where solutions must thrive in changing and challenging weather, such as sun, rain, wind, and snow."

Harri Santamala

"Further, our ability to operate without road markings, in daylight, and darkness, enables site operators to reliably increase their productivity,” said Santamala.

The dump truck market alone is worth up to US$25 billion. The growing shortage of drivers is affecting the transportation industry across the world. Today, there is a 20% shortage of truck drivers in Europe, by 2028 there will be a shortage of 280,000 truck drivers in Japan.

An automated truck brings more flexibility and predictability to the operation which is repetitive - pick up, drive, dump - repeat.

An automated fleet of vehicles enables on-demand or continuous operations, whilst reducing operating costs and increasing productivity.  Because of automation, more vehicles don’t lead to increased driver costs.

Some operations, that currently run with heavy haul trucks, can be replaced by a larger fleet of smaller, fuel-efficient electric trucks. The commercial viability is why automated trucks are operating in industrial sites.

The post Bringing autonomous driving into an industrial setting appeared first on FutureIoT.

The annual report highlights changes in consumers, retail associates (front-line retail staff) and decision-makers among retailers over the 15 years the survey has been conducted.

Gearing toward a mobile-first retail experience

Among surveyed shoppers in Asia-Pacific (APAC), 68% say inflation has caused them to delay purchases (compared to 75% globally). However, they are still returning to stores. However, most shoppers (76% globally, 68% APAC) want to get in and out as quickly as possible. They are also willing to help make that happen with their growing affinity for self-serve technology.

Preference for a traditional check-out register staffed by a store associate has similarly declined (51% in APAC).

This trend for using self-checkouts is now being echoed among retailers in APAC with 79% viewing staffed checkouts as less necessary, while 53% have converted store space to self-serve areas and 52% are offering contactless options.

Device shopping

Overall, shoppers are ready for technological advancements, with about eight-in-10 expect retailers to have the latest technology.

Among shoppers in APAC, 46% of those surveyed opted for cashless payment methods. Half of APAC respondents prefer paying with a mobile device or smartphone.

Consumers also continue to rely on their smartphones during shopping trips; this year’s usage indicates price sensitivity as over half of those surveyed are checking for sales, specials, or coupons (48% in APAC), aligning with a good majority of shoppers (67% in APAC) concerned about having to reduce spending to make ends meet.

Everything experience

Consumers expect a seamless experience when they shop. Seven in 10 prefer shopping both in-store and online as well as favour online retailers that also offer brick-and-mortar locations. Convenience is king for fulfilment: most shoppers (73% in APAC) prefer the option to have items delivered and opt for retailers who offer in-store or curbside pick-up (64% in APAC).

The same is true for reverse logistics: about 77% in APAC prioritise their spending with retailers that offer easy returns. About 49% of surveyed retailers in APAC are converting space in their stores for order pick-up, supporting consumer fulfilment preferences.

Mobile ordering continues to increase, with around eight-in-10 shoppers and nine-in-10 millennials using it, and around seven-in-10 shoppers wanting more retailers to offer such services.

"With the convergence of retail channels today, retailers need to step up to meet renewed shopper expectations and ensure a seamless experience across their offline and online platforms,” said George Pepes, the APAC vertical solutions lead for retail and healthcare at Zebra Technologies.

“Furthermore, as the retail sector heads into the future of fulfilment, it is more important than ever for retailers to empower associates with the right technology to better perform their tasks.”

George Pepes

While 79% of global shoppers (76% in APAC) are concerned about inflationary price increases on everyday essentials, they are not necessarily leaving stores without the items they wanted due to price. Retail associates expressed out-of-stock complaints as their number one frustration (43% globally, 38% in APAC).

In APAC, the share of shoppers that do not complete their intended purchase order is lower overall (64%), with reasons including out-of-stock products (44%) or having found better deals elsewhere (27%).

Retailers are painfully aware of such reasons; 80% acknowledge the maintenance of real-time visibility for out-of-stocks as a significant challenge, needing better inventory management tools for accuracy and availability (84% in APAC).

Leveraging labour

Generally, shoppers, retail associates and retail decision-makers agree shoppers have a better experience when retail associates use the latest technology to assist them.

In the face of labour shortages: 74% of surveyed retail associates in APAC and 82% of retail decision-makers agree that stores leveraging retail technology and mobile devices attract and retain more retail associates as well. 

To further improve the shopping experience, more than eight-in-10 retailers surveyed aim to enable more retail associates or seasonal staff to help customers pick and fulfil online orders for the 2022 holiday season.

This also addresses another challenge cited by 73% of surveyed retailers in APAC: improving online fulfilment efficiency and expense (71%).

“To keep up with the ever-evolving retail landscape, retailers need to embrace intelligent automation and transform the way they integrate technology into their operations. Retailers also need to recognize that associates are a significant touchpoint to achieving long-term customer loyalty,” said Christanto Suryadarma, Southeast Asia (SEA) sales vice president for Zebra Technologies Asia Pacific.

“By equipping retail associates with the right technologies and processes, retailers will be well-prepared to respond to shoppers’ needs and deliver on-demand effectively.”

Christanto Suryadarma

The post APAC retailers moving to self-service egged by consumers appeared first on FutureIoT.

ABI Research estimates that households with one electric vehicle (EV) could consume 37% more daily energy. Most importantly, EVs will shift peak demand in homes from 4-8 kWh to 11 kWh, creating new loads, shapes, and peaks not previously considered in resource plans.

Combined with the increasing use of intermittent renewable energy, higher EV adoption will increase the risks of electricity outages in peak periods because the available energy supply will be insufficient to satisfy the demand.

On the upside, a wide range of load-balancing solutions can promptly provide the required grid flexibility to support vehicle electrification.

“While many regions have enough electrical energy available to meet the future EV demand, energy supply is not always available when needed. Places like Texas, California, and China are already facing grid imbalances caused by increased electricity usage in peak times,” said James Hodgson, smart mobility and automotive principal analyst at ABI Research.

He cited California which witnessed an all-time electrical grid peak load record in 2022, reaching 55,061 Megawatts (MW). He posits that the consumption is 6,155 Kilowatts (kW) above the average peak over the past 20 years and enough to power 4.6 million houses.

“In the face of these facts, OEMs, end consumers, governments, grid operators, utilities, and other energy supply and distribution stakeholders must work together to enable a smooth transition from ICE to EVs.”

James Hodgson

V2G possibilities

Because re-energizing the existing electrical infrastructure is resource and time intensive, the industry is exploring alternative solutions with a quicker turnaround. Smart charging is, by far, the least complex and most effective tool.

Provided chargers are connected to charging operators, strategies such as dynamic power sharing – the ability to control the energy available to plugged-in EVs preventing sites from exceeding their maximum energy capacity – and dynamic pricing – the ability to influence customer behaviour by altering price per kWh based on utilisation – can easily be deployed with significant results.

When chargers and vehicles are connected to the grid, users can sign up for demand response programs and get energy bill rebates or other financial incentives by shifting charging time from peak to off-peak hours or allowing utilities to remotely control the time and rate that plugged EVs are charged.

V2G use cases

According to OVO Energy, residential flexibility can generate US$6.8 billion in cost savings for the whole system in the UK.

Combining smart charging approaches with bidirectional energy flow opens the possibility of vehicle-to-grid (V2G) applications, in which EV batteries store excess energy during off-peak times and become energy resources during peak times.

Activities by companies like Nuvve show that V2G has a clear ROI for commercial vehicle fleets, especially school buses, but the business model in the consumer segment is still weak. Nevertheless, Kaluza reports that end consumers enrolled in its V2G trial earned an average of £420 a year by selling surplus energy back to the grid. Other effective EV charging optimization solutions include battery-buffered chargers such as ADS-TEC Energy's ChargeBox, energy storage, microgrids, charging hubs, and swappable batteries like NIO’s.

“As EV adoption continues to grow, so will the reliance on electrical energy, and the significant peak consumption increase is worrying. Therefore, ecosystem players must collaborate to deploy tools to balance the grid and develop and adopt standards to make these tools widely available to end consumers,” concluded Hodgson.

The post Load-balancing is needed to support vehicle electrification appeared first on FutureIoT.

The real-time nature of IoT data presents opportunities, challenges and threats to organisations. Analytics will have to happen in real time for companies to benefit from these types of data.

According to Niraj Naidu, APJ head of field engineering for DataStax, the internet of things (IoT) refers to the billions of internet-connected devices around the world that use different types of sensors to collect real-time data remotely.

He adds that the IoT use cases span many different industries in a wide range of applications, depending on the application, the data that is collected from these devices can be used to perform analytics.

These devices need support from a modern technology stack that can ingest and handle a continuous flow of real-time and often time series data. Some IoT devices may have multiple sensors collecting different types of data.

“All that data flows in and is integrated into a platform where analytics are applied, patterns emerge from the analytics and insights are uncovered. These insights are then effectively converted into useful information that is delivered to end users via the IoT application user interfaces.”

Niraj Naidu

“And so, we see the type of valuable information will vary by each application’s purpose, but it could be a recommendation it could be an alert, a status update, or any other variety of use cases being tackled by specific IoT initiatives that you know, these organizations have,” he added.

The six challenges of a growing IoT ecosystem

Naidu forecasts that by 2024, the global IoT market is predicted to surpass a trillion dollars annually.

He posited that due to this growth, companies are now speedily accumulating hundreds of terabytes or even 1000s of terabytes of data, depending on the industries that they're based in.

“These companies are therefore having to deal with many different challenges when it comes to managing data produced by these IoT devices or even gadgets.”

There are six main things that we tend to see:

Scalability: Companies need a modern architecture that can quickly and seamlessly scale alongside the number of users’ devices or even the associated data volumes if they suddenly skyrocket to this.

Security: Data flowing in from IoT devices can be located anywhere globally, and there is a high probability that some if not all of it, is sensitive information. A company trying to completely handle the security of this data internally places itself at risk of a breach occurring.

Control: Data should be a company's most asset, and IoT collection and analysis can yield some amazing insights that will lead to them creating a competitive advantage for them in their markets. Organizations should therefore have complete control over that data and their data. And be able to migrate whenever and wherever they want and make it a first-class citizen.

Performance: The value that can be gained from IoT data depends on its timelessness. And the effectiveness of IoT devices largely relies on the responsiveness of the system. The platform that can truly handle millions of devices, and elastically scale with any unexpected spikes, can do all of this without slowing things down

Flexibility: Companies need that flexibility to speedily adjust, when necessary, to handle that rarity of data and devices. The database should have the ability to deal with many different types of data models and cloud environments that these IoT devices are generating.

Availability: That's one of the other key challenges that organizations are having and the success of an IoT system requires continuous flow and exchange of data, and as such going offline, it could be disastrous.

“When it comes to smart products, smart devices customers expect to access and information to be just to be available right at the click of a finger. The systems must therefore always be online, with no single points of failure,” he concluded.

Data infrastructure for IoT

Naidu suggests that the data infrastructure for an IoT system today needs to be open. It is built on a modern data management layer that once again can ingest large volumes of high-velocity data that these IoT devices and gadgets are created.

There are three parts to the system there is device connectivity, IoT Hub and the business layer.

Device connectivity is metadata information for each deployed device that needs to be managed. Each of those management layers is looking at specific things like the device registry device. Once again, metadata right device configuration, looking at device states, the device commands and interactions, and device shadows.

This part of the IoT system also contains field gateways, specialized devices, or software that acts as a communication enabler in even a local device control system, and a device data processing hub.

The IoT Hub is where all the data comes together to allow operations, administration, and insights to take place. It has two or more types of storage, looking at a hot layer for ingesting and a holding layer for recent data and another cold layer for older data.

That hub can be on-premises or close to the edge or in the cloud depending on the scale of the data or latency requirements that the organization may have.

There are then two types of analytics that can be conducted via that hub. There's real-time analytics right as data arrives at a central hub. It is streamed with event streaming technologies, which allows complex event processing tasks and analytical tasks to take place.

Batch analytics is ideal for cases where large amounts of data must be analysed right with batch queries, or even ad hoc queries, as those systems or users require.

At the business layer is where all the data from those devices’ gateways and, other sources come together to provide analysis for actionable insights. This analysis provides the ability to spot anomalies and explore trends and measure operational efficiency is just an example.

Other tools like artificial intelligence and machine learning form the basis for predictive maintenance and operation.

“I think that those three elements, they're aligned around device connectivity, the IoT hub in the business layer is what really kind of help form the right data infrastructure, architecture for IoT.”

Click on the PodChat player as Naidu elaborates on how to achieve better results using IoT analytics.

1. What is IoT analytics?
2. How prevalent is the use of IoT analytics in Asia?
3. We know that IoT produces a lot of data. What are the real challenges why enterprises struggle to better utilise/monetise the data produced by IoT?
4. Can you name a high-value/promising use case of IoT analytics?
5. What would the data infrastructure for IoT look like?
6. Do you see IoT streaming data as further complicating (or facilitating) IoT analytics adoption?
7. Where does DataStax sit in the adoption of IoT analytics?

The post PodChats for IoT: Working with IoT data analytics appeared first on FutureIoT.

Zhu Jianwei, head of the Changning District Culture and Tourism Bureau, said, “The New Page Reading Room is the first place to adopt a digital application for borrowing books within the Changning Library.

“This is an exciting pilot program to enhance public cultural services. We look forward to creating a futuristic library experience by taking the lead in implementing digital applications that provide interactive public culture experiences while accelerating the pace of digital transformation.”

Adding AI to public library services

As soon as entering the lobby of the Changning Library on the first floor, guests are immediately greeted by a digital human named “Xin Ye”. 

Once they present a “QR Code” or reader’s card, Xie Ye will recommend personalized, popular books based on the reader’s personal preferences and their reading and borrowing records. 

The reading recommendations are calculated using a big data system.  The digital human will also assist readers to complete various activities including borrowing books and reserving a seat in the reading section of the library.

“Xin Ye” was created based on SenseTime’s AI digital human technology which integrates computer vision, natural language processing and decision-making intelligence. When guests approach her, the digital human automatically awakens to welcome them and offer a selection of library services.

Especially appealing is Xie Ye’s ability to have a realistic and natural dialogue with people using her expressions, gestures, and actions, which greatly improves the human-computer interaction experience. By using a specially customised recommendation algorithm that gradually optimizes itself, guests are provided with suitable recommendations of engaging books.

Xin Ye

The Changning Library offers two methods for readers to enjoy their books: “reading in the library” and “self-service pick up for books.”  If a reader chooses the option to “read in the library”, Xin Ye provides the guest with a reservation for a seat and then guides them to be seated. 

Once seated, a robot will deliver the requested books. The reader then enters a verification code and the robot automatically opens a “pocket” to deliver a book.  After the reader finishes reading the book, they can summon the robot again and conveniently return the books to the robot.

A smart book delivery robot

After choosing “self-service pick up for books”, the guest can also select a contactless mode. This allows the reader to pick up the reserved books by using SenseTime’s contactless smart bookshelf, which improves the convenience of borrowing and returning books as well as reduces risk of spreading infections.

“Smart library” will continue to support smart reading, improve readers’ experience, and provide intelligent infrastructure to upgrade Shanghai’s public cultural services.

The post What’s inside Shanghai’s first smart library? appeared first on FutureIoT.

These are some of the findings from the 2022 IoT & Edge Developer Survey, published by the Eclipse Foundation and administered by the Eclipse IoT Working Group, the Eclipse Edge Native Working Group, and the Eclipse Sparkplug Working Group.

Another survey finding is that edge computing is gaining traction in real-world applications as top edge computing workloads all show significant increases in adoption.

“IoT and edge computing are arguably the most important technologies today, particularly for industries like industrial automation, agriculture, and automotive,” said Mike Milinkovich, executive director of the Eclipse Foundation.

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This is the case of the DKI Jakarta Provincial Government's Flood Control System in the Jakarta Smart City application. Developed by Jakarta Smart City in collaboration with the Jakarta Water Resource Service (DSDA) to optimise flood risk management in Jakarta, the project involved the use of IoT, AI and ML as part of an early warning system against the risk of floods in the city.

As more organisations deploy IoT in commercial and industrial environments, the amount of data that is derived from these devices and sensors may prove important in improving quality, operational efficiency, and in the case of Jakarta – saving lives and property from natural disasters.

Kenneth Koh, head of industry consulting at SAS Institute, argues that the speed and accuracy with which an IoT system reacts to its environment is critical. However, with the devices and other sensors in a typical system generating overwhelming amounts of data, traditional tools and methods can slow down the process of making sense of that data.

Can you explain what AI-embedded IoT is?

Kenneth Koh: Processing data at or near the edge allows IoT systems to be nimbler and more impactful. But the quality of a data-led action is only as meaningful as the quality of the data-based insights it is acting on.

IoT by itself is not new to manufacturers. Manufacturers have been collecting and storing sensor data from machines for decades. The value proposition for them is in AIoT -analysing that data, at the edge in real-time, using AI and ML to drive efficiencies and value.

By equipping IoT systems with AI capabilities, a wide variety of data, both structured and unstructured, can be processed on the edge. High-quality insights are made available at increased speeds for systems to act on.

AI-embedded IoT and how it unlocks business value

Kenneth Koh: AI-embedded IoT improves operational efficiency and productivity while reducing costs. It also drives innovation towards better customer service, better products, and faster product deployment to the market.

Embedding AI in IoT devices enables edge computing, allowing for the deployment of IoT systems in situations where consistent 5G networks are unavailable. For example, logistics providers can use IoT sensors in their transportation fleet to monitor the internal and external conditions in their vehicles, even in remote parts of the latter's routes.

Aside from edge computing, AI-embedded IoT utilises machine learning to develop actionable insights from the terabytes of data an IoT system generates daily. In the example above, data collected from these sensors are sent to the cloud in real-time, enabling technicians to address vehicle breakdowns more accurately and much faster.

Manufacturers can also use these insights to predict when a particular factory system or piece of equipment would fail, allowing technicians to implement preventive maintenance. Proactive detection of faulty equipment saves precious man-hours while reducing costly unscheduled downtimes.

On the retail side, insights from IoT systems can be used to identify optimal prices for products and minimise disruption to their supply chains.

ML and its role in IoT analytics

Kenneth Koh: Machine learning is the edge AI-embedded IoT has over other IoT deployments. Systems can learn as it processes sensor-generated data using diverse advanced analytical methods such as decision trees, random forests, gradient boosting, neural networks, support vector machines, and factorization machines.

This creates savings for enterprises in terms of man-hours and specialists in the organisation. Without the need to extensively train AI systems, specialists can focus on other critical tasks as non-data scientists can access, view, and process data.

Machine learning capabilities also increase the range of data that AI systems can access and process: visual images online and offline, text, and even verbal speech. The increased volume and quality of available data increases the value and impact of insights derived from it.

Combined, these machine learning capabilities enable both increased speed and volume of data processing, enabling real-time actionable insights which are crucial in many IoT systems.

How AIoT supported Jakarta Smart City: Using SAS's AI-powered platforms, Jakarta Smart City was able to integrate multi-source data in real-time and provides advanced analytics with IoT, machine learning & AI technology to provide emergency/disaster predictive capability and optimisation to serve the public. The result is a flood emergency response to mitigate the risk of floods in Jakarta.

Given that IoT historically falls under operational technology, who should own the securing of IoT?

Kenneth Koh: The introduction of IoT is blurring the lines between IT and OT across enterprises. Sensors and devices are connected to the network to create new systems and improve processes. At the same time, this convergence exposes traditional OT equipment and systems to threats they were previously insulated from.

The fact is that true device security is a combination of technologies, processes, and best practices. Thus, securing IoT systems should not be the sole domain of either OT or IT teams but engendering closer, more effective collaboration between both.

However, this is easier said than done, as IT security teams and OT security teams often don't speak the same language and find it difficult to understand each other's point of view.

Responsibilities are distributed quite differently; priorities often diverge and regulations governing OT security and IT security can sometimes contradict one another. Gaining an overview of all assets within the given environment makes clear what assets and processes must not fail under any circumstances.

By doing this, organisations can establish and practice unified cybersecurity that ensures the confidentiality, integrity, and availability of data.

Name one best practice for IT and operational technology staff working together.

Kenneth Koh: In manufacturing, data is very time sensitive. For example, if the chemical concentration of a process is drifting away from optimal, the engineer may have only minutes to react to save many tons of product. 

In many semiconductor processes, engineers have only seconds to react. In such situations, Analytics needs to move to the ‘edge’ which means the data must be analysed and decisioned at the machine or on the shop floor, not in the back office or engineering.

This requires the ability to do analytics wherever it is needed –at the machine, on the production floor, in the cloud or the back office.

One of the major challenges faced is data silos. For organisations that are not implementing IT/OT convergence, due to a patchwork of unintegrated or partially integrated apps and enterprise systems. Without careful planning, introducing new sources of data (e.g. IoT sensors) will compound the problem.

Implementing a data integration platform to connect IoT systems with organisations' existing technology stack breaks down silos between historical and future data while providing all teams the same access through a single point of control. This ensures that IT and OT teams are with the same page, establishing a foundation for better IT/OT convergence.

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To be clear, enterprise 5G goes beyond standard consumer 5G service. In an enterprise 5G, the enterprise has complete control over the network assuming the company forks out the money to have its infrastructure, radio devices, mobile core, and management software.

The possibility of having private 5G networks means an enterprise will have better control over how it scales its network in addition to better control over cellular resources.

This will grow in importance as enterprises adopt IoT sensors into the workflow and gain real-time insights for improved efficiency and preventive maintenance.

One of the challenges this opportunity presents is around network management. Fortunately advances in artificial intelligence and automation may present a solution in the form of autonomous systems for managing network resources.

IEEE posits that autonomousity is not just making the network capable of managing resources, but rather making the network learn and adapt itself to the dynamic environment.

“In networks, the autonomous tasks refer to self-healing, self-diagnosing, and self-provisioning. With the help of emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), and Blockchain, autonomous tasks can be realised in current network systems.”

Autonomous Networks: Opportunities, Challenges, and Applications

Richard Howe, chief technology officer for Kyndryl Singapore, says an autonomous network is a self-configuring, or self-healing network that runs with minimal to no human maintenance. The network adapts to changes in devices being added, or degradation of network performance such as data throughput due to packet loss.

“Having a network that keeps devices consistently connected, and transmits data to an edge computing platform, enables fault detection. It ensures worker safety in industrial and manufacturing plants and facilities – you can add new drones to monitor whether employees are wearing hard hats or are in dangerous areas.”

Richard Howe

Benefits of autonomous networks for the manufacturing ecosystem

According to Deloitte, to remain competitive, manufacturers must absorb digital and advanced technologies across their business operations, including production.

The 2019 Deloitte and MAPI Smart Factory Study noted that connecting to an ecosystem was a hallmark of the Trailblazers (pioneers in smart factory adoption), a cohort of manufacturers that were making great strides by adopting Industry 4.0 technologies to solve specific business problems and opportunities.

The manufacturing ecosystem today is no longer limited to the manufacturer and its suppliers of raw materials. In smart manufacturing, an ecosystem is formed when different entities come together in meaningful ways to solve shared challenges and meet shared objectives.

Because the ecosystem comprises several companies, many independent from others in the network but sharing common interests, having a way intelligently manage some of the systems and processes automatically just makes sense.

According to Howe, autonomous networks enable scalable automation and add real-time intelligence to industrial processes, ensuring manufacturing quality, speed and efficiency without the need for much manual and human management.

“It enables fault detection and works safety, and for a manufacturer, this means more reliability and resiliency. For example, you can add cameras inside the manufacturing facility/plant for fault detection,” he added.

The use of 5G permits the use of mobile endpoints capable of collecting vast amounts of real-time data from industrial processes at low latency and taking advantage of local edge computing.

Machine learning leverages the experience of industry specialists at scale humans can’t match given the high data rates possible with 5G.

Use cases of autonomous networks

Asked where early applications of autonomous networks, Howe noted that in the manufacturing sector, these would include remote production monitoring using portable and deployable sensors.

He also highlighted use cases in predictive asset monitoring and condition-based maintenance, as well as vision analytics to ensure quality management.

He also highlighted the use of advanced robotics and human worker coordination (cobots), that can enable worker safety through wearable sensors, or support real-time worker augmentation via low-latency augmented reality/virtual reality that can either troubleshoot field problems or enable knowledge transfer between workers

“It is important to understand that successful integration of such autonomous networking applications will require the migration to cloud-native technologies and robust deployment of 5G. Such a foundation increases the speed and efficiency of properly integrated use case rollout that can be adjusted for specific operating environments,” he explained.

Integrating autonomous networking

Howe warns that implementing autonomous networks and also other related intelligent edge solutions can be a daunting task.

He stressed that a foundation of different technologies across the autonomous network’s application stack will be required like specialised compute infrastructure, wireless network connectivity like Wi-Fi 6 or 5G, along with IoT devices, data acquisition protocols, and lifecycle management tools in which volume of data can be compiled and processed by cloud-based Artificial Intelligence (AL) and Machine Learning (ML) algorithms.

“Such an undertaking will certainly require the right expertise for building applications on the autonomous network, and knowledge of the latest orchestration techniques. A majority of these technologies have only recently evolved and developed over the last decade, there is also an existing shortage of skill sets that can support these emerging use cases,” he added.

He posited that introducing and deploying autonomous networking to tomorrow’s industrial and manufacturing environments is a challenge that will require concerted support from an ecosystem of multiple vendors and partners.

“Such an ecosystem will include the major hyperscalers, vendors that provide low latency connectivity or analytics, AI and ML, and also managed services providers that can interconnect elements across all application layers,” he continued.

Economic implications of autonomous networks

Citing a 2021 study, Statista researchers noted that the concept of autonomous networks implemented in the sector of telecommunications may have a global economic impact of 13 billion U.S. dollars in 2021, and it is forecast that the implementation of this concept could have an economic impact of more than 800 billion dollars by the year 2030.

Howe believes that autonomous networks will simplify and enable the full extent of what can be possible in industrial and manufacturing environments by replacing costly, inflexible workflow processes that are manual and rely on legacy technological deployments.

“Aside from the direct benefits such as cost and workflow improvements, autonomous networks will enable the acceleration of a range of IoT, application and data use cases; this, in turn, will provide the basis for new revenue streams and products,” he added.

Advise for decision-makers

Asked what senior business, technology and operations leaders should bear in mind when evaluating autonomous networks as a solution to solve current business/operations challenges, Howe recommended that for organisations big and small, the transformation of network architectures and technologies can be uniquely challenging – yet imperative.

He further added that it is important to select vendors and partners that provide unbiased guidance and deep knowledge.

“Organisations have broad footprints, and each has the potential for thousands of edge environments needing deployment and management. Every manufacturing floor, every distribution hub, warehouse, or airport terminal counts as a single edge environment.”

Richard Howe

“The adoption of autonomous networks will enable organisations to speed system deployments and service activations, avoid failures and slowdowns, enable more dynamic operations, and operate at a greater speed and scale,” he concluded.

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Extending well beyond a website, the digital front door consists of a federated suite of applications, services, portals, and digital devices, enabling healthcare organisations to engage patients through digital touchpoints as they journey across the continuum of care outside of brick-and-mortar facilities.

The objective is to create a unified, seamless, consumer-centric patient experience that fosters behaviour change while providing better healthcare access, equity, efficiency, quality, outcomes and improved patient and staff satisfaction. The digital front door can also increase brand awareness, reputation, and revenue.

“As a result of the COVID-19 pandemic, the rise of healthcare consumerism, and new entrants in healthcare, the notion that the digital front door is an isolated part of an organisation’s digital health strategy is now archaic thinking,” observed Paul Sonnier, industry principal, healthcare and life sciences at Frost & Sullivan.

He opined that the competitive imperative to build a robust digital front door is a matter of survival, whether an organisation realises it or not.

“Patient expectations for quick, convenient, transparent, connected, and responsive healthcare services are redefining how they engage with their healthcare providers at each stage of their care journey, including pre-care, at-care, and post-care,” noted Rishi Pathak, director of healthcare and life sciences at Frost & Sullivan.

He added that this shift results in patients, especially Gen Z and Millennials, choosing healthcare providers that offer digital capabilities across the care continuum, therefore forcing healthcare systems to find new ways to digitally transform their services to deliver a truly omnichannel healthcare experience through digital front door strategies.

“Now is the time for the providers to act,” he concluded.

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Tiny Machine Learning, or TinyML, is typically used for automated tasks involving sensory data. As TinyML vendors continue to democratise Machine Learning (ML) at a rapid pace, ABI Research forecasts that TinyML Software-as-a-Service (SaaS) revenue will exceed US$220 million in 2022 and become an important component from 2025 onward.

While total revenue will be dominated by chipset sales, as TinyML device shipments continue to grow, the TinyML SaaS and professional service market have the potential to become a billion-dollar market by 2030.

The TinyML market has come a long way since ABI Research first analysed this market back in 2020. The TinyML Foundation, which gathers most of the main vendors in this space, has greatly expanded in recent years. And so have the applications of TinyML, with forest fire detection, shape detection, and seizure detection among some of the most spectacular use cases.

Given how central environmental sensors are to TinyML, the possibilities are extensive. David Lobina, artificial intelligence & machine learning research analyst at ABI Research, explains, “Any sensory data from an environment can probably have an ML model applied to that data.”

He listed out some of the most common applications including Word Spotting (the identification of keywords in text or utterances), Object Recognition (the detection of a person by a sensor), Object Counting (a sensor that counts the number of people inside a building), and Audio or Voice Detection, (as in the models that activate upon hearing ‘Hey, Google’).

Ambient sensing and audio processing remain the most common applications in TinyML, with sound architectures holding an almost 50% market share in 2022. Most of these applications employ either a microcontroller (MCU) or an Application-Specific Integrated Circuit (ASIC). The personal and work devices sector will be the largest increase soon.

With the myriad possibilities, there are also potential pitfalls, but for which, ABI Research believes there are well-identified solutions. “The physical constraints on TinyML devices are genuine. These devices favour small and compact ML models, which call for innovation at the software solutions level for specific use cases. And software providers will be the most active in the TinyML market,” says Lobina.

Software providers include leaders such as Edge Impulse, SensiML, Neuton, Nota, and Deeplite.

ABI Research recommends vendors concentrate on those applications that TinyML has a clear value proposition worked out before production.

Lobina says the role of software is crucial, and vendors must develop software tools to automate TinyML itself, a recursive process that necessitates employing TinyML applications to automate other TinyML applications.

“And finally, new technology will be required to bring about ever more sophisticated TinyML models. Neuromorphic computing and chips, along with the corresponding technique of Spiking Neural Networks, would bode well for the future,” he concludes.

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However, indirect communication via the cellular network (e.g., V2N2X, I2N2V) still constitutes the most significant yet untapped vehicle-to-everything (V2X) opportunity. Cellular connectivity will be available in 346 million vehicles by 2025, and smart city cellular connections will exceed 165 million.

Europe’s short lead getting shorter

In 2021, Europe was the region with the largest fleet of short-range V2X communication-enabled cars, but all from a single automaker, Volkswagen.

Maite Bezerra, smart mobility and automotive industry analyst at ABI Research, attributes this decline in Europe to a lack of commitment of more automakers. She predicts that by 2023, China alone will have overtaken Europe.

“The inauspicious scenario in Europe is leading industry players to place more emphasis on cellular network tests for the time being. However, there are still fundamental business model challenges to be overcome with this route.”

Maitê Alves Bezerra

“Although a truck and a private vehicle OEM may deploy ITS-G5 in 2023, the crucial market driver for mass adoption will be the V2X inclusion in the Euro NCAP scoring, as is currently happening in China. Lagging, the United States now has a solid regulatory framework for C-V2X, paving the way for deployments," she added.

Restarting the V2X momentum

There are suggestions in the industry that the V2X inclusion in the 2025 Euro NCAP rating scheme will be delayed to 2027 due to insufficient time to develop new test protocols. This includes establishing enough labs and validating new vehicle capabilities.

"If this the case, it would conveniently coincide with New Radio technologies' readiness (802.11bd/NR-V2X PC5), meaning that carmakers could 'skip' the implementation of existing/legacy radios – provided backward compatibility with current ITS-G5 infrastructure and vehicles is not required. However, it would delay the take-off of the technology even further," says Bezerra.

While the NCAP has not officially confirmed any changes, there is consensus that if the 2025 timeframe is maintained, it will focus on Day One use cases. There is also consensus that 2027 will be the inflexion point for mass adoption because a complete range of Day Two use cases will become part of the Euro NCAP scoring.

The spectrum wars

The recent dismissal of the appeal against the FCC's 5.9GHz spectrum proceedings means that C-V2X has a clear path in the US and should spur the FCC to grant the existing C-V2X waiver requests faster.

On the downside, the US may not have enough spectrum for some advanced cooperative perception/Day 2 use cases in the future.

In China, C-V2X is currently found in low-volume premium vehicle models, but there are at least 25 OEMs in different stages of V2X production in the country. COVID-19 lockdowns and discussions about the GNSS positioning standard slowed down deployments in 2022. However, shipments of vehicles with C-V2X will grow exponentially in 2023, surpassing the one million mark as carmakers prepare for China NCAP 2025.

V2X has significant potential to increase traffic safety, optimize traffic flow, and reduce traffic congestion and emissions.

Bezerra posits that the long wait for mass adoption should not discourage interest in the technology. Instead, it should motivate players to leverage the sizeable installed base of vehicles and infrastructure with embedded cellular connectivity.

“This will deliver immediate value through basic V2X services that do not rely on low latency and can greatly increase driver awareness scopes, such as road, traffic, traffic-light, and weather hazard alerts and information," Bezerra concluded.

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Speaking at the 2022 World Artificial Intelligence Conference (WAIC), Dr Zhang Shaoting, vice president and president of smart health business at SenseTime, introduced SenseTime’s comprehensive Smart Hospital Solution by depicting how the future healthcare landscape brings better patient experience, combined with real cases:

“Through conversations with the intelligent chatbot on a mobile phone, the patient was able to receive a recommendation for the most suitable department or doctor, as well as a complete appointment at home; after arriving at the hospital, the patient was able to follow the AR navigation function which indicated the best route and arrived at the destination without any hassles.”

Dr Zhang Shaoting

Based on deep learning algorithms, the AI diagnostic assistance software helps doctors quickly detect lesions, analyse the patient’s conditions, and plan for future treatments. Doctors can also simulate and assess a surgical plan through 3D visualized models, to better communicate with patients and their families.

The regional-level medical collaborative platform connects experts from different cities to discuss the case, analyse surgical difficulties and optimize treatment plans. During the rehabilitation phase, doctors can keep close track of patients’ conditions through intelligent follow-up and management systems.

Putting the smart in healthcare

Smart Hospital Solution has the capability to upgrade a hospital’s facilities with fully digitalised and intelligent processes including contactless temperature sensors and verification devices at entrances, effectively ensuring the safety and order of hospital admission.

The possibilities

Adhering to the “patient-centric, quality first” mission, SenseTime’s Smart Hospital Solution is designed to promote a new mode of healthcare and enhance various healthcare scenarios by providing the following services:

For medical professionals, the SenseCare Smart Health Platform provides high-performance clinical assistance covering multiple medical imaging modalities and body parts.

For patients, the Smart Outpatient Assistant simplifies outpatient procedures and communication processes to reduce waiting time and optimise the patient experience.

For hospital operators, the Smart Hospital Operation and Management service provides comprehensive digital and intelligent solutions for managing patients, hospital staff, space, and facilities.

For researchers, the Intelligent Clinical Research Platform provides a platform to accelerate innovation, elevate research efficiency and facilitate R&D projects across different research institutions.

For regional-level medical alliances, the Smart Medical Cloud Platform enables a more convenient and flexible remote diagnosis and patient referral to optimize the allocation of medical resources in the region. In addition, it also facilitates collaboration between hospitals of an alliance, making high-quality medical resources more accessible in grassroots healthcare institutions.

Actual use cases

Ruijin Hospital (one of China's most prominent hospitals): Its Pathology department has deployed the SenseCare Smart Health Platform to improve the efficiency and accuracy of diagnosis and treatment planning by doctors, and facilitate remote diagnosis across different branches

Qingdao West Coast New Area (China’s State-level new area): Deployed the SenseCare Smart Health Platform and the Smart Medical Cloud Platform to promote AI-enabled processing and interpretation of medical images at the regional level, contributing to the construction of a hierarchical medical treatment system and facilitating the allocation of regional medical resources

Xinhua Hospital (a leading hospital in China): Deployed the Smart Outpatient Assistant to streamline outpatient procedures and optimize patients’ experience

Xiangya Hospital (one of the earliest Western hospitals in China): Deployed the Intelligent Clinical Research Platform to accelerate innovation, elevate research efficiency and facilitate R&D projects, especially for multicenter research

Kiang Wu Hospital in Macau (one of the largest and oldest hospitals in Macau): Deployed the SenseCare Smart Health Platform to elevate clinical efficiency and accuracy for the Radiology department

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The Frost & Sullivan report, Growth Opportunities Driven by New Form Factors, revealed that the adoption of new form factors for devices will surge rapidly with advancements in connectivity technology.

It also noted that the advent of 5G and expanding artificial intelligence (AI) use cases will further inflate the global demand. This will lead to improved innovation across wearables, flexible devices, and implants.

“As the demand for new pliable form factors increases, companies cannot rely on traditionally shaped devices to capture market share,” said Akshay Menon, senior research analyst at Frost & Sullivan.

He added that this encourages big electronic companies to work with newer materials to manufacture durable and flexible electronics.

Partner with application companies and social platforms to ensure their offerings are compatible with the device hardware, establishing an immersive customer experience.

Invest in research to develop durable materials, as current stretchable materials are thermoplastic, meaning heat softens them and makes them unable to withstand thermal exposure.

“With consumers’ growing preference for small-sized electronic devices, miniaturization will lead to developmental objectives for manufacturers. Further, new form factor development will lead to increased human-machine interaction, making data security a strategic priority for organisations."

Akshay Menon

Associate with organisations in the technology-enabled space as a new form of technology is dependent on internet connectivity and AI.

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One of the earliest examples of IoT was in the early 1980s and it involved a Coca-Cola machine that was located at Carnegie Mellon University. Programmers would connect through the Internet to the refrigerated appliance and check to see if there was a cold drink available before making the trip to purchase one.

Most discussions around the IoT will likely revolve around the hardware. This is understandable that most of the enterprise IoT technologies we’ve become familiar with are with simple devices that perform a few tasks. For example, monitor the temperature in a production line.

But as advances in communications converge with business demands for doing things faster, better, more safely and cheaper, even technologies like IoT are evolving to include features that in some cases incorporate intelligence, manageability, and more recently, security.

This growing sophistication in the demand for IoT and expectations of what it can do means that IoT discussion is no longer limited to hardware design but must, by default, include software considerations.

FutureIoT spoke to Joanne Wong, vice president for international markets at LogRhythm, for her take on how IoT software is evolving.

What is IoT software?

Joanne Wong: Anything from lamp posts and running shoes to fish tanks can now be connected to the Internet with the advent of inexpensive computer chips, sensors, and wireless networks, which enables them to collect and share data in real-time autonomously without human interference.

IoT software connects the computer chips, sensors and networks in the broader system together. It plays a crucial role in the data collection and communication process, as well as the management of the IoT application and device itself.

Take smart lamp posts for example. The Singapore government plans to roll out 110,000 lamp posts equipped with a network of wireless sensors and cameras that will help to detect and monitor changes in environmental conditions, and track vehicle speeds – beyond illuminating the streets.

In this case, the IoT software controls the systems such that imagery and traffic data collected from the sensors and cameras are communicated to the central management system in the cloud, which is then turned into actionable insights.

Looking back from pre-pandemic to this period (mid-August 2022), how have things changed when it comes to IoT software?

Joanne Wong: The IoT software market has grown significantly over the past few years, in tandem with the accelerating adoption of IoT solutions and devices. While the sector was briefly affected during the pandemic due to a pause in technology spending for certain sectors, it has since regained much of its initial momentum. IDC predicts IoT spending in Asia Pacific to reach US$437 billion by 2025.

Over the years, IoT solutions have become more powerful and efficient, thanks to advancements in Artificial Intelligence (AI), Machine Learning (ML), edge computing, automation and other emerging technologies. Machine learning algorithms, for example, can add predictive capabilities to IoT solutions.

For example, sensors attached to machines in the manufacturing sector can monitor the performance of the equipment and predict when failures and breakdowns will happen. Having access to such information early on allows for the repair or replacement of faulty parts, to prevent wide-scale operational disruptions.

On the other hand, edge computing technology makes IoT devices with onboard analytics capabilities possible. This brings computing as close as possible to the source of data, reducing network latency and relieving network congestion, thus allowing for quick delivery of insights to the end user. On top of that, as personal data no longer needs to leave the individual domain, a lot of data privacy and security concerns with IoT can now be mitigated.

IoT as a service (IoTaaS) offerings have also emerged as a new way for businesses to access IoT solutions. Vendors such as Microsoft are moving towards offering IoT platform management services, which allows businesses to leverage IoT software and infrastructure without having to invest heavily into building the network architecture hardware, purchasing expensive software, or hiring trained personnel to manage the process.

In the period of accelerating digital transformation, which areas of IoT software have gained importance?

Joanne Wong: IoT security has become crucial for organisations looking to successfully implement IoT solutions.  This is because digital transformation acceleration has led to an influx of devices coming online. With the exponential growth in the number of devices now connected to the internet, the attack surface has also gotten significantly larger.

Opportunistic cybercriminals now have more entry points – from insecure connections, and legacy devices to weak digital links – to take control of these IoT devices to spread malware or gain direct access into the network to obtain critical data.

For IoT devices, the risks are doubly high for two reasons. Firstly, IoT devices typically do not come with in-built security functions, which makes them an easy target for hackers. Secondly, IoT devices, especially those that are small or light, can be easily misplaced or stolen. Unauthorised users who have gained physical possession of the devices can easily access your network.

This is also why cybersecurity is now a huge area of focus for IoT devices and software. On the other hand, failure to secure IoT ecosystems could lead to eroding trust in their potential across the organisation, as well as wasted investment costs. 

More technology providers are now adopting the “security by design” approach to IoT hardware and software development, which looks at building security features right from the initial developmental stage.

Cybersecurity platform vendors too are adding specific security features to IoT data collection and storage functions, to safeguard sensitive data flowing between the IoT device and network from unauthorised access.

Which industry sectors in Asia are leading the charge in terms of IoT software adoption and development?

Joanne Wong: With the worldwide pandemic over the past two years, organisations in healthcare are understandably one of the most active areas of IoT development. According to Data Bridge Market Research, the IoT APAC healthcare market is predicted to grow with a CAGR of 30.55% between 2022 to 2029. This applies broadly to the rise in telemedicine adoption and narrowing down to connected specialised equipment, all while accommodating to recent lifestyle changes.

Medical professionals are now able to collect patient data and understand patient conditions, without the risk of large group interactions. Healthcare IoT equipment inherently addresses the areas of shortage in hospitals, where necessary patient care and attention are provided for those in dire need. Additionally, it accelerates and improves access to healthcare services, especially reaching remote areas, beyond the pandemic.

Supply chain management is another sector thriving from IoT adoption. Frost & Sullivan highlighted that almost 21% of logistics companies in Asia currently leverage IoT for their fleet management solutions and this number is only set to increase in the next few years.

Industrial IoT has been the driver for parallel growth in smart manufacturing which includes factory automation, GPS shipment tracking and machine-to-people communications. The ease of data collection and real-time data encourages calculated risk-taking, allowing organisations to maximise opportunities for growth and revenue — more data, and more cost savings. For instance, better forecasting of demand, ship and fleet tracking and better risk management.

What needs to happen for organisations in Asia for us to see greater integration of IoT software in industrial settings?

Joanne Wong: With new manufacturing and smart city initiatives underway, there are numerous opportunities for greater integration of IoT software and the development of horizontal capabilities across industrial settings. This includes predictive maintenance and connected operational intelligence in manufacturing, as well as security and surveillance for smart cities.

However, closing the gaps in IoT security will be key to maximising the potential of IoT across industries and areas of operation. With more devices now connected to the internet, greater interconnection can pose higher cybersecurity risks for these industries.

It is more important than ever that organisations maintain clear oversight across their entire digital supply chain, including their IoT endpoints, to ensure that there is constant monitoring and surveillance for potential threats.

Companies should seek to redefine security ownership within the organisation to improve the management of IoT devices. Currently, IoT security falls under both the security and operations function - which may lead to confusion on whose responsibility it falls under.

At the same time, companies should also ensure that the adoption of security solutions is also compatible with the business needs — adapting to network changes, and automatically detecting, predicting, and responding to real-time threats.

The post IoT software trends in 2023 appeared first on FutureIoT.

The second, and arguably more dramatic, are the nearly persistent cyberattacks against private businesses and the continued operation of critical infrastructure. Nearly all industries are unable to escape unscathed from these attacks.

IoT adoption in manufacturing

Specific to Asia’s manufacturing sector, IDC is projecting continued growth in the integration of IoT technologies into the region’s manufacturing sector.

IDC estimates that in 2020, US$83.4 billion was spent on IoT technology by manufacturers in Asia/Pacific (excluding Japan) with discrete manufacturing accounting for 60% of spend. Process manufacturing spent more than US$33 billion in the same year.

By 2025, IDC expects discrete manufacturers will send US$88.7 billion compared to US$51.9 billion among process manufacturers. The analyst says manufacturers can profit greatly from retrofitting smart sensors to old equipment because of the insights they can obtain about their equipment

FutureIoT touched base with Piyush Singh, senior market Analyst for IoT Insights, IDC Asia/Pacific to discuss how IoT is trending within the manufacturing sectors of Asia.

Manufacturers, whether in process or discrete, have used instrumentations to get feedback and provide some control over the production line. How can a manufacturer introduce IoT technology without disrupting the production line?

Piyush Singh: Industrial IoT uses a network of sensors to gather crucial production data, and cloud software to transform this data into insightful knowledge about how well industrial activities are run. The primary use case for expenditure was operations, followed by production asset management, maintenance, and field service.

Most of the manufacturers start with pilot testing by upgrading the existing legacy machines with the implementation of various hardware products. Additionally, it is true that replacing a plant entails a lengthy period of machine downtime.

In terms of time, this is frequently unsustainable. In this regard, a refit operation evaluation would be helpful. The most difficult barrier to a retrofitting effort is that a legacy system has machine tools from many manufacturing eras with various connection protocols.

Process control must be carried out manually by monitoring, sensing, estimating, and modifying the machine parameters due to the lack of sensors and actuators.

"Usually, in Asia, the retrofitting is completed in a phased manner wherein one production line is taken for the upgradation to avoid unnecessary downtime in production. Once the transformation of machines is completed in one production line, later the retrofitting of other machines will be considered."

Piyush Singh

Specific to manufacturers in Asia, do you see information security including cyber security, as a priority over production? How has the perception/acceptance/attitude towards security changed over the last five years?

Piyush Singh: The fourth industrial revolution, often known as Industry 4.0, is the logical outcome of the third revolution and is primarily focused on two key elements: the Internet of Things and Services (IoT) and Cyber-Physical Systems (CPS).

In Asia, retrofitting is not only the key concept of factory automation. Cyber security, data security, and enhanced data privacy are all covered under one umbrella called industry 4.0.

With the growing demand for IoT in various sectors, the demand for robust cyber security is also the need of the hour. Spending on security solutions and services in Asia/Pacific is forecasted to exceed $31 billion in 2022, an increase of 15.5% from 2021 in which almost $2 billion in security spending would be under the discrete manufacturing section, according to IDC's latest Worldwide Security Spending Guide.

Despite headwinds such as looming global recession, geopolitical conflicts, and rising inflation, investments in hardware, software, and services related to cybersecurity are expected to reach US$ 57.6 billion in 2026, with a CAGR (compound annual growth rate) of 16.4% for the period of 2021-26.

China will continue to be the region's largest market, accounting for more than 40% of total Asia/Pacific* security spending in 2022, with a five-year CAGR of 21.2% during the forecast period. This clearly showcases that the demand for security infrastructure is increasing in the Asia Pacific manufacturing sector.

If you think of IoT integration in the manufacturing process as a timeline, what IoT technologies do you see being deployed over time and what other technologies do you anticipate will follow because of IoT?

Piyush Singh: Most of the downtime and accidents are caused by the wear and tear of machines in many manufacturing plants. By virtualizing the plant and averting high-risk operator occurrences, the retrofitting goal is to ensure predictive maintenance applications.

Remote monitoring and management system, digital connectivity, cloud storage and robotic process control are some of the IoT retrofitting trends seen in manufacturing processes. 

To identify and detect upcoming errors, Deep Learning algorithms and Digital Twin (DT) approaches is something which is being used and have the tendency to grow exponentially in future. Artificial neural networks (ANN) for detecting the tool wear in a CNC machine after retrofitting is a concept which is in great demand in many production plants.

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“Industries cannot be formed without standards”, Xu Li, executive chairman of the board and CEO of SenseTime. He posited that standardisation would lead to a flourishing AI industrialisation.

“Through powerful infrastructure, we can produce high quality and standardised models with replication in various scenarios, as well as efficiently manage the whole process of model production. It is worth mentioning that standardisation is not a constraint and will ultimately create infinite possibilities in AI applications,” he explained.

Xu stressed that a standardised AI manual is needed to enable scalable AI innovation.

As AI develops towards commercialisation, AI models become the standardised features for the intelligent era, supporting various applications such as advanced driver assistance system (ADAS), city management, surgical planning, and intelligent agents in games, in which issues can be resolved through the same standardised AI models. 

The four new AI platforms

Stressing the importance of standards for the further adoption of AI at scale, Hong Kong-based SenseTime unveiled four new AI platforms covering different fields including AI cloud computing, vehicle-road collaboration, AI in gaming and smart hospitals, aim to drive AI’s scalable industrial application through standardised, more efficient, easy-to-use, and low-cost platform services.

The SenseCore AI Infrastructure, as an innovative “Yingzao Fashi” developed by SenseTime, achieves highly efficient, low-cost, and scalable AI innovation and empowerment for industries.

SenseCore AI Cloud is developed into an out-of-the-box industrial-grade AI toolchain underpinned by the SenseCore AI Infrastructure. It can facilitate AI infrastructure’s comprehensive digital management, effectively meeting the requirements for future industrial AI pipelines as well as the large-scale training, verification, and reasoning for AI models.

SenseCore AI Cloud can help customers double the efficiency of AI research and development with lower infrastructure costs by providing a full-stack deep learning platform and a series of advanced algorithm platforms and models.

Essentially, it creates a new paradigm of AI cloud infrastructure that innovatively empowers various application scenarios including autonomous driving, smart city, AI for Science and Metaverse.

SenseAuto V2X is SenseTime’s vehicle-road synergy platform committed to providing a one-stop analysis and decision-making solution for future mobility by integrating “smart cars, intelligent roads and collaborative cloud”.

Through the fusion control and analysis of vehicle and road information, it can achieve intelligent operation of “vehicle, road and cloud” platforms to improve traffic management efficiency.

SenseAuto V2X can transmit sensory output from roadside sensors to the vehicle and empower intelligent vehicles with more comprehensive sensing capabilities to better adapt to complex traffic scenarios.

Currently, SenseAuto V2X is deployed in the management of national Internet of Vehicles (IoV) pilot zones, closed parks, highways and urban traffic, facilitating the decision-making for traffic management with higher efficiency and safety.

SenseMAP Multi-Agent Platform is SenseTime’s tailor-made AI gaming production and operation platform. Leveraging the strength in computing power, deep learning and intelligent decision-making technologies, SenseMAP provides game developers one-stop full-cycle production services, covering auto-adaptation in gaming ecosystem, auto-creation of gaming content, and auto-operation of gamer community.

It has largely elevated the productivity of game development to create a better competitive experience for gamers. SenseTime will continue accelerating the diverse applications of AI in games and join hands with industry partners to boost the innovation and development of the game industry.

SenseTime Smart Hospital Solution provides a suite of smart services across various scenarios with the goal of delivering “patient-centred and quality-first” services.

For medical professionals, the SenseCare Smart Health Platform provides high-quality, efficient AI diagnostic assistance throughout clinical processes; for patients, the Smart Outpatient Assistant can streamline the outpatient procedure and optimize the patient experience.

For hospital operators, the Smart Management Service accelerates hospital operation and management’s digitalization.

For research organizations, the Intelligent Clinical Research Platform facilitates R&D work and boosts research efficiency.

For regional-level medical alliances, the Smart Medical Collaborative Platform optimizes the allocation of regional medical resources. SenseTime is committed to leading the development of AI-powered smart hospitals and accelerating the digital transformation of high-quality hospitals.

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The programme aims to help these startups to scale by co-developing solutions with businesses with the NWD group ecosystem in Hong Kong and Guangzhou. The next cohort of the GBA Accelerator is now open for application.

The GBA Accelerator identified technology improvement opportunities from NWD's residential, retail and construction business units; from increasing customer engagement within the group's retail properties to automating services in property management.

"Breaking into a market as large as the GBA can be difficult and Eureka Nova has acted as a bridge between these startups and the NWD businesses needed to help them succeed. The startups have also been networking with like-minded entrepreneurs and mentors to develop their go-to-market strategies,” said Paul Sin, director of technology and transformation at NWD.

Besides showcasing their technologies in NWD's properties, Sin added the startups have learned to localise their solutions for an entirely different customer base and what business requirements are necessary to win over large B2B clients.

Eureka Nova launched the inaugural cohort of the GBA Accelerator programme in September 2021, targeted at robotics and AI startups looking to scale their business across the GBA.

The programme attracted applications from around the world to develop solutions that solve real-world business problems for New World China Land, K11 MUSEA, 11 SKIES, Property Management, and Hip Seng.

Nine have been selected for their robotics and AI solutions – four from the Chinese Mainland, four from overseas, and one from Hong Kong. During a five-month incubation period, the nine startups received development support and training by Eureka Nova, while seizing the opportunity to work closely with NWD's business units.

Startups from GBA  Accelerator’s inaugural round to pilot solutions

Three international startups from the first cohort of nine  – Trace from the US, DeepBrain AI from South Korea and R-Storm from Mainland China – will pilot their innovative solutions in NWD's businesses in the coming month for them to test and refine their products and go-to-market strategy in the GBA.

These solutions will eventually have the opportunity to be integrated into New World businesses in Hong Kong and Guangzhou:

• Trace has been developing an Augmented Reality (AR) tour guide technology that can transform any living space, retail store, mall and museum into an interactive brick-and-mortar digital experience for in-person visitors.
• DeepBrain AI develops real-time video synthesis, speech synthesis and Natural Language Processing (NLP) from actor-enabled videos to create interactive AI human avatars with multi-language capability that customers can engage with to address their customer service needs.
• R-Storm specialises in autonomous window cleaning robots that offer a cost-effective and safe alternative for cleaning high-rise buildings. Their window cleaning robot utilises image recognition, pressure sensors and wide-angle cameras to carefully analyse each window to ensure accurate cleaning.

Meanwhile, the six other startups that composed the first batch of the GBA Accelerator program also had the opportunity to land their technology in New World Development's construction and facility management lines of business.

They were able to land four commercial pilots and co-develop two product collaborations with New World Development. These internal business units look forward to continuing such discussions to provide a gateway for these startups in the GBA.

Building cloud-native applications

Microsoft Hong Kong, the technology partner for this accelerator programme, has been supporting the startups to bring their innovations and solutions to life by enabling them to build, run and manage applications on Microsoft Azure.

The startups have deployed  Azure's wide range of products, such as AI, IoT, machine learning and mixed reality to help realise their business propositions and innovative dreams while accelerating the digital transformation of the GBA.

"A robust, trusted, and secure cloud infrastructure is essential for innovative companies in this cloud-first era. As part of our mission to deliver enterprise-grade cloud infrastructure to support the GBA's digital economy, we launched Azure Availability Zone in Hong Kong last year to add additional capabilities and improve resilience for companies in the GBA,” said  Cally Chan, general manager, Microsoft Hong Kong and Macau.

She added: “We support innovative international startups to land their innovations on Azure technology to develop scalable and agile solutions in a secure environment and bring their ambition to life. We wish to continue paving the way for more tech unicorns to enter the GBA."

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The new joint venture company based in Singapore sees a tremendous opportunity in the region with the increased adoption of virtual healthcare and growing investments in digitalisation by healthcare institutions.

“Owing to the rise of artificial intelligence, IoT, and big data in healthcare, the region’s digital health market, valued at US$40.3 billion in 2021, is expected to expand to US$326.7 billion by 2030 at a CAGR of 26.5%. As such, Healthcare Triangle’s entry into the region couldn’t be timelier,” said company chairman and CEO Suresh Venkatachari.

The company’s expansion into the region is expected to bolster the role of Singapore as a medical innovation hub. With their experience working in the developing healthcare technology industry in the US, Healthcare Triangle aims to help healthcare companies scale their digital solutions and innovation in the region.

Fostering partnerships for a resilient healthcare ecosystem

Meanwhile Healthcare Triangle will be  fostering partnerships and collaborations that help create better and more robust digital healthcare solutions in the Asia Pacific.

Specifically, the company plans to tap into Shankar Group, a leading diversified enterprise in FMCG, property development and services presence across the region, including South Asia, the Middle East, Japan, and Australia to expand its services all over the ecosystem.

Partnerships have been crucial  in enabling Healthcare Triangle to create a resilient healthcare system. It is one of the few providers in the region that has such a comprehensive network of partners that allows them to support regional and global healthcare projects.

The company is HITRUST certified and a premier partner of Amazon Web Services (AWS), Google Cloud (GCP) and Microsoft Azure to provide multi-cloud services to customers. To provide holistic digital health solutions, it collaborates with EPIC and Meditech, leading Electronic Health Records (EHR).

Opportunity abounds across the region

According to McKinsey, digital health in Asia could collectively create up to US$100 billion in value by 2025, up from US$37 billion in 2020.

A large population of the APAC region still lives in remote areas seeking digital healthcare services. Increasing awareness about telehealth services and the growing demand for low-cost remote patient monitoring services are expected to drive the market in the next ten years.

The growing need for clinical information systems and electronic medical records will propel digital healthcare platform adoption.

“We are confident that our platform solutions will elevate healthcare and life sciences businesses with the power to transform and manage their cloud infrastructure across any CSP (Cloud Service Provider) and empower businesses with utmost security and compliance to harness the full potential of their data and thereby speed up their data-driven digital transformation journey,” said Venkatachari.

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"Technologies such as digital twins, smart streetlights, micro-grids, computer vision, smart city management platforms, and micro-mobility are all growing in popularity and can help with decarbonisation," said Dominique Bonte, vice president for verticals and end markets at ABI Research.

The research firm cited a couple of examples where these strategies have a direct impact on energy consumption, and they also encourage citizens to make a better choice to help their city decarbonise.

One is  London’s recent expansion of the ULEZ (Ultra Low Emission Zone) which uses a variety of technologies such as ANPR (automatic number plate readers), CCTV cameras, and environmental sensors to assess the impact of the new regulations.

Another example is Singapore's innovation district, Tengah, which deploys a variety of technologies to support decarbonisation including a centralised cooling system, smart streetlights, smart waste removal, a mobile app for citizens' smart metres, and mass rapid transport with a car-free city centre.

Bonte noted that the principles behind smart city technologies, such as increasing efficiency, better data management, and better decision making are also essential for decarbonisation and reaching net-zero goals.

He added that technologies can enhance decarbonisation through more efficient energy use, better project planning, predictive maintenance, greener mobility options (such as e-bikes and e-scooters), and greater urban management through better data management.

"Cities have a great opportunity to influence how we reach net-zero goals through their ability to regulate, purchase, and influence their services. By opting for smarter, more resilient solutions they can reach and maintain their decarbonisation goals to increase the health of their citizens and the wider community," Bonte said.

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Based on recent figures from Counterpoint Research, the demand for 5G AIoT solution is expected to skyrocket, with shipments of 5G AIoT modules reaching a CAGR of 84% between 2022 and 2030, as the combination of AI and IoT open new possibilities for industries requiring automated real-time decision-making and data analysis

Fibocom's AI smart module is bound to play a crucial part in the industry, with the potential to empower a massive range of compute-intensive use cases.

Equipped with the Qualcomm QCS8250 IoT solution, Fibocom's new SCA825-W module integrates an octa-core Kryo 585 CPU, Adreno 650 GPU, dedicated NPU 230 (Neural Processing Unit), as well as Hexagon DSP for machine learning.

The module can deliver a computing power of up to 15 TOPS (Tera Operations per Second), enabling complex AI computing performance with exceptional features.

"With AIoT continuously transforming every industry, high-performance AI modules will become an important pillar," said Eden Chen, general manager of MC Product Management Dept., Fibocom. "Our newly-launched AI smart module SCA825-W is an exceptional part of the Fibocom smart module family, which will take a big step forward in the AIoT field with technological advancements."

Featuring a powerful Spectra  480 ISP (image signal processor) Adreno 995 DPU and Adreno 665 VPU, Fibocom SCA825-W supports up to seven concurrent cameras, triple 4K display and video encode at up to 4K resolution at 120 fps, 8K at 30 fps (frames per second), offering superior image capturing, processing and displaying capabilities.

In addition, the module supports 5G, Wi-Fi 6.0, Bluetooth 5.1 as well as 2×2 Wi-Fi MIMO multi-antenna technology, which allows various wireless connectivity options for industrial and commercial use cases. It also supports Android 10 operating system and a wide range of interfaces (MIPI-DSI, I2S, PCIe, UART, USB, I2C, SPI), enabling much flexibility and ease of integration to meet the application demands of the AIoT industry.

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This is one of the key takeaways from the “Emerging Giants in Asia Pacific” report, which looks into the region’s maturing technology-focused ecosystems that are producing billion-dollar companies at a rapid rate.

"Fast-growing technology start-ups are the new wave of SMEs contributing towards economic growth and more. Looking ahead, the global push towards carbon-neutrality will be a major driver of innovation as traditional sectors go green, and Emerging Giants will likely play a key role in developing the technologies that can reduce carbon emissions and promote more responsible stewardship of the environment. Asia will be a crucial battleground in the fight for a more sustainable future," said Honson To, chairman, KPMG Asia Pacific and KPMG China.

Close to over 6,500 technology startups with a valuation of up to US$500 million were studied across 12 markets, including China, India, Japan, Singapore, South Korea, Australia,  Indonesia, Hong Kong, Malaysia, Taiwan, Thailand and Vietnam.

According to the report, the emergence of new sector verticals is attracting record-breaking investments, leading to a proliferation of larger, more valuable startups in the region.

Beyond Fintech and SaaS

Beyond the traditional sectors associated with new economy businesses such as FinTech or software-as-a-service, the report identified around 120 technology-related industry subsectors among these businesses, with blockchain, smart city, and sustainability and ESG verticals being the most prominent.

Sustainability and ESG verticals such as EV charging infrastructure, sustainable packaging and sustainable fashion are among the top 20 subsectors, making sustainability-related products and services a key focus for roughly 15% of the emerging giants identified.

The top 20 list also included four health-associated verticals, including assistive tech, AI-powered drug discovery, neurotechnology and mental health technology.

Meanwhile, the smart city-associated areas, such as IoT security and digital twins were present in the leading 10 subsectors. Virtual collaboration technologies also feature prominently with two categories – virtual events and low-code/no-code – making the top 20 list.

Advanced computing technologies were also well represented, with quantum computing making the top 5 and cognitive computing making the top 20.

"Emerging Giants in Asia Pacific excites us because we see the start-up ecosystem as complimentary to the established end of the financial services industry: they're a source of innovation, and invigorate both local and regional economies with their dynamism," says Surendra Rosha, co-chief executive, HSBC Asia-Pacific.

Other key findings

Daren Yong, head of technology for media and telecommunications, KPMG Asia Pacific, noted that the region’s emerging giants are bold, ambitious and cutting-edge in the new platform and software applications they are offering.

“Most importantly, they are transforming and pioneering the technology landscape over the coming years, in addition to thinking about what is useful to their customers now," said Yong.

Meanwhile, below are other key findings from the report.

• While a repeat of the record-breaking private investment levels in 2021 is unlikely, 1Q 2022 figures suggest that 2022 is on target to exceed both 2020 and 2019 funding levels in the Asia Pacific. Australia, Malaysia and South Korea have already seen deal values pass or nearly pass 2020 totals.
• As the world's biggest fintech adopter, the Asia Pacific region has experienced a boom in financial services transformation within the last two years as fintech applications progress in tandem with user uptake. Considerable interest in cryptocurrencies has also led to a surge in crypto financial services providers and blockchain players.
• Top challenges faced by Emerging Giants include navigating regulatory complexity and securing technology talent. Formulating effective ESG and tax strategies, as well as leveraging government incentives and implementing management processes for distributed workforces, will be cornerstones of future growth.

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The  ESS will contribute to helping the SGMS to improve the energy efficiency of port operations by 2.5%. It will also reduce the port’s carbon footprint by 1,000 tCO2e per annum, the equivalent of removing around 300 cars off the road annually.

“Electricity demand will grow in the next decade with increasing electrification. The adoption of innovative demand-side technologies such as smart energy management systems and energy storage systems will help us optimise our energy supply and power grid capabilities,” said Ms Jeanette Lim, director of the industry development department at the Energy Market Authority (EMA).

She added that  innovative digital solutions such as this project will play a part in making Singapore’s energy systems more efficient and resilient.

The SGMS project is part of the S$8 million partnership between the EMA and PSA Corporation (PSA) to transform PSA’s energy usage in port operations through the use of smart grid technologies and energy management systems. A consortium led by Envision Digital has been tapped for the project, which also includes the installation of solar panels.

The EMA-PSA partnership is part of EMA’s Accelerating Energy Storage for Singapore (ACCESS) programme to facilitate ESS adoption in Singapore by promoting use cases and business models. This project will also go towards supporting EMA’s target of deploying at least 200 MW of ESS beyond 2025.

Real-time automated forecasts

With the dynamic nature of port activities, energy demand can fluctuate throughout the day. Port operations involve the use of energy-intensive equipment such as cranes and prime movers. Due to the dynamic nature of port activities, the energy demand can fluctuate throughout the day.

The ESS is managed by the EnOSTM platform uses machine learning to provide real-time automated forecasts of the terminal’s energy demand. This enables long-term planning of port assets, short-term scheduling and real-time energy management within the Pasir Panjang Terminal to reduce overall energy costs and carbon footprint.

Whenever there is a forecasted surge in energy consumption, the 2 megawatt/2 megawatt-hour battery ESS is activated to supply energy to help meet demand. With this enhancement to Pasir Panjang Terminal, spikes in energy demand of the port will be minimised.

“As a premier hub port driving innovation, digitalisation and sustainability, PSA can play an active role in contributing and co-creating Singapore’s smart grid architecture and energy systems. We are excited to partner EMA in unlocking the full potential of battery energy storage solutions to achieve cleaner and more efficient energy for our operations. As PSA enhances efficiency with port automation, we will continue to drive collaborative innovation with our partners for greater resilience in our energy future,” said Alvin Foo, head of new technologies and sustainability at PSA.

Meanwhile, at times when the ESS is not being used at the terminal, it will  participate in the National Electricity Market of Singapore to provide ancillary services to the power grid and to generate revenue. Insights from the project may also validate the possibility for commercial and industrial users to adopt ESS to serve multiple purposes, such as demand management on-site and providing commercial ancillary services to support power systems.

Sustainable development journey

Tan Joo Hong, head of global ports solutions at Envision Digital said its collaboration with the PSA will result in a reference model for ports embarking on sustainable development journey.

“With energy, machines, and systems orchestration through the use of EnOSTM, our jointly developed SGMS solution will support PSA in its sustainable development initiatives such as large-scale electrification and enable better management capabilities when PSA adopt different green energy sources,” said Tan.

Insights from the SGMS can also be applied for advanced energy management and optimisation at the Tuas Port, which would be the world’s single largest fully automated terminal upon completion in the 2040s. For greater sustainability, retired batteries from port equipment such as automated guided vehicles can be repurposed into second-life ESS.

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According to a Digitimes research report, the country’s ICT industry has shifted from focusing on hardware to hardware/software integration models. The industry is combining big data analysis and AI applications in public IoT to facilitate the development of smart city management.

Tools such as IoT, AI, cloud computing, and communications technologies are efficiently integrated with urban infrastructure to produce economic benefits and improve quality of life.

“Taiwan's expertise in semiconductor and hardware is important to smart cities' development as more data is being used to improve AI systems, resulting in rising demand for stronger infrastructure and hardware with next-generation AI semiconductors,” said Dr. Ayesha Khanna, co-founder and CEO of Addo, an AI consulting firm based in California.

Khanna will be one of the speakers at the upcoming smart city webinar in Taipei later this month to be hosted by Digitimes Asia.

Khanna believes that whether it is AI, robots, 3D printing, Internet of things or 5G, smart city's development should not start purely with technologies but the idea of assisting people to solve their problems or become the aspirational goal for citizens.

It is estimated that the business opportunities of smart cities will reach US$2.6 trillion in 2025, mainly in the Asia Pacific region. This includes sectors such as smart poles, building, parking, monitor, government, transportation, fire protection, water conservancy and WITMED.

“When people want to have better energy and waste management in their city, designers can create an AI solution for monitoring energy usage that can turn streetlights on and off with a built-in smart lighting system. They can also build a centralised trash collection mechanism with sensors and have robots powered by AI to collect waste all around the neighbourhoods to reduce traffic and road congestions,” Khanna said.

Collecting and integrating public and private data

Khanna pointed out that it also important to collect and integrate publicly available data and data from the ecosystem's private firms to form a system.

For example, by combining data of taxi companies and traffic light operation, it reduces people's waiting time for taxies, while traffic congestion can also be significantly lowered with the system's assistance in rerouting or changing the traffic lights.

Technologies for smart healthcare

Nowadays, because of the pandemic, the number of hospital visits via online meeting software or telemedicine services increased dramatically as people find it more convenient and efficient.

The technologies used by medical care system are also making improvements with some designers beginning to adopt biometric sensors onto the terminals for the machines to collect more patients' data, giving doctors more information to make intelligent diagnosis, such as handheld ultrasound products that can be connected via smartphones for patients to check on themselves via AI or by medical staff nearby and then send results to their doctors.

“Technologies for remote medical care are a key area that many IT companies have devoted their R&D effort to. Ambulances built with remote medical care system can connect doctors with ambulances care assistants for them to do check-ups while transporting patents to the hospital. The doctors can also make an examination over patients' injuries via a head-mounted display (HMD) to save time,” said Khanna.

Vital role of 5G in smart city

However, Khanna said all these innovations still rely on 5G, which allows devices to communicate with each other with its fast transmission speed, and has brought a revolution to the manufacturing industry and factories.

In Singapore, a lot of investments are being made for deploying 5G infrastructure throughout the city. This is also the case for many countries including the US.

As smart systems are adopting more sensors to enhance their data collection ability, 5G's commercialisation has become the key to unlock the potential of IoT.

With telecom carriers worldwide keenly expanding their 5G infrastructure, Dr. Khanna is optimistic about the birth of more new smart systems and the rapid development of smart cities worldwide.

“The future of smart city will not be operated by one large central AI, but multiple small ones. Issues within smart cities' key sectors such as healthcare, energy and education will continue to be overseen by government departments or public sector companies with them using AIs to optimise and create innovations for their services,” said Khanna.

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The annual gala concert dubbed "A Lovers' Reunion" will give the audience a brand-new symphonic experience driven by the integration of cutting-edge AI technologies developed by researchers from the HKBU's Augmented Creativity Lab.

The HKBU Symphony Orchestra will share the stage with an AI virtual choir to perform a newly arranged choral-orchestral version of the song Pearl of the Orient. It will be the world's first AI choir to perform a choral piece with Chinese lyrics.

“The first human-machine collaborative performance of its kind in the world presented by HKBU at the Gala Concert is an important outcome of the 'Building Platform Technologies for Symbiotic Creativity in Hong Kong' research project. It is also a milestone of AI research revealing the unlimited potential of human-machine symbiotic creativity,” said Professor Guo Yike, vice president for research and development at the HKBU Augmented Creativity Lab.

Professor Guo is the project leader of a research project entitled "Building Platform Technologies for Symbiotic Creativity in Hong Kong" – a HK$52.8 million research fund awarded by the Theme-based Research Scheme (11th round) under the Research Grants Council (RGC) for a period of five years.

He added: “HKBU is dedicated to building a world-class AI art-tech platform that will drive a new revolution that transforms the creative and cultural industries. It will enable Hong Kong to assume a leading position in art-tech on the global stage.”

For the gala concert, Professor Guo’s team has also trained an AI artist to create a cross-media visual narrative based on the lyrics and music to accompany the choral piece. The audience is invited to share the AI's imagination of Hong Kong as the Pearl of the Orient.

Another highlight of the concert is a ballet performance featuring AI virtual dancers in Ravel's Daphnis et Chloé, accompanied live by the HKBU Symphony Orchestra. The ideas for the choreography come from the natural world, which provides dance movements inspired by a newly discovered species of box jellyfish in Hong Kong. In collaboration with professional dancers from the Hong Kong Dance Company, the AI-generated dancers have been trained to perform the ballet with movement-data collected by HKBU scientists.

The concert will also spotlight the artistic prowess of our award-winning student musicians in the performances of Saint-Saëns's Introduction and Rondo Capriccioso in A minor, Op. 28; Borne's Fantaisie brillante sur 'Carmen'; and Lauryn Kurniawan's Rasa for string quartet and gamelan.

Professor Johnny  Poon, who is also the music director and conductor of the HKBU Symphony Orchestra and the Collegium Musicum Hong Kong, said: "In addition to celebrating HKBU's young musicians, the innovative concert showcases how the University is using technology to push the envelope of human imagination in the arts and cultural sphere.

"By leveraging our established strengths in both the arts and sciences, HKBU is taking a trans-disciplinary approach that will advance the development of the arts, culture and creative media in Hong Kong. Our art-tech research also enables musicians and artists to go beyond the traditional forms and interact with the audience in brand new ways."

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The company, primarily known for its security products and applications, deployed an intelligent video system to monitor the animals’ activities and their interaction with humans. The system integrates professional video software with dedicated functions including AI-equipped cameras that can identify this unique animal automatically.

"The protection of pangolins is of great value in protecting the biodiversity in our forests," said Li Chen, director of Xizijiang Ecological Conservation Center, a non-profit organisation for monitoring, studying, and protecting wildlife.

Focus has been placed on surveying and monitoring wild pangolin populations and their habitats. Patrolling forests and mountains has radically diminished poaching efforts while also strengthening on-going research on the artificial breeding measures currently underway.

“The intelligent video system allows for smart, information-based and real-time monitoring of pangolins. It relieves researchers from patrolling pressures and provides precious data for the scientific research of pangolins. We are expecting more technologies to be used in the future of the Wuquinzhang Reserve to protect pangolins, so that more of them can thrive here,” he added.

Before the system was installed, research in the reserve was impeded by the lack of data and video footage on the local ecosystem in general and pangolin activity in particular.

Researchers were forced to travel dozens of kilometres on foot deep into mountainous areas and dense, unfriendly forests only to collect very limited data. After the Hikvision system was put into place, however, workers have been able to access large amounts of video footage, studying and documenting pangolin living habits. These valuable materials currently help reveal and restore populations as they facilitate the work of researchers.

Critically endangered

Known as “guardians of the forest”, pangolins are ancient creatures that appeared in fossil records possibly going as far back as 35-55 million years. Even with the strong shield pangolins wear, their population has declined at an alarming rate – the result of poaching and illegal trade.

What’s more, deforestation and intrusive human activities have disrupted their forest ecosystems extensively, leaving pangolins vulnerable. The destruction of their habitats further exacerbates their plight. Pangolins feed almost exclusively on ants and termites. Such a simple diet makes them particularly poor at adapting to changes in their environment.

In China alone, its population is estimated to have decreased by an exorbitant 90% since the 1960s, prompting the International Union for Conservation of Nature (IUCN) to put the Chinese pangolin on its red list as a critically endangered animal.

Governments and international organisations have intensified their efforts to crack down on poaching and illegal trading of pangolins over the years. Significant resources have been dedicated to the animals' protection and breeding in the field. The United Nations has declared the third Saturday of February as "World Pangolin Day" in order to raise awareness about protecting these creatures across the globe.

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“We are leading the way in leveraging AI technology to empower a wide range of industries. Our partnership with Alfa Romeo F1 Team ORLEN will unleash the potential of AI to transform the motorsports industry by taking its performance to new heights. We look forward to combining our latest SenseAuto technology with F1’s brand to revolutionize motorsport experience,” said

Xu Li, co-founder, executive chairman of the board and CEO, SenseTime.

To mark this technology partnership, the former’s branding was featured prominently on the sidepods of Alfa Romeo’s F1 cars during last weekend’s British Grand Prix, as it will be in future Grand Prix Races.

AI offers many possibilities to improve a car's performance, helping drivers maximise their decision-making process. The technology also optimise racing strategy through reinforcement learning of optimal race strategies, speech transcription, anomaly detection in the race car’s sensor data, comprehensive competitor analysis and competitor database.

The technology partnership between the two companies represents a shared passion for innovation, and a desire to pursue new frontiers by reshaping the way technology drives racing.

Frédéric Vasseur, team principal of Alfa Romeo F1 Team ORLEN, said: “Artificial Intelligence is the new frontier of innovation. It will influence many fields of applications – motorsport included. Our partnership with SenseTime allows the team to collaborate with a global leader in this growing sector, making sure we explore every opportunity to gain an advantage over our competition and push the boundaries of technologies together.”

SenseTime has been  leveraging AI technology to empower a variety of industries globally, including the Middle East through its partnerships with local clients. Racing offers an abundance of opportunities for AI to enhance data processing and provide an advantage in overall performance.

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AI Dynamics' entry into the Soracom Partner Space builds on previous collaboration between the two companies in Japan, where AI Dynamics has provided pre-built, fully trained AI/ML algorithm libraries for use with Soracom's reference edge computing camera (“S+ camera basic”).

These libraries let users rapidly apply AI edge capabilities to a wide range of use cases, from inventory management and industrial process optimisation to parking lot capacity tracking, license plate recognition and more.

“Running artificial intelligence and machine learning algorithms at the edge is a crucial capability for IoT, but very few customers have the tools today to develop ML systems, train models and deploy, manage, or maintain AI edge devices,” said Kenta Yasukawa, co-founder and CTO at Soracom.

He added: “Combining AI Dynamics’ strong algorithm libraries and ML expertise with Soracom’s connectivity and edge device management platform lets IoT innovators offload undifferentiated heavy lifting and focus on bringing new products and services to market quickly and operating efficiently at scale.”

AI Dynamics’ easy-to-use and highly accurate end-to-end AI platform, called NeoPulse, is simple to implement for every industry, business and device. The company specializes in solving a wide range of business problems using AI, with a focus on healthcare, life sciences and Industry 4.0.

NeoPulse enables engineers to build deep learning models faster than using off-the-shelf libraries while handling dataset management, model tracking, deployment and monitoring automatically. This proven joint solution effectively gives end users a plug-and-play AI edge camera complete with an AI/ML algorithm that suits the target use case from day one with no custom code required.

“Our founding belief remains that everyone should have access to the undisputed power of AI,” said Rajeev Dutt, founder and CEO of AI Dynamics. “We are extremely pleased with the ongoing partnered work happening in Japan, and we’re looking forward to offering the fruits of that labour to all S0racom customers and Partner Space members.”

In May this year, Soracom announced the global expansion of its Soracom Partner Space program, which now reaches more than 800 best-in-class members throughout the world, including more than 100 certified partners representing hardware, software, solutions and integration services.

Soracom Partner Space members help IoT innovators accelerate time to market with as-needed access to complementary, best-in-class solutions and services that are ready to integrate at every level of the IoT stack.

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The four Asia Pacific cities are joined on top of the list by Copenhagen, Amsterdam, London and Paris in Europe and New York and Washington DC in the United States.

The index was produced by Economist Impact and supported by NEC.

According to Ritu Bhandari, manager for policy and insights at Economist Impact, smart cities will be safer, cleaner and more inclusive urban landscapes, where citizens enjoy better public health and services, more efficient transport and major economic improvements to be shared as public goods.

“The index highlights how outlier cities are leveraging technology to improve quality of life for millions of citizens around the world. While we see strong leadership from cities in Western Europe, the table is led by major cities from a wide geographical spread. The most significant improvements were delivered against tightly defined goals – a critical success factor for urban digital transformation,” said Bhandari.

A peek at the top performers

Copenhagen, Amsterdam, Beijing, London and Seoul performed the best, with successful open data projects and major strides in smart technology-powered sustainability projects like utility management.

Cities with very defined goals realised the greatest benefits: European cities ran highly impactful traffic management systems, while Beijing made progress using applied digital technologies - tackling air pollution, optimising its utilities and promoting its sharing economy. The Atlantic nation cities led in open data innovation with a boom in travel and mobility apps.

Sustainability was the biggest impact area highlighted by the White Paper, with leading smart cities realising major gains in air quality through smart utility management. Sustainability brought the highest overall scores, with Copenhagen, Seoul and Toronto scoring highest for their use of digital technology to support urban sustainability.

Copenhagen and Singapore were the most connected cities, followed by Zurich, Beijing and Sydney. Singapore’s strategy for developing digital connectivity is built on the premise that AI, 5G and cyber security will drive the country’s growth and innovation post-covid. Smart cities are anticipated to drive economic growth: 5G alone will enable an estimated US$660 billion global mobility and transportation market by 2035.

Internet services impact smart city goals

According to the index, unaffordable, unreliable or inaccessible internet services impact other city level goal, with half-a-million households reportedly lack a reliable internet connection in New York City, for instance, disadvantaging low-income children for remote learning.

By contrast, Washington DC has offered low-cost or free services and devices to families unable to afford a broadband subscription and Paris has the most affordable mobile data of all the cities analysed.

Digital technologies enable progress in public health

Since the pandemic, digital technologies have enabled real progress in public health. In Asia, apps were central to managing COVID-19, while telemedicine and real-time remote monitoring of chronic patients has marked digitisation everywhere. In New York, for instance, a diabetes-prevention initiative for adults has reduced the risk of type 2 diabetes in high-risk individuals by 58%.

Singapore, São Paulo and New Delhi ranked the highest for their delivery of digital municipal services. New Delhi ranks high in part because of the success of Aadhar, India’s ground-breaking national digital identity scheme. In Korea, Metaverse Seoul, announced in November 2021 by the Seoul Metropolitan Government, will provide citizens with access to government services via the metaverse.

The index also noted that involving citizens in the design of smart city schemes underpins meaningful inclusion, a critical success factor for smart city projects, along with delivery against tightly defined goals.

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According to Mark Verbloot, senior director of  product, solutions and systems engineering for Asia Pacific Region at Aruba Networks, the turbulence in manufacturing and the supply chain seen in the last two years have underscored the need for manufacturers to accelerate their transition from “mass production and economies of scale to prioritizing market and customer responsiveness".

"In response to the issues they face, high-tech manufacturers are increasingly aligning their technology investments to secure and optimise operations while addressing data privacy and security concerns even as they build greater resilience in the long-term,” said Verbloot.

The study, entitled “High-Tech Manufacturing Begins with High-Performance Networking and Security Solution”, was conducting by Forrester Consulting on behalf of Aruba – a Hewlett Packard Enterprise company, surveying more than 270 business and IT decision-makers from high-tech manufacturers in Australia, India, Japan, Malaysia, South Korea, Taiwan, and Thailand in the first quarter of 2022.

The study found three in four manufacturers in the region are prioritising innovation and automation for greater operational efficiency and resilience over the past 12 months.

It also found that edge solutions, IoT applications, and networks were essential to driving innovation for 63% of respondents, with 61% indicating they had optimised manufacturing processes with automation and robots. Meanwhile, 69% of respondents said they were either piloting or already using cloud-managed networking and security solutions to benefit from improved flexibility, scalability, and defense capabilities.

Furthermore, 64% of respondents who indicated their intention to build on previous investments in AI-powered software to optimise operations, implement predictive capabilities, and optimise productivity.

Data privacy and security concerns

With the increased connectivity and digitalisation of processes and operations, the study states that the collection, transmission, and utilisation of the breadth of data is becoming critical to the sectors' ability to scale operations and address the challenges posed by privacy and security concerns.

Indeed, more than half (52%) of APAC decision-makers ranked data privacy and security concerns within their top five challenges when implementing networking solutions, while 48% said the lack of cybersecurity features in legacy IoT devices is one of their top five challenges. About 18% ranked information technology/operational technology (IT/OT) divide as one of their top two networking challenges.

In response to data privacy and security concerns, manufacturers have plans to leverage emerging technologies and automation to secure their operations in the next 24 months.

These solutions include cloud-managed networking (38%) and SD-WAN (37%). More than 50% of manufacturers are also expanding, upgrading, or planning to invest in Zero Trust Edge solutions in the same timeframe, while 57% said identity-based traffic segmentation helps them to achieve their business goals.

"As we emerge from the pandemic, there is a need for the manufacturing industry to develop greater agility and flexibility in their operations. Innovation is at the heart of decision-makers’ priorities but manufacturing leaders need to act now by leveraging high-performance network and security solutions to help the smart manufacturing industry scale effectively,” said Verbloot.

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"Sharks and rays play an important role in maintaining marine ecosystems by keeping other fish populations in check. If stripped from our oceans, there would be dire consequences for ocean health, which would affect us, and our food security,” said Dhanushri Munasinghe, project coordinator at the Conservation International Singapore.

He added: “As one of the world's most significant transhipment hubs, Singapore is well positioned to combat illegal wildlife trade. Conservation International, supported by Microsoft and other partners, is excited to support Singapore and the Singapore National Parks Board's leadership in conservation through the creation of Fin Finder".

The mobile app was created by a Singapore-led team from Conservation International in consultation with NParks with support from the Microsoft AI for Earth program. It will be used by officers from the Singapore National Parks Board to combat illegal wildlife trade.

Fin Finder, a complex AI and cloud based mobile application that runs on Microsoft Azure, was created in just nine months to address a pressing need. The project was supported by a highly collaborative consortium of global experts in conservation and technology, with resources, data, and volunteer contributions from Microsoft, Conservation International, the NParks, Sineurope, Rumah Foundation, Coastal Natives and Wild Me.

Stopping illegal trade of sharks and rays

There are approximately 1,000 species of sharks and rays in the world, of which over 30 species are listed under the appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) for regulated trade.

Between 2012 and 2020, more than 160,000 kilograms of fins from CITES-listed sharks and rays have entered the Singapore waters. The current process requires officers to collect the fins from each shipment for DNA testing to determine its species. This takes an average of up to one week.

Ivonne Higuero, secretary general of CITES, said: "The first step in ensuring international trade complies with CITES regulations comes with the, sometimes difficult, process of identifying the species being traded. Fin Finder is a welcome and innovative addition in the identification of fins and will complement other tools such as iSharkFin. It will give customs and enforcement officers an easy-to-use tool that will contribute to an international trade in CITES-listed species that remains legal, traceable, and sustainable."

Fin Finder optimises the identification process by allowing officers to take photos of fins that will be matched against a database of over 15,000 shark and ray fin images via an AI-driven algorithm in the app. In a matter of seconds, the AI-powered app which runs on Microsoft Azure will quickly and accurately provide a visual identification of shark and ray species onsite and empower officers to quickly flag suspicious fin shipments for further DNA testing to stop the illegal trade of shark and ray fins.

When wildlife species are traded illegally, the consequences are far-reaching to many ecosystems, economies and communities around the world, according to Dr Adrian Loo, group director of wildlife management, NParks.

“By using advanced technology in the creation of Fin Finder, we can strengthen the enforcement against the illegal trade of sharks and ray species following CITES regulation, and boost Singapore's capabilities in conserving precious biodiversity,” Loo said.

Fin Finder as a single-platform directory

Beyond identification of illegally traded shark and ray fins, officers from the NParks will also use Fin Finder as a single-platform directory of relevant shark and ray species. The app also offers onsite access to reference materials that can be used for validation of CITES-approved permits or shipping documents. This feature is expected to reduce the time and effort spent to on shipment validation, enabling officers to help put a stop to illegal wildlife trade more quickly.

Richard Koh, chief technology officer, Microsoft Singapore,  said: "AI has the potential to solve critical environmental challenges. By taking AI tools out of the lab and putting it into the hands of experts in the field, we can accelerate new solutions for a better world. That's why we are proud to support Fin Finder as it protects global shark and ray populations and preserves our ocean life. By conserving wildlife with help from technology, future generations can enjoy our natural world, as we empower every person and every organization on the planet to achieve more."

Fin Finder is a project in Microsoft AI for Earth, a global program that supports organisations applying responsible AI and cloud computing to address critical environmental issues. The program is part of Microsoft's AI for Good initiative, which aims to solve the world's most challenging problems, from climate change to agriculture, biodiversity and water. To date, AI for Earth has awarded 138 grants to people and businesses in more than 45 countries globally.

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The companies will also collaborate around creating and deploying smart factory IoT solutions for VinES batteries manufacturing and VinFast electric vehicles manufacturing.

“Vingroup has always been a pioneer in bringing consumers smart products and services integrated with world-class technologies, advanced features and outstanding experiences to improve their lives. We work towards realising this vision through partnerships like this, to create a smarter and more sustainable future for everyone,” said Le Thi Thu Thuy, vice chairwoman of Vingroup.

The collaboration is part of a continued effort from Vingroup to work with top tier global suppliers who can aid with manufacturing development, smart services and electric vehicle initiatives.

Vingroup recently adjusted its orientation and redefined three key groups of activities, namely technology and industry, trade and services, and social enterprise.

To develop the technology and industry group, Vingroup focuses on two main strategies: building Vingoup's technology ecosystem and connecting global intelligence – cooperating with the world's leading technology partners to accelerate the application of the most advanced and new technologies to Vingroup's products and services.

Advancing automotive technology

Under their new MOU, Vingroup and Intel will also  collectively define and build both an optimised and scalable computing architecture for AI training and inference for Vingroup's in-vehicle and cloud applications.

The applications will enable a specific in-vehicle experience for consumers and an optimised multi-cloud strategy to potentially migrate and deploy open-source in-vehicle and in-building applications. They can include high-performance data management systems for ADAS and Infotainment, manufacturing and supply chain management along with enterprise solutions for Vingroup facilities.

Both companies will also work together to define a shared vision of future in-vehicle computing platforms and build scalable in-vehicle computing platforms for Advanced Driver Assistance Systems (ADAS) based on Mobileye technology and infotainment systems that deliver a unique in-vehicle experience for Vingroup and VinFast customers and create a suite of services that will differentiate them from competitors.

"The digitisation of everything is contributing to the insatiable need for semiconductors, especially in the automotive sector. Intel has the depth and breadth of software, silicon and platforms, and process with at-scale manufacturing our partners need for their next-generation innovations. This collaboration with Vingroup can help deliver needed technology innovations for safer roads, more sustainable manufacturing and smarter cities," said Pat Gelsinger, Intel CEO.

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These bioinspired sensors could usher in the next generation of artificial-vision systems used in autonomous vehicles and manufacturing, as well as finding exciting new applications in edge computing and the Internet of Things.

"They will greatly improve machine vision systems used for visual analysis and identification tasks," said Dr. Chai Yang, associate professor at the Department of Applied Physics, and Assistant Dean (Research), Faculty of Applied Science and Textiles, PolyU, who led the research.

Improving machine vision

Machine vision systems are cameras and computers that capture and process images for tasks such as facial recognition. They need to be able to "see" objects in a wide range of lighting conditions, which demands intricate circuitry and complex algorithms. Such systems are rarely efficient enough to process a large volume of visual information in real time—unlike the human brain.

The new bio-inspired sensors may offer a solution through directly adapting different light intensities by the sensors, instead of relying on backend computation. The human eye adapts to different levels of illumination, from very dark to very bright and vice versa, which allows us to identify objects accurately under a range of lighting conditions. The new sensors aim to mimic this adaptability.

"The human pupil may help adjust the amount of light entering the eye," said Dr. Chai, "but the main adaptation to brightness is performed by retina cells."

Natural light intensity spans 280 dB. The new sensors developed by Dr Chai's team have an effective range of up to 199 dB, compared with only 70 dB for conventional silicon-based sensors. The human retina can adapt to environments under sunlight to starlight, with a range of about 160 dB.

Light detectors developed

To achieve this, the research team developed light detectors, called phototransistors, using a dual layer of atomic-level ultrathin molybdenum disulphide, a semiconductor with unique electrical and optical properties. The researchers then introduced "charge trap states"—impurities or imperfections in a solid's crystalline structure that restrict the movement of charge—to the dual layer.

"These trap states enable the storage of light information," the researchers reported, "and dynamically modulate the optoelectronic properties of the device at the pixel level." By controlling the movement of electrons, the trap states enabled the researchers to precisely adjust the amount of electricity conducted by the phototransistors. This in turn allowed them to control the device's photosensitivity, or its ability to detect light.

Each of the new vision sensors is made up of arrays of such phototransistors. They mimic the rod and cone cells of the human eye, which are respectively responsible for detecting dim and bright light. As a result, the sensors can detect objects in differently lit environments as well as switch between, and adapt to, varying levels of brightness—with an even greater range than the human eye.

"The sensors reduce hardware complexity and greatly increase the image contrast under different lighting conditions," said Dr Chai, "thus delivering high image recognition efficiency."

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To help prevent unauthorised access of medical devices, Asimily and Extreme Networks team up to help healthcare institutions prevent unauthorised access of IoT-based medical devices.

Asimily is a provider of Internet of Medical Things (IoMT) risk management platforms, while Extreme Networks is a provider of cloud-based networking solutions.

With this partnership,  Asimily Insights will be integrated into the  ExtremeCloud IQ Controller, a cloud-based wired and wireless network management solution from Extreme Networks.

“Asimily’s intuitive platform helps us identify and respond to the most critical risks to our organisation, and the integration with Extreme’s solutions enables us to enforce policies on devices as needed and address any concerns that can impact the confidentiality, integrity or availability of IoT and medical devices and their data,” said Ali Youssef, director, Medical Device and IoT Security at Henry Ford Health.

“Together, these solutions allow us to fill the gaps we previously had in our ability to manage device security and ensure we can continue to deliver patient services, which is always our top concern,” he added.

Asimily Insights integration with ExtremeCloud IQ Controller provides a seamless solution to detect exploitable vulnerabilities and enforce policies to help identify and prevent cyberattacks.

“ExtremeCloud IQ Controller provides unified services and features in a simplified management console for on and off-premise deployments. On-Premise deployment is critical for many Healthcare Delivery Organizations (HDOs),” said Dinesh Katiyar, Head of Business Development, Asimily. “This integrated solution provides HDOs a best vulnerability management platform with the flexibility to deploy on-premise.”

Asimily Insights uses AI-based analysis to prioritise exploitable vulnerabilities and prescribe clinically viable remediations outside of segmentation and blocking that are easy to implement. These remediations are transmitted to ExtremeCloud IQ Controller to centrally enforce network access policies to secure the device.

In addition, for devices where segmentation is the only option, Asimily Insights generates policies which are transmitted to ExtremeCloud IQ Controller to configure, isolate, segment and micro-segment the devices on the network.

“Extreme’s solutions are trusted by hospital systems and healthcare providers around the world. Our integration with Asimily creates a solution that is specifically designed for healthcare IT teams and enables them to find and address vulnerabilities before they are exploited, as well as ensure that security measures necessary for safe clinical operations are in place,” said Bob Zemke, Director, Business Development at Extreme Networks.

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Called AI Verify, the self-test toolkit aims to promote transparency between companies and their stakeholders through a combination of technical tests and process checks. The is developed by the Infocomm Media Development Authority (IMDA) and the Personal Data Protection Commission (PDPC).

“It is another step forward in Singapore’s AI development. This will promote greater public trust towards the use of AI. We invite industry partners from all around the world to join us in this pilot and contribute to building international standards in AI governance,” said Josephine Teo, Singapore’s minister for communications and information, at annual meeting last Wednesday of the World Economic Forum (WEF) at Davos, Switzerland.

Globally, testing for the trustworthiness for AI systems is an emergent space. As more companies use AI in their products and services, fostering public’s trust in AI technologies remains key in unlocking the transformative opportunities of AI.

Objective and verifiable testing process

Developers and owners can verify the claimed performance of their AI systems against a set of principles through standardised tests. A.I. Verify packages a set of open-source testing solutions together, including a set of process checks into a toolkit for convenient self-assessment.

The toolkit will generate reports for developers, management, and business partners, covering major areas affecting AI performance. The toolkit will transparently show how the AI model claims fared against  test results in areas such as: on the use of AI to achieve what stated outcome; understanding how the AI model reaches a decision; and, whether the decisions predicted by the AI show unintended bias

The toolkit will also assess the safety and resilience, as well as the accountability and oversight of AI systems.

“Rapid digitisation has led to a proliferation of data and improved algorithms. As companies across sectors continue to innovate, this toolkit will enable them to turn concepts of responsible and trustworthy AI into practical applications,” said Chia Song Hwee, deputy CEO, Temasek International and member of Singapore’s Advisory Council on the Ethical Use of AI and Data, which guided the development of the toolkit.

Positive industry feedback

Already, 10 companies from different sectors and of different scale, have already tested and/or provided feedback. These companies are AWS, DBS Bank, Google, Meta, Microsoft, Singapore Airlines, NCS (Part of Singtel Group)/Land Transport Authority, Standard Chartered Bank, UCARE.AI, and X0PA.AI.

“As organisations worldwide continue to harness data and drive increased adoption of AI-based solutions, it is more important than ever to establish the guardrails to ensure this is done responsibly. Singapore has, for some time now, been at the forefront in developing the thinking around the important and emergent subject of AI governance,” said Piyush Gupta, group CEO, DBS Group.

According to Pier Luigi Culazzo, group chief data officer at Standard Chartered Bank, the development of the AI Governance Testing Framework is an integral progress to Singapore’s vision of building a robust digital economy.

“From integration with other jurisdictions to standardisation across industries, the use of IMDA’s framework will go towards enhancing accountability and transparency of the AI ecosystem in Singapore, motivating more organisations to deploy AI responsibly,” said Culazzo.

George Wang, senior vice president – information technology at Singapore Airlines said: “We brought our strong data science and AI expertise and capabilities to IMDA’s AI Governance Testing framework, contributing to efforts to make it a Minimal Viable Product. Through this partnership, we gained insights that enhance our own digital capabilities.”

Singapore’s Land Transport Authority, which participated in the pilot together with its partner NCS, expressed optimism over the AI Governance self-test.

“The Land Transport Authority is in the nascent stage of exploring the use of AI to augment our work processes, and we are mindful that there should be clear guidelines and processes in place for safe and responsible application of the technology,” said agency chief executive Ng Lang.

IMDA is also working together with the U.S. Department of Commerce to build interoperable AI governance frameworks. Beyond the pilot stage of the MVP, Singapore aims to work with AI system owners/developers globally to collate and build industry benchmark, which will enable the city to continue contributing to the development of international standards on AI governance.

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The company announced its plans in the heels of securing a US$15-million Series B funding led by Meituan, China's leading tech and online retail company, and Fosun, a global innovation-driven consumer group.

"While we've previously focused on the Chinese market, 2021 has brought us more success outside China. We're looking forward to making our solutions available to a broader audience and cementing our position as a key player globally," stated Andy Lu, partner & SVP of RobotPlusPlus.

To support its global expansion, the company is set to open an office in Singapore to serve the Asian and Middle Eastern markets.

RobotPlusPlus has a portfolio of robotic solutions for crucial industries such as maritime, ship repair, petrochemicals, and power generation, with hundreds of magnetic crawler robots deployed globally. The company focuses providing aerial work safety for operators while improving the efficiency of Inspection, Maintenance, and Repair (IMR) solutions and lowering operating costs for asset owners.

With its large team of skilled engineers and operators in place, RobotPlusPlus also provides Robot as a Service(RaaS) services to clients, enabling them not only to offer timely and cost-effective services but also to gain insights into industrial application scenarios.

"An aging workforce, rising labour costs, frequent aerial work-related accidents, and the COVID-19 pandemic have had an accelerative effect on the aerial work robotics sector," said Pu Xiao, investment manager at Fosun. "RobotPlusPlus empowers people with robots while helping increase operational safety and productivity. We're excited to support the company in leveraging AI and RaaS to optimise aerial work environments and enable robotic applications."

Hua-yang Xu, founder and CEO of RobotPlusPlus reiterated the company’s commitment to delivering “more transformational results” to its customers

The company plans to use its fresh funding to upgrade current products by integrating more autonomous technologies

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The entry of insurtech has also opened new avenues for insurers to market products, in some cases, create totally new offerings in new locations, not possible with the conventional model for marketing insurance.

Concirrus CEO Andrew Yeoman acknowledged that the pandemic has challenged the insurance industry business model in Asia. He commented that COVID-19 has given the industry problems and opportunities.

"It's given us a problem because operating a business where you're we've been predominantly used to doing face to face work, and then trying to do that remotely has been challenging. And clearly, there's going to need to be some investment going forwards in some of that backend office and infrastructure. The very manual methods of perhaps processing policies have been challenged," he added.

IoT-led innovations in insurance

According to the IMARC Group report, IoT Insurance Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027, the global IoT insurance market reached a value of US$20.2 Billion in 2021. The Internet of Things (IoT) insurance refers to a technological solution that collects, transmits, and shares data of the client to insurance companies.

Yeoman acknowledges that IoT is creeping in everywhere. "Everything that we see in touch with seems to be monitored these days. What we're starting to slowly see is that the insurers are building products around that," he added.

"We're seeing it rising everywhere at the same time, both in personal lines and in commercial lines. And really the most exciting part of it is that it gives you some that hyper-personalised proposition so around how you work, how you're behaving and how you're driving."

The value proposition of IoT in insurance

IoT brings with it data not previously available to insurers. Yeoman commented that the data represents the behaviour, in the form of how, where, and when, of the asset. He cited the example of vehicular insurance. Where traditional insurance would mean that the insurer would only have a record of an incident during an insurance claim, embedded insurance describes a behaviour that is a far better indicator of risk than the static factors that have been used previously.

According to Yeoman, from the insurer's perspective, the data that they get from IoT devices will allow for disaggregation of risk. He posited that using data gathered by IoT devices, insurers can price their products and services to the risk profile of the insured.

"The secondary benefit that it also provides is the concept of nudge behaviour. I think that notion of those additional benefits changes our relationship with an insurer from just being somebody that's there, when things go wrong, to somebody that can help me live a healthier life," he added.

Supporting the operations of insurers

Beyond the embedding of IoT into insurance products, Yeoman says insurance companies make their living off managing the risks of the insured. He cited the example of insured vehicles – that under the traditional business model, the insurer has no awareness of where an insured vehicle is at any given time, whether it is on the road or parked somewhere, the road conditions and the driving habits or pattern of the driver.

He posited that the insurer would not know how many risks the insurance company is taking during the lifetime of the policy. IoT quantifies some of these risks and provides a granularity of risks down to the individual policy owner.

Importance of data

To realise that example of automotive insurance, it is important that data from IoT devices are collected and processed according to a pre-defined workflow.

To succeed in integrating IoT into the insurance business model, Yeoman says it is important to have a very clear understanding of what their business model is going to be, how that's going to scale, and how they can adopt such a business model.

He posited that insurers would need to be willing to experiment and be able to adapt to what works for them. "They need to see what's acceptable to their policyholders. And they need to do that quickly. I think the short, sharp, focused experience. What can we learn? We call it fail-fast," he commented.

Managing the unknown – IoT skills, experience, and expertise

Yeoman noted that insurers are used to dealing with data – much of it recorded on paper. With an IoT-led insurance model,

Clearly, if you go in with an IoT enabled proposition, you might take on a new supply chain, you might have to buy hardware, you might have to have connectivity issues in terms of SIM cards or other sorts of network connectivity. And you need a supply chain to then say, both procure those but then get those shipped out or installed with a customer or whichever. I think that in terms of the insurance expertise, depending on the particular business case, and the line of business that going into, clearly, it changes the need of an insurer, what skills they need in that supply chain. My one-sentence advice is, don't build that in-house, just partner with somebody who's an expert in that.

Click on the PodChat player to hear Yeoman's insights and recommendations around how the insurance industry can meet the evolving challenges using IoT.

1. How has the insurance industry in Asia evolved in the last five years?
2. It can be argued that IoT is still relatively new as applied in insurance. Can you cite one or two recent innovations around the use of IoT in insurance?
3. What is the value proposition of IoT in the provision of insurance products and services?
4. There are two aspects of IoT that need to be addressed in insurance: risk management and the other is around data privacy and protection.
   1. How are insurers using IoT to better manage their risks? (insight into behavioural analysis)
   1. In your observation, is the understanding of IoT technology, sufficiently mature around data privacy and protection?
5. How important is having a clear business model to benefit from IoT data? And how can businesses adopt such a model?
   1. What skills, expertise, and experience must an insurer have access to benefit from the use of IoT?
   1. When looking to tap IoT, what questions should leadership ask their CIO/CTO to ensure they are in the right direction and frame of mind?
6. What does Concirrus bring to the table?

The post PodChats for FutureIoT: Redefining insurance with IoT appeared first on FutureIoT.

The project called “Own My Voice” seeks to provide a “spontaneous-style” text-to-speech technology, which essentially makes the synthesised voice sounds like a real person in its intonation, pause speed and other features. It hopes to replace the monotonous electronic voice with a more natural one.

Currently, this technology applies to many smart devices equipped with Xiaomi, the AI voice assistant of Xiaomi. The "Own My Voice" project shows spontaneous style text-to-speech technology can also be widely adopted in accessibility areas and improve user experience.

“We are excited to explore multiple values that technology innovation brings to us, such as responding to users' demands for the self-identity and the construction of identity,” said Zhu Xi, technology committee topic convener on Tech for Good initiative at  Xiaomi Corporation.

The backbone of the project is a group of speech technology experts from Xiaomi AI Lab, who have published 37 papers on speech at top international conferences, such as the International Conference on Acoustics, Speech, and Signal Processing (ICASSP).

Deploying voiceprint matching algorithm

To generate the most suitable and personalised voice for intended users, Xiaomi AI Lab gathered voices of 200 volunteers from within the company.

The project team then deploy voiceprint matching algorithm to match the features of donated voices with those of the recipient’s voice. Through this approach, they find the most suitable voice as the basic sound of voice reference for the recipient.

In consideration of personalisation and privacy protection, the chosen real voice is manipulated with complex acoustic modification to form a new and original sound of voice. After this, the Xiaomi project team use spontaneous style text-to-speech technology to train AI model to gradually gain a natural voice rhythm and intonation that can express the emotion and the tone of a human.

"If we notice and address the needs of minority groups at an early stage, the process of technology diffusion could be greatly shortened. This allows the benefits of new technologies to become accessible to users with special needs without delay,” said Zhu Xi.

The "Own My Voice" project combines a variety of advanced algorithms with Xiaomi's self-developed speech technology to ensure the specificity, safety, and high-level of authenticity of the synthesised voice.

Moving forward, Xiaomi will continue receiving feedback from the voice recipient, and further study the feasibility of  this project for a wider range of applications.

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With the opening of flights into Hong Kong, returning residents and visitors still  have to undergo a week-long hotel quarantine to ensure the downward trend of infections in the city.

At quarantine hotels Oasis Avenue – A GDH Hotel and Metropark Hotel Kowloon, robots have been deployed for two purposes: food delivery and disinfection.

“Technology can be used effectively to curb the coronavirus,” said Zhang Tao, founder and CEO of Pudu Robotics. “When it is needed, we have the obligation, the ability, and the willingness to stand with the frontline workers and combat the pandemic. Turning the power of science and technology into an actual pandemic prevention force, we are ready to support and give back to global society with our products powered by advanced technologies."

The Shenzhen-based company donated several of its commercial service robots to the two Hong Kong hotels at the height of the Omicron outbreak.

Its BellaBot food delivery robot is equipped with an automotive-grade independent linkage suspension system, an  intelligent infrared induction tray, and 3D obstacle avoidance as well as the dual Laser SLAM and Visual SLAM positioning and navigation system. The robot’s robust four-layer tray allows the delivery of more than one item at a time.

On the other hand, the company’s Puductor 2 is UV cleaning robot is equipped with dual disinfection modes: ultrasonic dry mist disinfection where the disinfectant is atomised into 10µm dry particles that ensure complete sterilisation by remaining suspended in the air in a random motion, and UV-C Disinfection where a UV lamp is equipped, delivering disinfection with an ultraviolet illumination of 188μW/cm² at 1 meter.

By delivering daily necessities to the quarantine hotels’ guests in a contactless manner, BellaBot minimises the risk of cross infection by avoiding direct contact between staff and guests in addition to helping save on anti-pandemic supplies, while Puductor 2 guarantees safe and healthy indoor environments within the hotels by enabling its 24/7 automatic disinfection. The two robots work in tandem to maximise their effectiveness as a pandemic preventive solution.

Since the outbreak of the Covid-19 pandemic in early 2020, Pudu Robotics has donated several hundred robots to hospitals, isolation wards, quarantine facilities, and several public transit hubs across China to support combating the pandemic. In addition, its service robots have contributed to solving the problems of labour shortage as a result of the ongoing COVID-19 pandemic worldwide.

Further inroads into the retail sector

Meanwhile, Pudu Robotics through its Jordanian partner Quill has been recently tapped to deploy BellaBot robots to promote and distribute Coca-Cola products at supermarkets throughout the Middle Eastern country.

"Unlike traditional retail services, having intelligent robots serve our customers will go a long way in meeting the expectations of various brands when it comes to more personalised and functional service robots, thereby significantly improving the in-store experience for shoppers,” said Zhang. “In addition, the high-tech robot itself will undoubtedly gain popularity among young audiences who love Coca-Cola beverages.”

BellaBot, with its attractive cat-like look and great human-computer interaction, is expected to attract the attention of consumers, particularly youngsters, while circulating around the aisles of retail businesses across Jordan.

“With the global pandemic prevention and control measures becoming normalised and integrated into the day-to-day landscape worldwide, it has become necessary for retailers to adopt a new, no-contact approach with shoppers as the sector shifts to intelligent operations that combines digital mindsets with innovation in merchandising,” added Felix. "The partnership with Coca-Cola Jordan marks the further implementation of Pudu Robotics' strategy to empower innovation across the retail sector by virtue of multiple cutting-edge technologies, including big data and AI."

Pudu Robotics has shipped over 600 units of its delivery and reception robot KettyBot to Chinese dairy giant Inner Mongolia Mengniu Dairy (Group) according to an agreement previously signed between both companies. The robot is being used by Mengniu to promote and hand out its products in supermarkets throughout China, facilitating the firm’s shift to a new intelligent retail model where products are transported and stocked by robots from the traditional one where these same actions are handled by humans.

The post Robots get the job done appeared first on FutureIoT.

"This is a great opportunity for us to showcase our solutions, from devices to software and services, all tightly integrated and presented in a narrative that highlights the impact that we are making to organisations and industries in Singapore," said Nigel Lee, general manager - intelligent devices group at Lenovo Singapore.

"We are putting a spotlight on our efforts as a service-led company in how we are bringing all these incredible technologies – artificial intelligence, augmented reality/virtual reality–into the world, and transforming experiences in the workplace and the classrooms of the future. And we are very proud that we are achieving this in a way that's sustainable,” Lee added.

The event provided a peek into the smart workplace of the future to demonstrate how CIOs can re-examine their IT infrastructure, while keeping in mind aspects such as employee experience and Environmental, Social, and Governance (ESG).

Lenovo showed  its extensive suite of devices, services and solutions through six immersive experience zones.

New suite of building and workplace solutions

The Lenovo's Workplace Solutions zone showed how solutions like simplified workspace booking, utilization analytics, and smart facilities management coupled with professional services can help businesses provide employees with enhanced flexible working options, offering the benefits of both in-office interactions and remote work.

The Lenovo Workplace Solutions portfolio helps businesses and CIOs adapt to the hybrid work era with several smart workspace solutions, including:

• Workspace Booking: Scheduling software offering real-time visibility on workspace occupancy enabling employers to manage capacity better, helps employees book facilities quickly to save time, and improves contact tracing with automated post-event reporting.
• Workplace Analytics: Delivered via a dashboard providing real-time insights on space usage, based on non-invasive data from heat and motion sensors.
• Digital Signage: Content management system that turns traditionally static displays and signages at high-traffic locales and touchpoints into visually-rich multimedia screens that is dynamically updated to convey important updates in a timely manner.
• Smart Locker: Flexible self-service storage service enabling employees to store, pick up and drop off assets securely 24x7 with minimal fuss and reduced waiting time.
• Smart Collaboration: All-in-one meeting room solution with video conferencing software and integrated devices that are easy to use and scale according to meeting sizes, protected by ThinkShield, a suite of security solutions to safeguard users' privacy and data.

A glimpse of extended reality technologies

In 2020, COVID-19 became a catalyst for extended reality (XR) technologies (both AR and VR) to help enterprises maintain business continuity and enable people to collaborate and work remotely more efficiently.

Lenovo showcased its ThinkReality A3 Smart Glasses, which is being targeted for various industries such as manufacturing. For one, Lenovo ThinkReality powered by holo|one software is giving Micron's engineers the ability to keep production facilities running while helping the company meet growing demand for its products.

Meanwhile, Lenovo also demonstrated how Lenovo Asset Recovery Services (ARS) and CO2 Offset Services mitigate security and environmental risks associated with new device procurement and end-of-life asset disposal. These services ensure organizations are procuring, managing, and disposing their technology hardware in a responsible and sustainable manner, while making sure that the entire process is legally compliant, secure, and consistently applied globally.

"In many ways, Lenovo Experiential Day 2022 highlights that Lenovo is no longer just a device-centric company," said Lee, "but an end-to-end solutions provider that is helping customers embark on their journey to digital transformation 2.0 in an era filled with increasing challenges but also tremendous opportunities."

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“It’s important we design in a way that is built for the real world — and doesn’t take you away from it. And AR gives us new ways to accomplish this,” said Sundar Pichai, CEO, Google and Alphabet, during his keynote speech at the conference.

“Let’s take language as an example. Language is just so fundamental to connecting with one another. And yet, understanding someone who speaks a different language, or trying to follow a conversation if you are deaf or hard of hearing can be a real challenge. Let's see what happens when we take our advancements in translation and transcription and deliver them in your line of sight in one of the early prototypes we’ve been testing,” he added.

This is Google’s second attempt at developing smart glasses. It comes 10 years after the debut of Google Glass, a pair of avantgarde spectacles fitted with built-in camera, which raises privacy concerns.

On the other hand, the latest prototype looks like an ordinary pair of glasses. In a video shown at the conference, the new AR glasses are shown displaying  conversations involving English, Mandarin, Spanish and American Sign Language.

“What we're working on is technology that enables us to break down language barriers. Taking years of research and Google Translate and bringing that to glasses,” said Eddie Chung,  “I’m actually looking straight into your eyes, and it seems like you're looking right at me. Making access to information just instant and intuitive. By doing that, technology fades into the background, and we're more connected with the people and the things around us.”

Google has been building augmented reality into many of its products from Google Lens, multisearch, scene exploration, and Live and immersive views in Maps.

“These AR capabilities are already useful on phones and the magic will really come alive when you can use them in the real world without the technology getting in the way,” said Pichai.

At the conference Google also gave a glimpse of its product roadmap: a tablet to be launched in 2023 and a smartwatch that will go on sale late this year.

Google has been trying to come out  with wearables and devices that can stand up to Apple, but its hardware business remains small. According to IT research firm IDC, its global market share in smartphones is under 1%,

The post Google’s new AR glasses translate language in real time appeared first on FutureIoT.

The March 2022 update of IoT Analytics’ Global IoT Enterprise Spending Dashboard, reveals the IoT market grew slightly slower than the 24% forecasted last year attributing this to factors such as a slower-than-anticipated overall economic recovery, a lack of chipsets, and disrupted supply chains.

North America was the fastest-growing region in 2021 (+24.1%), and process manufacturing was the fastest-growing segment (+25%).

The researcher forecasts connected IoT devices to reach 14.5 billion globally by the end of 2022. IoT Analytics noted the increasing importance of artificial intelligence in IoT projects. It posits that the infusion of AI into legacy applications and advances in AI hardware will boost the Artificial Intelligence of Things (AIoT) – a US$102.2 billion market opportunity by 2026.

Editor's suggested reading: OREM to deploy AIoT at 82 solar farms in Japan

With connectivity a central tenet of IoT, FutureIoT spoke to Sanjiv Verma, vice president of RUCKUS Networks, APAC, Commscope, for his take on where things are headed for the technology in 2022 and beyond.

What are the top IoT trends we can expect to see in 2022?

Sanjiv Verma: IoT will continue to skyrocket, with ongoing strong business investments in IoT. Businesses are looking closely at how they can run their operations better – optimizing shipping, for example – and putting sensors in the right places can help with that effort.

AI and machine learning (ML) use cases combined with augmented reality (AR) will grow rapidly in 2022. Facebook announced a name change and is now orienting the whole company toward the AR-driven metaverse. This AR-driven metaverse will lead to the evolution of commercial use cases for everyday business functions like meetings, sales, marketing, and skills training.

The key purpose of IoT is to collect data. We need AI because as you collect more data you need AI to process that data- you can’t do it manually anymore (think of facial recognition or contact tracing).

Further developments in AI and machine learning will continue to evolve alongside the expanding metaverse, as more complex solutions are needed to make sense of increasing amounts of data derived from emerging applications

When it comes to enabling the IoT and smart things, everything comes back to data. If you think about all the tiny data points involved in something as simple as a door sensor (when is it open, when is it closed, is it locked or unlocked, who unlocked or locked it) and you multiply that by the number of sensor applications (temperature, occupancy, lighting, water usage, etc.), it’s all data that needs to be stored someplace and accessed by an application or user. The infrastructure that makes that work is all in the data centre, where single-mode fibre adoption has accelerated.

Could you share industry-leading use cases and key sectors that are set to benefit from IoT solutions in APAC?

Sanjiv Verma: Key industries where we have seen accelerated adoption of digitized solutions, especially driven by the pandemic, include healthcare, hospitality, and education.

In a physical hospital setting and in remote healthcare services, we are seeing IoT solutions speed up healthcare delivery and build efficiency. For instance, an IoT-based healthcare management system acts as a central platform to manage the registration of patients to assign them wards and beds. In addition, the use of IoT solutions aid hospitals in better allocating resources by monitoring visitors’ movements.

IoT projects: CUHK Medical Centre commits to smart tech in healthcare

When it comes to the hospitality sector, hotels and apartment owners can more easily enhance security and convenience for guests and property managers through remote key card management, energy management and other amenities to improve guest satisfaction and build safer experiences.

Hotels will increasingly adopt a broader range of connected sensors, lights, and devices to provide “smarter” facilities management. The management of such smart facilities could take place through a single integrated network platform, which can enable more precise control of essential protocols like guests’ experiences and staff operations that are also made possible by IoT solutions.

In the education sector, we are seeing smart buildings play an integral role in smart campuses and enhancing operational efficiencies. On- and off-campus networks, lecture theatres, digital classrooms and libraries are modernizing to provide automated services and real-time information by tapping on IoT solutions, allowing students and faculties to be more time- and resource-efficient.

What are some challenges of enterprise IoT adoption and how can we overcome these hurdles?

Sanjiv Verma: While Asia-Pacific continues to lead the world in demand for IoT solutions - the region is expected to account for 48% of global IoT spending by 2023 - many organisations still face a complex, fragmented ecosystem of connectivity standards and siloed devices and services, that often slowed or stalled IoT deployments that are essential to enabling proper integration of emerging technologies. 

For many verticals, siloed IoT deployment is still prevalent. Such a format offers limited opportunities for infrastructure interoperability and requires redundant network infrastructure, additional security apparatus and extensive integration services to work with enterprise partners across the value chain, who might also employ their own disparate IoT systems and networks.

Enterprise networks are becoming increasingly complex by the day, with numerous endpoint devices, new applications and network protocols involved. Successful enterprises adopting IoT will require a single, multi-standard cloud-based architecture that enables more granular control of both IoT and OT networks to improve efficiency.

This approach prevents companies from deploying unnecessary resources for specific devices, and aggregate and backhaul traffic. Instead, the provisioning, management, and securing of networks are simplified through convergence. Immediate and evolving requirements from increasing network density and applications can also be easily supported as well. 

The post What lies ahead for IoT in 2022 appeared first on FutureIoT.

Tracr is the world's only distributed diamond blockchain that starts at the source and provides tamper-proof source assurance at scale, enabling Sightholders to provide an immutable record of a diamond's provenance, and empowering jewellery retailers to have confidence in the origin of the diamonds they purchase.

The platform brings together a range of leading technologies – including blockchain, artificial intelligence, the Internet of Things and advanced security and privacy technologies – to support the identification of a diamond's journey through the value chain.

De Beers has already registered one quarter of its production by value on Tracr in the first three Sights of the year in preparation for this first scale release.

Delivering100% source assurance

With more end clients wanting to know the source of the products they buy, the deep meaning associated with a diamond purchase requires a technological step-change to meet their expectations. The introduction of Tracr at scale delivers immutable information on the source of De Beers' diamonds across the value chain and makes source assurance for 100% of De Beers' production possible.

Bruce Cleaver, CEO, De Beers Group, said: "De Beers discovers diamonds with our partners in Botswana, Canada, Namibia and South Africa and, with our long-term investment in Tracr, we are proud to join with our Sightholders to provide the industry with immutable diamond source assurance at scale.

“Tracr, which will enable the provision of provenance information from source to Sightholder to store on a secure blockchain, will underpin confidence in natural diamonds and represents the first step in a technological transformation that will enhance standards and raise expectations of what we are capable of providing to our end clients."

Advanced data security and privacy

The Tracr platform combines distributed ledger technology with advanced data security and privacy, ensuring that participants control the use of and access to their own data. Each participant on Tracr has their own distributed version of the platform, meaning that their data can only be shared with their permission, and only they choose who can access their information.

The advanced privacy technologies used by Tracr reinforce data security on the platform. The immutable nature of each transaction on the platform ensures that the data cannot be tampered with when the diamond progresses through the value chain.

Moreover, the decentralised nature of the platform ensures its speed and scalability, with the ability to register one million diamonds a week onto the platform. With centralised platforms, dealing with large volumes of data can cause bottlenecks, but the decentralised model used by Tracr avoids such issues and enables rapid scaling.

The scalability, speed and security of Tracr are combined into an intuitive user experience to support ease of use for platform participants.

Lefoko Moagi, Minister of Minerals and Energy, Government of Botswana said: "The introduction of this advanced provenance technology is extremely exciting and we are very pleased as a large diamond producing country, and shareholder in De Beers, to be a part of this development. Confidence in diamond origin is extremely important and we look forward to seeing the roll out of this new programme delivering new benefits to the diamond industry and giving more assurance to consumers."

De Beers' provenance claims have been certified by the Responsible Jewellery Council and trust in the De Beers source of diamonds is also assured by the business's Pipeline Integrity programme which involves annual third-party verification visits of participants by independent auditors.

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AI giant SenseTime has been working hard to develop digital humans that can carry out  various tasks across different milieus in the real world.

“With the dawn of the AI era, digital human is developing into a more advanced and intelligent model which is comparable to human beings. The AI-enabled intelligent service provided by a digital human can significantly increase productivity, facilitating the integration of digital economy and physical economy,” said Tian Feng, dean of SenseTime's Intelligence Industry Research Institute.

Five development stages of digital humans

The AI pioneer recently came out with what is touted to be the first-ever definition of  the five development stages of digital human, analysing its core technologies and future trends.

In a whitepaper entitled “AI Digital Human: New Momentum for Digital Economy Development”, written in collaboration with The China Augmented Reality Core Technology Industry Alliance (CARA), SenseTime described the development stages of digital humans from two perspective: level of automation and similarity to human beings.

At levels 4 and levels 5 of development, SenseTime claims that a digital human attains a level of sophistication to simulate human behaviour.

“AI digital human of L4 can learn from a large number of human conversations, facial expressions, and body languages. It can achieve intelligent human-like interactions by performing natural facial expressions and body movements,” SenseTime said in a statement.

With its advanced deep learning capabilities, a digital human at the upper development levels can rapidly acquire knowledge from various scenarios to become an “expert” of a specific field. The intelligent interactions by AI digital humans of L4 or higher can be applied in general scenarios and various industries, providing momentum for industrial transformation.

AI digital humans to empower industries

Moving forward, SenseTime will continue to leverage AI technologies to unlock the potential of  digital humans in empowering industries to forge a path for its smart journey

The company leveraged proprietary multimodal interaction, deep learning algorithms and full stack AI-Generated Content (AIGC) to create smarter and more professional AI digital humans, enabling human-machine interactive experience.

At the 2020 World Artificial Intelligent Conference, SenseTime’s digital human acted as a docent to guide tours for guests and visitors. Meanwhile, the company’s  digital humans have served as a shopping guide in Guangzhou AEON Mall, as well as the customer service manager in the Bank of Ningbo Shanghai Branch, providing inquiry services for customers.

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The study also showed that indoor air quality (70%) ,cleaning frequency (65%) and virus transmission risks (61%) are key concerns among Singapore residents who were polled.

“This sheds some light on the concern levels of Singaporean workers as many are now heading back to the office. With 64% indicating they’re somewhat or very concerned about contracting Covid-19 at work, office cleanliness and safety are top of mind,” said Stephen Tracy, chief operating officer at consumer research firm Milieu Insight.

Milieu Insight conducted the study in collaboration with SoftBank Robotics and Infogrid, to understand employee sentiments about their office cleanliness since the pandemic

Tracy added: “There’s an enormous opportunity in applying data and robotics to address these concerns. And the study shows that support is high for integrating things like more data and transparency around office cleaning practices, as well as the integration of robotics, including robo-vacuums.’’

Indeed, nearly 75% of those surveyed want to see  greater transparency on cleanliness statistics

“This survey conducted in collaboration with Milieu Insight is extremely insightful for employers and building owners to understand the importance of using data to reassure our Singapore workforce that there are specific benchmarks in place to ensure that their office is safe and clean,” said Kenichi Yoshida, chief business officer, SoftBank Robotics Group. SoftBank Robotics is the company behind the autonomous AI-driven robot called Whiz.

SoftBank Robotics’ Cobots (collaborative robots) are specifically designed with the principles of human-robot interaction and to support an organization’s current staff, not replace them. Deploying autonomous cleaning cobots can help impact the bottom-line for organisations seeking efficient solutions that reduce repetitive or strenuous tasks for the cleaning staff, allowing them to focus on nuanced, uniquely human needs and improving overall cleaning efficacy.

Using cobotics to improve employee experience

Meanwhile, SoftBank Robotics recently partnered with Infogrid to integrate the latter’s AI-powered building management platform into the Whiz cleaning robot.  Infogrid’s multi-sensor technology and analytical dashboard will help companies deliver a better working environment.

Yoshida added: “Cobotics is the collaboration between workers and robots, or other automation tools to improve employee experience. Whiz’s smart AI cleaning with real-time data on indoor air quality using Infogrid sensors and its analytical dashboard can deliver peace of mind to both employers and employees concerned with the risks of transmission of airborne viruses at the office.”

“Our Smart Building Platform when deployed with Whiz provides the reassurance that businesses and their employees need as they return to the office,” said  Ross Sheil, senior vice president for global revenue, Infogrid. “By being able to monitor and report on indoor air quality in real time, businesses can take immediate action to keep their employees safe and also improve productivity and mental wellbeing. Our partnership with SoftBank Robotics allows us to ensure that building managers are able to make the right decisions at the right time based on real data.”

Meanwhile, SoftBank Robotics has introduced GERMii UV-C for Whiz, a disinfection and vacuum cleaning 2-in-1 function for Whiz that is able to eliminate surface pathogens in Singapore. Its features include obstacle detection, fall prevention (LIDAR sensor, 3D camera), impact detection (sensor-installed bumper), anomaly detection (Cliff sensors, wheel contact sensors,  and emergency brake function).  Whiz has its own proprietary BrainOS Navigation Software that helps determine the best cleaning route based on its real-time surrounding environment.

By deploying the newest Whiz products with Infogrid’s smart technology, organisations can monitor their office indoor air quality, occupancy levels, building usage, humidity levels and other AI-powered insights to take action to improve the workplace environment.

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Lee Kum Kee (Hong Kong) Foods Limited has earmarked HK$46 million to build its new oyster sauce smart production line, which is scheduled to start operation in the first quarter of 2024.

The new fully automated production line will produce 20,000 bottles of oyster sauce per hour, doubling the production capacity of the company's oyster sauce manufacturing plant at Tai Po InnoPark. Artificial intelligence (AI) will be deployed in the new line to monitor the production process and to gather real-time data to enhance product traceability and overall operational efficiency.

The  company last week received HK$15 million under the RFS to partially fund the project.

“We are glad to receive funding support for our new Oyster Sauce Smart Production Line project under the RFS. We are committed to implementing digital upgrade and smart factory transformation, in order to enhance our production efficiency and satisfy consumer needs,” said Kathy Lam, CEO, Lee Kum Kee International Holdings.

Launched in July 2020 under the auspices of the city’s Innovation and Technology Commission (ITC), the RFS provides subsidy to manufacturers in Hong Kong who are upgrading their factories into smart production lines. The scheme offers a matching financial support amounting to one-third of the approved project cost, capped at a maximum ceiling of HK$15 million per project. Projects under the scheme are expected to be completed within 24 months.

Upgrading production processes

Lee Kum Kee (Hong Kong) Foods is the latest local food manufacturer to avail of the RFS initiative.

In January of this year,  the ITC approved a HK$14.9 million RFS project to help Leun Tai Hong Kong Fresh Liquid Eggs Limited to establish its smart production line  for its fresh liquid egg products. The new smart facility will be similarly located at the Tai Po InnoPark.

The smart production line project is expected to increase the daily production of fresh liquid eggs by two to three times, while lowering the production cost by 20% to 30%.

Established in 1957, Luen Tai Hong is  a key local supplier of fresh liquid eggs (with a market share of nearly 30%) for many restaurants and food manufacturers in Hong Kong. It established the first pasteurised liquid eggs factory in the city in 2013.

Leun Tai Hong last month has enlisted the help of the Hong Kong Productivity Council (HKPC) to customise the design of its new smart production line.

“At present, 30 tons of fresh egg liquid are produced every day, mainly relying on manual supervision and productivity is limited. With intelligent production, the production capacity can increase by 2 to 3 times, with 60 to 70 tons of fresh egg liquid to be produced per day,” said Young Kam-yim, managing director of Luen Tai Hong.

He added:  “At the same time, manpower, production time and human error will be reduced, achieving overall cost saving of up to 30%. Staff can also be deployed to handle high-tech work, reducing costs and raising efficiency. Intelligent production will also diversify our business. In addition to expanding from B2B to B2C retail business, high production capacity will also help the brand enter the huge and potential Greater Bay Area (GBA) market with a population of more than 86 million, making Hong Kong’s food manufacturing industry shine on the global stage.”

By applying HKPCs one-stop integrated technical support, Leun Tai Hong will be able to optimise its production process through the adoption of  sensors, Internet of Things and machine vision. Furthermore, the production process will be monitored with real-time data to ensure product safety and traceability, while increasing productivity and stability.

“The food industry is one of the top four sectors boosting the largest value growth among local manufacturing. We determined to lead the food industry gradually move towards advanced manufacturing so as to strengthen the ‘Made in Hong Kong’ brand and let it shine in the international market,” said Edmond Lai, chief digital officer, HKPC.

He added: “With the advanced manufacturing technologies of i4.0, HKPC helps the manufacturing industry to streamline the traditional production process. Through data-based real-time monitoring of product quality, operators can also flexibly deploy according to the data of each position, and establish predictive maintenance to avoid losses incurred by unexpected downtime, making enterprise management more handy.”

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The study is hoped to pave the way for the company’s overseas expansion, banking on its cloud-based digital treatment of the medical condition that afflicts three of 100 children in the population.

“The study, which includes two sites in Shanghai, is led by Dr. Rui Liu from the Eye & ENT Hospital of Fudan University, one of the mainland's top hospitals, and will involve 20 patients in the CureSight treatment group and 20 in the patching control group,” said Ran Yam, CEO, NovaSight.

He added: “This marks another milestone for NovaSight and the beginning of our journey to secure the mainland National Medical Products Administration clearance in preparation for our future commercial activities in the mainland.”

Yam said the results of the Shanghai study would be released by the end of 2022.

A similar clinical trial was conducted last year in six medical centres in Israel, including Sheba Medical Center, which was ranked one of the top 10 best hospitals in the world.

The study, which randomly assigned 103 patients from the ages of 4 to 9, compared the improvement in visual outcomes achieved by CureSight digital treatment versus eye patching, considered the current gold-standard-of-care treatment.

In addition to achieving the non-inferiority primary endpoint, NovaSight noted that the topline analyses from the pivotal study demonstrated that best corrected visual acuity (BCVA) improvement at week 16 was larger in the treatment group compared to the patching control group.

The study also evaluated adherence and patient satisfaction, noting a mean adherence of 93% among clinical subjects in using the CureSight eye tracking system, with 93% of parents saying that they are likely or very likely to choose the CureSight digital treatment over patching.

“Eye patching is effective when patients are compliant, however, patching is often associated with insufficient adherence due to the discomfort it brings to the patient and the social stigma that many children experience when wearing a patch," Yam said.

Cloud-based digital device

The CureSight system consists of a digital screen device and a red-blue treatment glasses that trains brain to use both eyes simultaneously, while the user watches any streamed video content through red-blue treatment glasses.

Optical image sensors track and record momentary gaze position, sampling 90 times a second to create objective and comprehensive eye movement patterns.

Using sophisticated AI algorithms and eye-tracking technology, CureSight blurs the centre of vision of the image that is shown to the strong eye using real-time image processing.

This encourages the brain to complete the image fine details from the amblyopic eye image and trains the two eyes to work as a team. The device is designed to be used at home, and it shares treatment reports with caregivers via a cloud portal.

By tracking the patient eye movement, the AI algorithms receive the data which allows for unique insights into human behaviour and facilitates natural user interfaces.

All collected data is uploaded to the cloud and is processed in real-time for immediate analysis of the results to help in the assessment and decision of treatment. The eye care provider receives a comprehensive patient vision summary. Progress reports and real-time monitoring of the child's treatment are easily accessible.

Using digital technology to diagnose vision problems

Meanwhile, NovaSight plans to introduce its EyeSwiftPRO system, another device which helps diagnose conditions such as myopia by tracking patients’ eye movements as they watch animated videos on a screen.

“Traditional vision exams such as the eye chart, undergone by hundreds of millions of patients worldwide every year, are manual, subjective, time-consuming, limited and often inaccurate – especially for toddlers who can’t always understand the examiner’s instructions or communicate what they’re seeing,” said Yam. “Therefore, they are not sufficiently effective to detect many visual impairments, including amblyopia (lazy eye). As a result, these conditions often go undetected or are misdiagnosed.

Suitable for both children and adults,  EyeSwiftPRO is designed to replace the traditional eye chart and other manual exams and deliver any trained eye-care provider various fields of diagnostic tools by using dedicated protocols such as myopia, amblyopia, binocular vision and more.

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"Global manufacturing took a hit during the beginning of the pandemic. Businesses in Southeast Asia started facing supply chain disruptions, lower productivity, and rising manufacturing costs," said Marcelo Tarkieltaub, regional director for Southeast Asia, Rockwell Automation. "As we recover from the pandemic, businesses must address these key issues, improve their manufacturing capabilities, and supply chain processes, and build resilience to withstand unexpected disruptions. Digital technologies, smart manufacturing, human-machine interaction, and advanced analytics are helping manufacturers optimize processes and strengthen their position as 'factories of the world.'"

He added: "Southeast Asia is one of the fastest growing sub-regions for us. We are very pleased to partner with CAD-IT who is well-versed in the region. By combining our technologies and expertise with their strong regional network and execution competency, we can make smart manufacturing and digital transformation solutions more accessible to businesses in Southeast Asia.”

The partnership will see CAD-IT offer Rockwell Automation's smart manufacturing and automation solutions: newly acquired Plex Systems, a cloud-native smart manufacturing platform; and Fiix, a cloud-based, artificial intelligence (AI)-powered computerized maintenance management system. Both Plex and Fiix cater to the food and beverage, household and personal care, and automotive industries across Asia Pacific.

CAD-IT delivers end-to-end Industry 4.0 solutions encompassing additive manufacturing, augmented reality (AR), industrial internet of things (IIoT), engineering simulation and more. With manufacturing expertise gained through its production facilities in China, the company has delivered numerous multi-factory digital transformation projects in various verticals across Asia Pacific.

CAD-IT has a wide network in Southeast Asia, with presence in Singapore, Malaysia, Thailand, Indonesia, Philippines, and Vietnam, serving more than 1,000 customers. Beyond the sub-region, it has offices in China, South Korea, and Australia to serve Asia Pacific customers.

Rising demand for automation and Industry 4.0 solutions

CAD-IT joins the growing PartnerNetwork of Rockwell Automation channel partners to support the increasing demand for industrial automation and Industry 4.0 solutions in Southeast Asia, with plans to expand the coverage across the rest of Asia Pacific in the near future.

The region's industrial automation and process control market is expected to be worth US$4.97 billion by 2025. This demand is driven by high technical awareness around the usage of robotics and the manufacturing sector's robust production capabilities.

Additionally, the demand for Industry 4.0 solutions is on the rise. According to Mordor Intelligence, Asia's Industry 4.0 market is expected to reach US$71.59 billion by 2026.

"Partnering with Rockwell Automation gives us the opportunity to expand and build our product and services suite of Industry 4.0 solutions. Besides enhanced manufacturing and digital transformation, businesses in the region will benefit from our local market presence with implementation, support, and maintenance from our on-ground team of experts across the region," said Terence Chan, CEO of CAD-IT.

Rockwell Automation has been in Asia Pacific for over 40 years and continues to invest in its vision of expanding human possibility and digital transformation for its customers across the region. With over 5,800 dedicated employees in the region and a robust ecosystem of partners collaborating towards delivering value for our customers, Rockwell Automation continues to transform the industry, unlocking potential and productivity through automated and connected innovation.

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The partnership between the two companies aims to streamline work processes, allowing efficient mobilisation of on-site manpower resources. It will also improve customer service experiences with more targeted and enhanced cleaning services

“We have always been committed to providing solutions such as Whiz, an AI-enabled vacuum cleaning robot to facility operators. With the use of disruptive technologies such as predictive data on maintenance monitoring, it will provide building owners with building intelligence that is needed to digitally transform this industry operating landscape,” said Kenichi Yoshida, chief business officer, SoftBank Robotics Group Corp

“Teaming up with UnaBiz, we are confident that this partnership will not just add value to our customers but eventually make a difference in the entire sector,” Yoshida added.

SoftBank Robotics believes that facilities management operators are faced with handling many different building management tools and different brands of robots. On the backend, there are several dashboards – most of which don’t have a central control system for easy management.

It’s alliance with UnaBiz is part of the company’s  overall roadmap to implement an IoT system onto a unified smart facility management platform – where IoT devices trigger alerts and automate AI-enabled autonomous vacuum cleaning robots like Whiz to tasks in addition to providing AI predictive data analytics.

Massive IoT provider has deployed UnaBiz has deployed last year one of the largest Integrated Facilities Management projects in Singapore, with over 3,000 sensors at Temasek Polytechnic. On top of smart facilities management, UnaBiz also focuses on smart cities applications like smart metering, asset management, and asset tracking. The scaleup has deployed more than 1.3 million sensors globally, of which, over 1 million were smart gas meter sensors for Nicigas, Japan’s major LPG company.

Henri Bong, co-CEO and co-founder of UnaBiz said : “Facility managers are embracing technology to increase the productivity of the workforce, improve customer satisfaction, and reduce carbon emissions. Both IoT and robotics have a lot of complementary purposes and the synergy of both can unlock new value for future disruptions and growth. We are confident that the right mix of SBRG robotics and our IoT devices could greatly benefit the whole industry.”

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Newly launched Neuron Digital Group is setting its sight to making buildings smarter and leveraging the power of data and technology to decarbonise building assets and facilitate digital property management.

Headquartered in Hong Kong, Neuron is already serving several prominent clients in the local market. It also plans to expand from its research and development base in Hong Kong and establish operating hubs in mainland China and other key leading smart cities in the Asia Pacific.

“Neuron is a powerful demonstration of our commitment to a sustainable future. It offers a systematic approach to decarbonising the built environment by unlocking the potential of data and technology. With this joint venture, we aim to scale up the accessibility and usability of Neuron via cloud platforms, facilitating the industry to accelerate the journey to net zero,” said Dr. Andy Lee, co-chairman of Neuron and East Asia chief operating officer of Arup.

Neuron is a joint venture between global built environment consultant Arup and China’s Venturous Group. With the domain knowledge of these two companies, Neuron is best position to develop the ideal platform for smart and sustainable buildings.

Benson Tam, co-chairman of Neuron and founder & chairman of Venturous Group, said: “Neuron is proudly a ‘child of Hong Kong’. We are so excited to launch it here. Neuron is an infrastructure key to Smart Cities, which is at the core of our firm’s mission. At Venturous Group we not only invest, but also build and operate Citytech. Neuron is a perfect example of what we can achieve together with best-in-class, long-term strategic partners such as Arup.”

Neuron embraces data technology to serve modern-day buildings, including energy management, tenant wellness and satisfaction, automation and indoor air quality. It will also help reduce maintenance costs and equipment downtime, and optimise asset management.

The Neuron solutions have been implemented in different projects in Asia, resulting in a significant improvement in building energy and operation efficiency. With Venturous Group’s capital, strategy and technology capabilities, Neuron will further develop into a cloud-based integrated technology platform with Digital Twin, AI and big data capabilities that will meet the needs of building owners, operators and users.

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The new in-store experience boosted with new tailored services for greater personalisation is in line with the fashion company’s renewed focus on omnichannel engagement, leveraging the hybrid customer experience model.

The company will transform a number of stores in Australia, Indonesia, Malaysia, Singapore and Thailand into NextGen Indigo stores fitted with new store designs, digital features and operating models – all aimed at boosting Levi Straus’ omni-channel capabilities for deeper connection with consumers.

"We are committed to the future success of our business at every level and are reimagining what we do and how we win in today's marketplace. At the same time, we are embracing the technologies of tomorrow to power innovation and better serve our customers and deliver greater value to stakeholders. We will do this by placing people at the heart of our business and through responsible practices because being a force for positive change is integral to being the world's best apparel brand," said Nuholt Huisamen, managing director and senior vice president, Levi Straus.

Coupling heritage with digitisation

While drawing on its 169-year heritage to drive key category growth, Levi Strauss is redoubling its digital transformation efforts.

The company will leverage digital, data and AI to stay ahead of trends, drive efficiency and innovation in the product creation process, deliver omnichannel offerings, claim its space in the direct-to-consumer (DTC) sphere, and ultimately enhance the consumer experience.

As part of its DTC strategy, the company also provided learning opportunities to existing staff to upskill themselves through training and development programs such as a Machine Learning Bootcamp to equip employees with the tools they need to thrive in a changing and increasingly digitalised economy.

ESG initiatives

On the Environmental, Social and Governance (ESG) front, Levi Strauss targets measurable metrics and remains committed to responsible and sustainable practices outlined in its 2020 Sustainability Report.

The company is on track to achieving its 2025 Water and Climate Action Strategy targets. Initiatives include Water<Less finishing techniques that have enabled billions of liters of water to be saved; reducing emissions across the supply chain; driving innovation in sustainable materials and designs through Wellthread; and advocating ethical consumerism through the Levi's Buy Better, Wear Longer campaign. These initiatives embody the company's move to develop and implement circular products and practices

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"Streamlining our processes with this system has allowed us to work more efficiently. The automated security alerts and the HD Video help us to respond quickly and work with peace of mind,” said Khalid Al Mutawa, director of operations at Abu Dhabi Entertainment Company.

Abu Dhabi Entertainment company manages and operates Zayed Sport City, whose facilities include

a stadium, ice rink, bowling centre and tennis centre among others. Surrounding these facilities are an additional five outdoor festival spaces of varying size, divided among natural grass pitches, a 600sqm  indoor event space, plazas and tarmac areas.

Keeping an eye on safety

With more than 1.7 million people visiting Zayed Sports City each year, ensuring safety means keeping track of all areas of the complex during sports events, and to respond quickly if anything goes wrong.

Two major challenges confront the complex management when the decision was made to install  a site-wide security systems.

As hundreds of cameras are needed to provide full coverage of the complex, it would be quite difficult for the security team to manually process the vast amount of video streams that would be generated.

Furthermore, many facilities in the complex have high ceilings. This means that high-resolution security cameras are needed to provide clear imaging at significant distances, with cameras often mounted high up on pillars, posts, or ceilings.

To address these challenges, Zayed Sport City needed a security and safety system that could protect all areas of the site – without the excessive workloads associated with manual approaches.

Camera-based system with AI capabilities

Abu Dhabi Entertainment has tapped Hikvision to provide the camera-based security system and the control room equipment needed to guard Zayed Sport City around the clock.

More than 670 Hikvision cameras with different functions and types were deployed in two major project phases. These are being used to protect all of the sports venues and facilities inside the Zayed Sport City, as well as spectator seating areas and parking areas.

Hikvision delivered high-definition imaging with its with 2- and 4-megapixel resolution across the Hikvision bullet and PTZ camera fleet.

Some of the cameras have on-board AI capabilities to automate key security tasks. For example, cameras installed at the stadium parking areas have built-in license plate recognition capability, which increases the efficiency of parking operations.

Indeed , AI capabilities also allow the security team to search back through video footage much more quickly and easily when investigating accidents and incidents.

All Hikvision cameras have been integrated seamlessly into the Zayed Sport City Video Management System (VMS). This minimised deployment cost and risk and is ensuring that all elements of the solution work in harmony to protect visitors to the stadium.

"It was critical for us that cameras and other equipment deployed in phase 1 and phase 2 would integrate easily with our currently used VMS, with no compatibility issues," said Mutawa. "Hikvision offered a fast and easy solution, and full coverage of the site was installed on time."

A cost-effective system

According to Mutawa, the new Hikvision solution at the sports complex allows many routine security tasks to be handled automatically - reducing the risk of missed incidents, speeding up responses, and reducing staff workloads and costs.

With the ability to search through video footage quickly and easily to investigate accidents and incidents, the security team is achieving major time savings compared with reviewing video manually.

Moreover, the security team saves a substantial amount of time now that they do not have to search through video footage manually - making it easy for them to investigate accidents and other incidents.

"The Hikvision system's AI features are very valuable in investigating incidents and it reduces the time required by our staff significantly," said Mutawa. "This frees our security team up for our core activity: keeping visitors safe and ensuring that the complex is secure at all times."

The fact that Hikvision cameras use onboard AI capabilities has made it cost-effective for Zayed Sport City to deploy the latest security technologies quickly, across the entire site.

Additionally, new AI capabilities – such as the ability to locate and help unaccompanied minors or to count people to prevent crowding – can be added cost-effectively in the future, with no need to replace existing control room equipment or software.

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Shaping the future of manufacturing, WEF “Lighthouse” facilities implement Fourth Industrial Revolution technologies, such as the Internet of Things, big data, artificial intelligence and robots, into manufacturing and supply chain operations to deliver a wide range of benefits, from increased production efficiency to enhanced environmental sustainability.

“As the world grapples with many challenges, it is remarkable to see how Lighthouses are yielding sustainability benefits while achieving business goals, which we call eco-efficiency,” said Francisco Betti, head of Shaping the Future of Advanced Manufacturing and Value Chains, World Economic Forum. “We need them to continue illuminating the way forward for the global manufacturing community by shaping a responsible future of manufacturing that works for people, society and the environment.”

Futuristic manufacturing

Over the past five years, LG has transformed its factory complex in Changwon, South Korea into LG Smart Park, a futuristic hub of home appliance manufacturing.

The key elements of the transformation are a digitally-enabled end-to-end three-dimensional logistics system, an advanced analytics system based on edge computing technology and machine learning that predicts defects, and state-of-the-art facilities that can mass-produce multiple models to respond flexibly to customer requirements.

The newly implemented “digital twin” technology enables the operation system to analyse production processes in virtual reality. It can predict if any issues will occur within the next 10 minutes and provide exact parts and materials for the assembling of each appliance with an accurate, up-to-the-minute status of the facility’s logistics operations.

Sensors utilising deep learning technology are installed throughout the factory to monitor each phase of production in real-time, helping factory workers to pre-emptively identify and resolve any possible issues. As a result, the cost of defective product returns dropped by 70%  from 2020 to 2021 while overall quality competitiveness and production efficiency were both significantly strengthened.

Floors one, two and three at LG Smart Park employ an overhead conveyor system that quickly transports boxes containing refrigerator parts to the required production lines. Attached to each line is an intelligent warehouse that monitors inventory in real-time, enabling automated materials management, including the request of additional parts and supplies.

On the ground, automated guided vehicles (AGVs) leveraging stable 5G network connectivity transport parts and materials to wherever they are needed on site. Through its three-dimensional logistics automation system, the company can minimize the amount of warehouse space needed by 30% compared to conventional logistics systems, and shorten the time required for hourly materials transportation by 25%.

LG Smart Park has also adopted the use of robots featuring an AI engine and camera to make the home appliance production process faster and safer. The robots undertake dangerous and complicated tasks, such as welding and the lifting of heavy parts and equipment.

Taking it global

LG plans to apply the innovative, smart production technologies pioneered at LG Smart Park to a total of 26 LG production facilities in 13 countries, accelerating the digital transformation of its global manufacturing network by 2025.

“LG Smart Park illustrates our strong commitment to adopting the revolutionary technologies as the leader of the global premium home appliance market,” said Lyu Jae-cheol, president of the LG Electronics Home Appliance & Air Solution Company. “We are presenting a blueprint for the future of manufacturing, one that delivers better outcomes across environmental, economic and employment aspects.”

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The research firm defines a smart building as a building that uses connectivity to enable economical use of resources, while creating a safe and comfortable environment for the occupants.

According to its new report entitled “Smart Buildings: Key Opportunities, Competitor Leaderboard & Market Forecasts 2022-2026”, significant efficiency gains can be made by enabling buildings to monitor and automate common functions.  Automating these functions also improve the environment for workers and residents.

The report recommends that vendors focus on building analytics platforms for the most value to be driven from deployments.

Commercial premises drive smart building spend

The research found that non-residential smart buildings will account for 90% of smart building spend globally in 2026; at a similar level to 2022.

This dominance is due to the larger economies of scale in commercial premises driving this spend, as well as the commercial focus of most smart building technologies.

“Smart building platform vendors will understandably focus on non-residential use cases, as these provide a stronger return on investment, but they should not neglect the importance of residential deployments, as environmental concerns intensify,” said research co-author Dawnetta Grant.

Smart building sensors shipment to accelerate quickly

The research found that the global shipments of sensors used in smart buildings will exceed 1 billion annually in 2026 from 360 million in 2022. This represents a growth of 204%.

Sensors, when combined with intelligent management platforms, will allow smart buildings to adapt to conditions; matching elements such as lighting, heating and ventilation to live requirements.

The report recommends that smart building vendors partner with AI vendors to maximise the benefits of automation, such as reduced energy costs and improved working environments.

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These pilots signal the startup’s international expansion, which comes on the heels of the recent US$1.25 million seed funding secured from investors led by Silicon Solution Partners (SSP) and SEEDS Capital, the investment arm of Enterprise Singapore.

"We hope to conduct more pilot trials with companies and governments, to showcase how remoteEye results in benefits including cost savings, improved safety/hygiene levels, improved performance and reduced reliance on manpower,” said Deepak Pitta, founder and CEO, SpaceAge Labs

In the next six to 12 months, Pitta said the company  plans to double its current headcount of 12 employees as it opens international offices in Australia and the US.

Pushing for more pilots in Singapore

At the same time, SpaceAge Labs will continue piloting monitoring projects in its home country – specifically around water consumption patterns and leak detection in facilities,  air quality in outdoor spaces, and water quality in swimming pools to name a few.

Last year, Public Utilities Board (PUB) of Singapore collaborated with the local startup to trial an IoT-based monitoring solution aimed at preventing sewer overflows in the city state’s wastewater network.

Some 40 IoT devices have been installed in sewer manholes across Little India, Geylang and Serangoon Gardens, which were prone to overflows. These areas have a high restaurant concentration and tend to have faster build-up of fat, oil and grease in the sewer network which will eventually lead to a blockage if not cleared.

The battery-operated wireless IoT devices are installed inside the harsh, confined conditions within a sewer manhole, providing PUB with real-time alerts when waste water levels within the sewer system rises too high. When alerts are triggered PUB officers would quickly check for blockages downstream, with SpaceAge Labs informing them the areas that are likely to be clogged.

“Over a twelve-month period from January 2021 to December 2021, we successfully alerted PUB to 10 events within the wastewater network. PUB promptly cleared these blockages before any overflow events happened,” said SpaceAge Labs in a statement.

This has significantly improved efficiency of operations, and in preventing pollution to ensure safety and regulatory compliance.

Today, More than 750+ rEye devices deployed so far on site to monitor 1000+ remote assets for different applications.​

IoT devices trialled in greenery management

The company also conducted a pilot with another government agency in Singapore, deploying IoT devices to enable the National Parks Board (NParks) to track the completion and quality of the grass-cutting operations.

NParks manages some 400 parks, 3,347 hectares of nature reserves, the Singapore Botanic Gardens, Pulau Ubin and the Sisters' Islands Marine Park  With over 13,000 hectare of green spaces under its jurisdiction, it is a challenge to physically monitor each location regularly.

The grass height sensor is currently deployed as part of the pilot of park and greenery management using digital tools in the Bishan-Ang Mo Kio precinct. This project supports NParks’ landscape sector transformation plan that aims to elevate and grow the local landscape sector through digitalisation, mechanisation and “professionalisation”.

The IoT devices are worn by grass-cutters using push lawn mowers or handheld grass trimmers. They can also be installed on equipment such as sit-on mowers. The sensors transmit data on the height of grass (post-cut) as well as high precision GPS location data to the cloud. The data are available via web dashboards and a mobile app, where contractors and NParks staff can easily verify the completion and quality of the grass-cutting operation.

“It is important that we take steps to make operations more precise and think of ways to overcome physical and manpower limitations through the adoption of technology. Leveraging on SpaceAge Lab's smart technology, we have been able to conduct grass height inspections more effectively with less manpower.," said Ryan Lee, group director, National Parks Board.

Meanwhile, the IoT-based monitoring system also helps to expedite payment to the contractors as NParks can quickly confirm completed of their work. These operational data and insights also enable the contractors to improve their efficiencies, through better deployment of resources, resulting in lower labour and fuel costs.

Digitising distributed assets maintenance

Established in 2016, SpaceAge Labs started as a consulting company, designing end-to-end IoT solutions for its customers, but pivoted in 2017 to become a product company. In the same year, it became an NUS Enterprise incubatee, based within NUS Enterprise's deep-tech incubation facility in Singapore Science Park I.

The company has found its niche in transforming operations and maintenance of remote and distributed assets by collecting asset data using low power, long-range wireless IoT devices, together with advanced AI software to generate valuable insights from this data.

SpaceAge Labs’ solution aims to deliver the following benefits: asset's uptime (due to data-driven predictive maintenance); reduces cost (less manpower required) and provides peace of mind (operators gain real-time asset visibility).

Its flagship product called remoteEye is sensor-agnostic IoT/AI platform that enables connected operations and maintenance, consisting of three parts:

• rEye IoT Nodes – These are low-powered, wireless devices that read and transmit data from industrial sensors located at the assets.
• Wireless networks – The sensor data is transmitted via low power wide area wireless networks to the cloud. The networks are at low cost (from S$1 per month per device), able to transmit over long distances (several kilometres) and consume low power (up to five years of battery life).
• rEye Data Cloud – Enterprise-grade IoT/AI software that stores, analyses, and visualises this sensor data. This software is secure, easy to use and able to scale easily from managing one asset to thousands of assets. Proprietary AI software and geospatial data analysis provides useful insights and predictions that can be accessed via web or mobile.

SpaceAge Labs is initially targeting three sectors: Water/Wastewater; Urban Greenery/Landscaping; and Facilities management.

Currently, the company has IoT deployments with more than 30 customers, including two key Smart Nation pilot projects in Singapore with PUB and NParks.

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“Deploying solar power at pace means making the most of projects once they are up and running. It’s not just about the cost of capital and your project execution. Lightsource bp has an exceptional reputation on both fronts and once all that hard work is done, we don’t want to waste a single photon,” said Nick Boyle, group CEO of Lightsource bp.

“The partnership with Envision Digital gives us an anatomical level of insight on our assets to optimise them remotely and drive improvements,” he added.

Lightsource bp is targeting the development of 25GW of solar power projects globally by 2025 delivering renewable power at scale, and with the urgency the climate crisis requires. Through the partnership and the advanced analytics from Envision Digital’s AIoT platform, Lightsource bp will be able to gain data-driven insights to enable automation, efficiency, value and ultimately, substantial volumes of additional low-carbon power.

“We see a lot of synergies with Lightsource bp and our teams are rapidly deploying and scaling technology to power the energy transition together,” said Michael Ding, global executive director of Envision.

Envision Digital’s proprietary AIoT operating system called EnOS, currently supports more than 360GW of clean energy assets globally. As the partnership develops, and as global governments and corporations quicken net zero discussions, both companies will explore additional opportunities to drive value across Lightsource bp’s expanding portfolio of solar power projects globally.

Meanwhile, Lightsource bp is a 50:50 joint venture with global energy major bp. By leveraging this partnership with Envision Digital, as well as more than a decade of solar experience, the company expects to be able to deliver greater value at scale and enact a real change on the global energy landscape.

The 247MW Vendimia project in Spain started generating low-cost power in June 2021. The site created 600 jobs during construction and provides a snapshot of the benefits solar can provide to the economy and the climate.

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According to a recent Frost & Sullivan analysis, both AI and IoT are expected to play a bigger role as the industry recovers from COVID-19. From a revenue perspective, the total oil & gas automation market is expected to reach US$24.63 billion by 2025, up from US$17.17 billion in 2020 and growing at a compound annual growth rate of 7.5%.

"Industry 4.0 has been transforming the oil and gas value chain by enhancing connectivity, simplifying operation maintenance, and prioritising safety. The digitalisation of drilling processes in the upstream sector is a high-growth area and can significantly boost production," said Agustina DeSarriera, research analyst, for energy & environment at Frost & Sullivan.

She added: "Operational technologies (OT), such as supervisory control and data acquisition (SCADA) systems, distributed control systems (DCSs), and programmable logic controllers (PLCs), are already in place. However, to optimise automation, companies will soon have to include artificial intelligence, Internet of Things and robotics technologies in their operations."

As the industry feels the pressure to become more sustainable and less labour-intensive, there will be greater growth opportunities for technology providers of:

• AI: Vendors need to highlight the use of AI to automate drilling operations and their ability to eventually decrease the number of wells needed for oil & gas operations. AI can also help avoid incidents and improve environmental performance by predicting leakages and identifying them in real-time.
• Robotics: Vendors can help clients overcome their technology shyness by assigning robots to departments where they can demonstrate maximum value.
• IoT: By showcasing the technology's adaptability and ability to complement other technologies such as AI and OT, IoT providers will find it easier to get buy-in from clients. They can also partner with technology companies that provide OT solutions such as sensors and transmitters and help them transform into smarter tools.

DeSarriera said, "Environmental regulations and agreements are compelling the industry to become more sustainable, and participants are recognising that one of the easiest ways to achieve higher process efficiencies is automation. With the pandemic causing a resource shortage, it is imperative that oil & gas companies tap automation to reduce human exposure and perform rote tasks that were previously performed by humans."

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“Vendors are already building ways for users to replicate their lives in digital worlds,” said Marty Resnick, research vice president at Gartner. “From attending virtual classrooms to buying digital land and constructing virtual homes, these activities are currently being conducted in separate environments. Eventually, they will take place in a single environment – the metaverse – with multiple destinations across technologies and experiences.”

Gartner defines a metaverse as a collective virtual shared space, created by the convergence of virtually enhanced physical and digital reality. It is persistent, providing enhanced immersive experiences, as well as device independent and accessible through any type of device, from tablets to head-mounted displays.

Because no single vendor will own the metaverse, Gartner expects it to have a virtual economy enabled by digital currencies and nonfungible tokens (NFTs).

Massive impact on consumer and business engagements

The metaverse will impact every business that consumers interact with every day. It will also impact how work gets done. Enterprises will provide better engagement, collaboration and connection to their employees through immersive workspaces in virtual offices.

Businesses will not need to create their own infrastructure to do so because the metaverse will provide the framework. In addition, virtual events that have gained popularity over the last 18 months will offer more collaborative and immersive networking opportunities and workshops.

“Enterprises will have the ability to expand and enhance their business models in unprecedented ways by moving from a digital business to a metaverse business,” said Resnick. “By 2026, 30% of the organisations in the world will have products and services ready for metaverse.”

Invest with caution

The adoption of metaverse technologies is nascent and fragmented, and Gartner cautions organisations about investing heavily in a specific metaverse.

“It is still too early to know which investments will be viable in the long term, but product managers should take the time to learn, explore and prepare for a metaverse in order to position themselves competitively,” said Resnick.

Indeed, a latest Gartner Marketing Survey warns companies to temper short-term expectations, as more than one-third of American consumers (35%) have never heard of the metaverse.

The survey finds that 58% of respondents have either heard of the metaverse but do not know what it means, or think they understand the metaverse but would struggle to explain it to someone else. Only 6% of people identify as being comfortable enough in their understanding of the metaverse to explain it to others.

Kyle Rees, senior director analyst in the Gartner Marketing practice, noted that the survey result is a helpful signal to temper short term expectations of the metaverse, and its potential impact on consumer’s daily life

Metaverse opens new doors of opportunities

Rees pointed out that it will be exciting to see how meta-aware companies begin to make sense of next-generation technologies to bring new products, services and experiences to the world around us.

“Technologies that are intertwined with the metaverse, such as projects on the blockchain or digital currencies, need to be highlighted as disruptive to the status quo thinking. Even properly communicating business use cases around metaverse-adjacent concepts, such as AI and augmented reality, will go a long way in demystifying what is still largely an unknown technology to the everyday consumer,” Rees added.

Of those who at least know about the metaverse, 60% have no opinion on it, and only 18% are actually excited about it. Meanwhile, 21% say they are concerned about the impacts the metaverse might have.

“Companies with interests in the metaverse have a lot of work to change consumer’s attitudes,” said Rees. “Contemplating the metaverse is a luxury that most people don’t have time for currently. Getting people on board to see past the individual pieces of AI or head-mounted displays is paramount to them to truly embracing the multiple technologies that make up a complete metaverse. There are complex, innovative new opportunities and business models that the average consumer needs to be able to grasp easily, or companies risk losing their interest."

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The new facility at the port is touted to be the world’s first fully-automated cold chain port warehouse, providing low-temperature warehousing and other services in an area of over 30,000 square meters.

As the gateway to Beijing, Tianjin port is one of the busiest hub for China’s massive import and export businesses and it is the first stop in China’s cold chain logistics network.

“Geek+ will continue to work together with Engero to implement its innovative technology to extend this new industry benchmark to further cold chain logistics providers,” said Geek+ in a press statement.  “Our highly flexible autonomous mobile robots and advanced algorithm strategies are the twin engines driving the improvement and modernization of cold chain warehouse.”

Engero specialises in smart logistics and integrated solutions that help companies to improve efficiency, reduce costs, and improve management through automation and smart technologies. Engero conducts business throughout China.

Manual operations is not suited to cold chain logistics

According to Geek+, the extreme conditions in cold chain logistics is not well-suited for manual operations. Geek+’s AMR (autonomous mobile robots), on the other hand, can stably operate at low temperatures 24 hours a day, seven days a week, reducing the need for people to endure extreme, unpleasant working conditions.

“A further benefit of robotic automation of cold chain logistics is a reduction in risks to workers’ health and goods safety. Upon arrival in the port, goods requiring cold chain storage are carried by Geek+’s MP1000R moving robots to the depot area for customs inspection and disinfection, before entering the storage area for further processing and distribution,” the company said.

Within the warehouse, Geek+ robots interact and collaborate with different intelligent devices to handle the whole logistics process. Indeed, the robots autonomously handle all aspects of warehouse operations from pallet scheduling to packing. Furthermore, Geek+ MP1000Rs distribute goods automatically to the conveyor line for inspection.

AI algorithms optimise the robots’ routes with intelligent queuing strategies to avoid traffic jams in narrow passages and drive efficient cluster scheduling, according to Geek+.

“360° laser obstacle avoidance and omni-directional sensing allows the MP1000Rs to navigate in narrow aisles, maximising storage space density and further ensuring worker safety. The robot’s self-rotating jack allows for great flexibility with minimal space occupied when moving pallets, meaning that warehouses can be upgraded with a minimum of fuss,” the company said.

Artificial intelligence is seamlessly integrated into the warehouse control system and oversees the operations of the whole fleet.

The warehouse operates under the "cloud warehouse" management mode and all process data can be traced. This enables centralised inventory management, online billing, and real-time information flows, which greatly improve efficiency and makes it easy to track the whole process.

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Set to open in April, the new 9-metre-high facility in South China will have a higher storage density with a daily throughput expected to reach 128,000 units. It will be using HAI Robotics' ACR (autonomous case-handling robotics) system to help handle growing fulfilment workload.

"We see HAI ROBOTICS as an important long-term partner, as we have shared ambition in smart warehousing," Chen Jiancong, general manager of logistics of Anta Group.

HAI Robotics’ ACR system  was first deployed in Anta's warehouse in southwestern China's Chengdu, Sichuan Province, in April 2021, with 25 customised HAIPICK robots doing case picking and retrieving from shelves to continuously feed goods-to-person picking stations.

The storage density of the 5.7-meter-high warehouse increased significantly to offer up to 27,600 locations, handling up to 80,000 units in outbound orders per day. The warehouse, which was previously stretched tight to handle its tens of thousands of SKUs at low picking accuracy, is now feeding the needs from 1,200 brick-and-mortal stores with a weekly outbound volume of 60,000 pieces.

The tremendous efficiency improvement prompted Anta into a second warehouse automation project with HAI ROBOTICS only three months later, with a larger robot fleet deployed at its 3,500-square-meter warehouse in Jinjiang.

With the redesign of 11-layer shelves inside the 5.7-meter-high warehouse, the project provides around 20,000 storage locations. The warehouse reached a daily outbound capacity of 200,000 pieces with the use of HAIPORT-powered Workstation, an automatic loading and unloading machine.

"Together we will keep innovating to address more challenging scenarios for the footwear and apparel warehousing sector and bring more added value to our customers," said Richie Chen, founder and CEO, HAI Robotics.

Named a global AI unicorn by Hurun Research Institute last year, the company – which specialises in robotics- and AI-based warehouse solutions – currently has a number of ongoing projects with top footwear and apparel brands.

Founded in 2016 with headquarters in Shenzhen, China, HAI ROBOTICS has set up six subsidiaries in Hong Kong SAR, Japan, Singapore, the United States, United Kingdom and the Netherlands, serving customers from more than 30 countries and regions.

With more than 1,300 team members, the company has acquired over 600 global patents for core intellectual properties involving positioning, robot control, and warehouse management.

The post Anta and HAI Robotics embark on third robotics project appeared first on FutureIoT.

“They are specifically designed for use in electricity and water networks, and will be deployed to detect thermal fingerprints in high voltage transmission lines, substations, buildings and solar power stations,” said Saeed Mohammed Al Tayer, managing director and CEO of DEWA.

Al Tayer revealed this last Tuesday a month after the Dubai utility firm launched its first low-orbit satellite called DEWA-SAT 1 to complement the company’s terrestrial IoT communication network

DEWA-SAT 1 is part of  the company’s Space-D programme to improve operations, maintenance, and planning of electricity and water networks by using nanosatellites to support industry 4.0 applications around IoT, AI, blockchain and remote-sensing technologies.

In collaboration with NanoAvionics, DEWA launched the 3U nanosatellite on a SpaceX Falcon 9 rocket from Cape Canaveral Space Launch Complex in Florida, USA. The satellite now maintains a stable orbit at 525 kilometres, travelling some 7.5 kilometres per second and takes about 90 minutes to go around the Earth.

Smart water leak detection device brings AED2.74-M cost savings

Meanwhile, DEWA has been reaping the benefits of its smart initiatives.

For one,  its smart ball  leak detection device, which was inserted into the company’s  water network, has saved the company 68.45 million gallons and AED 2.74 million since its implementation in April 2021.

As part of its ongoing efforts to reduce water losses, DEWA has recently deployed a smart ball leak detection to discover invisible water leakages in water transmission pipelines that are otherwise hard to see or reach.

“We adopt latest technologies in generating, transmitting, and distributing electricity and water, applying the best global practices in all its projects to raise production and operational efficiency,” said Al Tayer. "It achieved concrete savings in developing the water network to promote its effectiveness and reliability, raise the water flow to meet the comprehensive development needs and the growing demand.”

The smart ball system consists of a small diameter sphere that travels freely, driven by the water flow. Sounds generated by a leak, gas pocket or anomalies have unique characteristics.  The system captures the sounds of these from inside the pipeline with the software then able to detect the location of the leak

"In Dubai we have a comprehensive vision to ensure the sustainability of resources as part of the integrated strategy of managing water resources, with particular focus on enhancing water resources, conserving consumption and using the latest technologies as well as innovative solutions,” said Al Tayer.

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The brand’s range of AIoT solutions fall under four products categories: smart entertainment, smart home, smart care and smart accessories. DIZO is the first partner brand under realme TechLife ecosystem.

“Malaysia is a large and emerging market with increasing numbers of tech savvy purchasers in pursuit of smart tech lifestyle products. We aim to offer cutting-edge digital products suitable for modern living, starting with DIZO Watch 2 and DIZO Buds Z.  Other products are in the pipeline will be launched here in stages,” said DIZO in a press statement.

DIZO products will be soon introduced to countries in Asia, Europe, North America, South America, and Africa.

In Asia Pacific, DIZO expects a turnover of RM30 million of sales by 2023, targeting the trendy and tech-savvy youngsters aged 15 to 28.

“As a new brand, we aim to break the clutter of tech similarities and offer products that are aligned to the  needs of every consumer. We offer technology that complements the individuality of every consumer, empowers them and become an extension of their personalities,” said DIZO.

The post DIZO enters Malaysian market with trendy smart wearables appeared first on FutureIoT.

Traditionally, at production lines at manufacturing sites where mass production is undertaken, field personnel mainly use sensor data from equipment to monitor usage thresholds. However, there is a need for experience and know-how in order to understand the fine changes in individual data, and passing these skills along is a challenge.

The beverage maker’s own in-house IT team at Suntory System Technology is currently working with  NEC Corporation to implement the latter’s  NEC Advanced Analytics-Invariant Analysis system, which is set to go live in late May.

Using AI to sift anomalies in sensor data

The new AI-based anomaly detection system from NEC Corporation will automatically discover the relationships between approximately 1,500 sensors at the new can filling line at Suntory’s Natural Water Plant, which will start operating in April.

The system will trigger alarms when changes occur, thereby detecting equipment anomalies at an early stage and helping to resolve them faster.

"Through the provision of this system, NEC is supporting the stable operation of facilities, preserving expert know-how and experience, recognizing errors that are difficult to detect, and contributing to the DX of production lines," said Masayuki Ikeda, general manager, AI Analytics Division, NEC Corporation.

The system uses Invariant Analysis Technology, part of NEC's leading-edge AI technology group, NEC the WISE. By collecting and analysing a large amount of time-series data from a large number of sensors installed in facilities through control systems such as PLCs (Programmable Logic Controller), modelling invariant relationships between sensors (invariants) and comparing changes between predicted data with actual data, users can detect "irregular" occurrences at an early stage.

This system takes advantage of the features of White Box AI and provides information necessary for taking action at maintenance sites, such as where and why functions are performing abnormally. When modelling, users can easily visualise conditions by simply entering the sensor information they want to see with the time that those sensors were operating.

Moreover, NEC will install microphones near filling machines in order to analyse when sounds are different from usual, which could possibly indicate an abnormality with the system.

In the future, it is expected that these advancements could help to reduce the number of people required for maintenance work, while helping to detect abnormalities more quickly.

The post Suntory Beer sets up AI-based anomaly detection system appeared first on FutureIoT.

In recent years, the convergence of IoT technologies with machine learning, artificial intelligence, and cloud, along with automation, have raised the possibility of putting smart IoT technology into business processes or workflows with the idea of automating these with minimum human intervention.

Seth Ryding, chief sales officer (CSO) global sales, Telenor Connexion, acknowledges that how IoT is valued by a business varies from industry to industry.

“There are general values that you see in different verticals such as increased reliability, predictability and being able to collect real time data. You can also add a new customer value that can generate new charging models for users. The way you operate your business and the transition from selling a product to selling a product as a service brings new and shifts the total business value,” he continued.

How do average business and operations leaders in organisations see IoT?

Seth Ryding: There are always two sides to a coin. There are risks and, in some cases, hesitation in moving into a new solution. The pandemic has shown us that those who had made or initiated the transition towards a connected solution pre-pandemic, have been much stronger when it comes to continuing through the pandemic.

What challenges must CIOs address if called upon by leadership to introduce IoT into business processes whether it is workflow or automation or actual operations?

Seth Ryding: An IoT solution is something the whole company needs to stand behind. CIOs and IT heads need to be well prepared to have a good plan about security and capabilities within the company and have a clear view on how they want to create their solution.

Things are evolving so fast and are so complex so the faster you develop your solution and focus on the customer value; it helps the operations process.

When is the best time to consider adopting IoT into the business processes? If yes, how do you minimise disruption and risk to existing operations?

Seth Ryding: I would say there is no time to wait. Looking from an employment perspective, we are living in a time where you can recruit people anywhere in the world which means it is easier to acquire competencies for areas you want to develop. It might just take a little different approach on how you do it.

What is your advice for CIOs and CTOs to help them guide the successful adoption of IoT into the business process?

Seth Ryding: You need to focus on what value you want to bring. Without the value that is related to your connected solution, there is really no point of doing it.

In addition, you need to be agile, try not to overcomplicate things. Create the solution that you can test and that you can scale and then start to roll it out.

Finally, you need to have the support of the whole management team as this is a transformation journey.  

Click on the PodChat player to listen to the full discussion including some interesting use cases of IoT integration.

1. In the context of a typical business operation – for example a financial institution, hospital or government – what is the business value of IoT?
2. How do business and operations leaders in these organisations see IoT? Any preconceived ideas that may hinder adoption of IoT in business processes?
3. For CIOs and heads of IT, what are the challenges they must address if called to introduce IoT across several business processes – for example process or workflow automation?
4. Given the continuing uncertainties arising from the pandemic. Is now the best time to consider adopting IoT into business processes? If yes, what is the better approach to ensure minimal disruption to existing operations, and minimised risks?
5. What is your advice for CIOs and CTOs to help guide the successful adoption of IoT into the business process?
6. You spoke about partnerships and core competencies, what is Telenor Connexion’s value proposition in an organisation’s IoT journey?

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"While most of the revenue today is attributed to hardware, a greater reliance on analytics, collaborative industrial software, and wireless connectivity (Wi-Fi 6, 4G, 5G) will drive spending on value-added services, namely connectivity, data management, and enabling platforms, to more than double over the forecast," said Ryan Martin, Industrial & Manufacturing Research Director at ABI Research.

The top producing manufacturing regions are China, the United States, Japan, and Germany (in that order) and the transportation industry, more specifically automotive manufacturing, is the top industry in terms of revenue in all regions except China, where automotive is second and electronics manufacturing is first. These regions are also the early adopters of advanced manufacturing technology and are the most developed manufacturing economies globally. In terms of automation, the automotive industry leads, having automated close to 50% of operations.

"Manufacturers and their technology partners are acutely focused on supporting the shift to digital threads for better data management and enrichment throughout the manufacturing lifecycle," said Martin. "A common data backbone allows manufacturers to operate more efficiently across teams and departments, and there are a range of suppliers helping manufacturers with their digital threads."

Siemens, PTC, and Hitachi Vantara are some of the leaders in terms of overall innovation and ability to execute. Other important players focus on core aspects of the manufacturing data lifecycle, including modeling and simulation (Autodesk, Ansys, Dassault Systèmes, MSC Software), connectivity (Nokia, Ericsson), quality (Hexagon, Instrumental, Cognex, Keyence), and industrial automation (Rockwell, Emerson, ABB).

"Increasingly, there are more data sources (including spatial data) that can be layered and compared in real time for more contextual and predictive operations.The most advanced manufacturers are starting to think along these lines while the majority have started their digital transformation journey but have yet to fully scale," Martin said.

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Entitled the Future of Work in Logistics, the report pointed out the multiple forces of change – from shifting demographics, technology advancement, to the Covid-19 pandemic –  that are coming together to change long-established status quo at a pace and scale never seen before in the logistics industry.

“The convergence of these forces will transform the way each of us works, to varying degrees – some jobs will require the use of new tools, some jobs will no longer be needed, and many new jobs will be created,” the report said. “While this may seem like a far future topic for some, at the time of writing, severe supply chain labour shortages are so severe it’s making front page headlines around the world.”

The report incorporated perspectives from over 7,000 logistics professionals around the world. From truck drivers and warehouse workers to supply chain planners and data scientists, the industry is already grappling with a growing labour shortage and a war for talent.

Technology advancement

The DHL report noted that the most recognised force sustaining the current pressures for change in logistics and reshaping the Future of Work is the advancement of technology.

Continual improvements in the realms of digitalisation, automation, and artificial intelligence (AI) are already having a significant impact on jobs, workplaces, and entire sectors around the world, further permeating all parts of the supply chain every year.

To date, the report cited sources saying that 29% of all current workplace tasks are done by machines. This is expected to grow to 52% by 2025.

“Logistics can now adopt once infeasible or cost-prohibitive technology, thanks to important technological breakthroughs in recent years involving sensors, batteries, wireless communication, data storage, computing power, and material sourcing,” the report said. “It is only with these modern advancements that augmenting and automating technologies have become unlocked and accessible to supply chains, opening the door to further developments.”

Here are some interesting facts – based on various third-party research – about several important technologies that will drive the digital transformation of logistics:

• From 100 km (60 mi) in 2017 to 1,099 km (683 mi) in 2021 – range of electric light commercial trucks
• 10 hours over 1,530 km (951 mi) – delivery time saved with a semi-autonomous truck
• 10,000 different items with 99% accuracy – picking and packing performance by robot arms
• US$1.5 billion – amount spent on robotic process automation (RPA) software in 2020
• 815 km (506 mi) – range of new all-electric airplanes
• 1,000 devices per meter – connectivity provided by 5G
• 80% price decrease, 2x read accuracy, 4x range – RFID tags over last decade

With the increasing diffusion of augmenting and automating technology into supply chains, the DHL report said workers on facility floors and in the office are seeing their tasks transform and new roles emerge.

However, despite the acceleration of breakthroughs, DHL does  not foresee for the logistics industry an instant and dramatic “flip of the switch” from human labour to automation.

“Instead, we see a gradual period of change over 30 years in which more roles will collaborate with technology in the workplace instead of competing with it,” the report said. “Furthermore, we anticipate an uneven application of technologies around the world, with some regions and teams along supply chains experiencing slower or smaller changes than others.”

Changing demographics

Meanwhile, the big highlight of the report is the shifting demographics within the industry and the need to attract the technology-savvy Millennials and Generation Z to make a career in logistics.

For the logistics industry, the report states the demographic shift builds pressure at both ends of the demographic curve.

As more Baby Boomers retire, Generations Xers – those born between 1965 and 1980 – are expected to take on the leadership roles in the logistic industry. This generation has seen the steady progression of technology advancement in their lifetime from analogue to digital through the advent of the internet and the beginnings of e-commerce.

Today it is estimated that over 50% of all leadership roles are held by Gen Xers, and this generation will become the most senior and experienced supply chain employees in the coming decade.

“Organisations are concerned about a brain drain of institutional knowledge as older employees with decades-long experience and know-how begin leaving en masse for retirement. On the other end, they are eager to backfill vacant positions and attract new talent.”

Indeed, Millennials born between 1981 and 1996 are expected to fill the bulk of new openings. As the first generation to grow up with the internet and the worldwide proliferation of digital technology, they will help drive the digital transformation of the global supply chains. This age group is expected to make up 40% of the working-age population by 2030.

Growing influence of the younger generations

Besides the Millennials, the report pointed out that the future of logistics lies in attracting Generation Z – born between 2012 and 2025 – to work in the industry. Although this generation is still years ahead from joining the work force, they are often considered true digital natives and are already the largest generation alive at 26% of the world’s population.

As Millennials and Generation Z now make up the majority of the global workforce and wield a significant amount of power as consumers and employees. Together they are amplifying pressure on the logistics industry to meet new expectations around sustainability, diversity & inclusion, employee well-being, and tech-forward environments.

“This continued transformation of people in the workforce is accelerating a shift of values in the workplace. Workers are making new decisions about the conditions under which they will provide their labour and skills, the types of organisation for which they are willing to work, and the rewards they expect in return for their time and effort.

“While everyone has their unique set of preferences and goals, they are also often heavily influenced by the period in which they came of age – that is to say, different generations generally have markedly different attitudes and values about the concept of work,” the report said.

The report offers an interesting glimpse of how these two generations view these four areas based on various third-party studies:

• 50% of Millennials would consider quitting their current job to work for an organization they consider to be more environmentally friendly.
• 34% of Millennials and 38% of Generation Z believe systemic racism is widespread in their workplace.
• 50% of Millennial and 75% of Generation Z workers have left a job for mental health reasons.
• 1 in 6 young workers have already quit a job “because their employer did not provide the proper technology for them to do their job.”
• 80% of Generation Z members surveyed around the world want to work with cutting-edge technology.

“To succeed, organisations need to deploy strategies that will attract, retain, develop, and motivate workers in the digital era,” the report said.

The report also cites the big impact that the current COVID-19 has on the global supply chains, greatly accelerating the digital transformation of logistics.

“Many roles – from customs agents to customer service representatives – suddenly faced strict occupancy limits or could no longer come into the office altogether. Organisations are having to quickly source and deploy the equipment, skills, and collaboration tools to enable remote work, as well as allow for new work schedules. Visibility tools, automation, contactless and flexible delivery technologies, and IoT sensors to track shipments are just some examples of technology acceleration as a result of Covid-19.”

The report added: “While things are still fluid in our ‘new normal’ it is clear that some things will never go back to the way they were, and a new way of life and work has emerged. This new Future of Work is here to stay.

The post DHL study: More automation in the cards for logistics industry appeared first on FutureIoT.

Since March of last year, DeepBrain AI has been working closely with AI bankers to improve functions and enhance performance by piloting AI bankers in the AI experience zone located at KB Kookmin Bank's Yeouido headquarters.

As a result, it succeeded in commercialising AI human-based kiosk products for the first time in East Asian country, drawing great attention from the IT industry as well as the financial sector.

"The AI banker has endless possibilities that can be used for customer service with a variety of devices such as mobile devices as well as kiosks in the future. Based on DeepBrain AI's recognised AI human technology and business value, we will continue to explore business routes so that it can be applied to more diverse fields,” said Eric Jang, CEO, DeepBrain AI.

DeepBrain AI's AI human technology is a solution that creates a virtual human capable of real-time interactive communication. It implements AI that can communicate directly with users by fusion of speech synthesis, video synthesis, natural language processing, and speech recognition technologies.

Contactless service amid COVId-19

As a technology that can realise complete contactless service in various fields, banks have the effect of providing a secure counselling service to customers who prefer non-face-to-face in accordance with the COVID-19 situation, and shortening customer waiting time through faster response.

First, the AI banker greets customers when they arrive at the kiosk and provides answers to their questions. All answers go through the process of deriving optimal information based on KB-STA, a financial language model developed by KB Kookmin Bank, and delivered to customers through the AI banker's video and voice implemented with DeepBrain AI's AI human technology.

Specifically, it is possible to guide how to use peripheral devices such as STM (Smart Automated Machine), ATM (Automated Machine), and pre-writing service, introduce financial products, and guide the location of the kiosk installation point. In addition, it is loaded with information on convenience of living such as financial common sense, today's weather, and surrounding facilities.

In addition, the AI banker, with idle-mode, can make natural gestures such as moving hands, nodding, and tidying up clothes during conversation maximizing user experience from the customer's point of view. In addition, it is possible to recognize people through the front camera, so if a customer leaves their seat, the kiosk is automatically finished as a thank you.

This time, KB Kookmin Bank's AI banker modelled and implemented one male and one female model, and used their actual audio and video data. In the case of clothes, the main colours of KB Kookmin Bank are yellow and gray, so that the brand image can be recognized by customers while using the kiosk.

The post KB Kookmin Bank deploys South Korea’s first “AI banker” appeared first on FutureIoT.

“More and more organisations are embracing a digital-first strategy to scale their operations, enhance the experiences of their customers, and unlock the value of technologies like 5G, IoT, artificial intelligence (AI) and machine learning (ML),” said Charles Meyers, president and CEO, Equinix. “Korea and the broader Asia-Pacific market are both enablers and beneficiaries as organisations prioritise digital transformation. To address demand for cloud and digital infrastructure, we have continued to invest in the region through the expansion of International Business Exchange (IBX) capacity and locations, as well as the expansion of our hyperscale program, xScale, in Australia, and now Korea.”

The new joint venture will bring the global xScale data centre portfolio to more than US$8 billion across 36 facilities, and an expected greater than 720 MW of power capacity when completed and fully constructed.

xScale data centers offer access to Equinix's comprehensive suite of interconnection and digital services. These services will tie into the hyperscale companies' existing access points at Equinix, thereby increasing the speed of connectivity to their existing and future enterprise customers.

Equinix entered the Korean market in 2019 with its first IBX, SL1. At the facility, customers can connect their corporate IT infrastructure to global hyperscale providers, including Alibaba Cloud, Amazon Web Service, Google Cloud, Microsoft Azure and Oracle Cloud, via Equinix Fabric, for a high-performance solution and enhanced user experience.

With this xScale expansion, these hyperscale providers can continue to grow at Equinix, in close proximity to an ecosystem of more than 10,000 customers on its growing platform of more than 235 data centers around the world.

The two facilities under the new joint venture, to be named SL2x and SL3x, are expected to provide more than 45 megawatts (MW) of power capacity to serve the unique core workload deployment needs of hyperscale companies, including the world’s largest cloud service providers.

With more hyperscale providers expanding in Korea to support businesses’ digital infrastructure needs, the cloud computing market in the country is expected to flourish. According to IDC Korea, the cloud IT infrastructure market in the country is expected to reach an average annual growth rate (CAGR) of 15% over the next five years, reaching approximately US$1.86 billion (2.2189 trillion won) in sales by 2025. The Global Interconnection Index (GXI Vol. 5), an annual market study recently published by Equinix, also estimates that Seoul will have the most interconnection bandwidth from hyperscale providers within Asia-Pacific by 2024.

To date, seven xScale data centres have opened globally, with more currently under development. The establishment of xScale data centers in Korea will allow hyperscale providers to add core deployments to their existing access point footprints at Equinix, enabling their growth on a single platform that can immediately span 65 global metros and offer direct interconnection to their customers and strategic business partners.

The post Equinix and GIC to build two hyperscale data centres in Seoul appeared first on FutureIoT.

The two companies will bring together Envision Digital's strengths in digitalisation and AIoT, with Mott MacDonald's infrastructure transformation expertise, to help cities, industrial clusters, transport operators and other customers achieve their net zero goals faster and more effectively.

"To overcome the challenges of decarbonising the global economy, digitally enabling infrastructure is essential to make assets smarter, greener and more efficient. Our common vision and technology capabilities will accelerate city infrastructures needed for the new net zero grid,” said Michael Ding, global executive director of Envision.

Mike Haigh, executive chair of Mott MacDonald, believes their latest partnership is a perfect fit as it enables the company  to collaborate in new areas to create innovative solutions to achieve net zero.

“Envision Digital's capabilities in AIoT and digitalisation aligns with our vision of the role digital twins can play in rising to the challenge set by the statements made at COP26."

Envision Digital and Mott MacDonald are already working together to assist Sunderland City Council and South Tyneside Council to facilitate the electrical infrastructure to support Nissan and Envision AESC's multi million pound investment in electric vehicle production and a new Gigafactory in Sunderland, UK at the International Advanced Manufacturing Park (IAMP). 

IAMP is a hub for sustainable high value manufacturing and the project involves creation of one of the largest industrial microgrids in the UK, including proposals for on-site renewables and storage, facilitating the provision of 100% renewable electricity.

As countries, cities and companies declare their net zero target aligned with the Paris Agreement, net zero carbon and infrastructure transformation has become a quintessential part of governments and enterprises' Environment, Social, Governance (ESG) strategy. The strategic partnership between Envision Digital and Mott MacDonald will provide comprehensive sustainability offerings to help drive organisations' net zero infrastructure transformation worldwide.

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The deployment of the robot is also part of FedEx Express’ latest push in digitising its operations and building a smart logistics network.

Called the DoraSorter, the robot is being deployed at the 5,200sqm FedEx South China E-Commerce Shipment Sorting Center in Guangzhou. DoraSorter is already part of the daily sorting operations and is capable of handling small inbound and outbound packages from e-commerce customers in South China.

Kawal Preet, president of the Asia Pacific, Middle East and Africa (AMEA) region at FedEx Express, said: “With e-commerce taking centre stage in the future of retail in our region, the speed with which a parcel can be picked up and delivered to customers’ doorsteps has become a dominant factor in driving the adoption of sorting robots.”

He added that bringing DoraSorter to China as a pilot program is a natural choice as the country is the world’s biggest e-commerce market with an expected valuation of US$3.3 trillion by 2025.

“As we look to build a data-driven, smart logistics network to help our customers thrive in the digital economy, this alliance with Dorabot is part of becoming the network for what’s next. AI-powered technology will continue to change how we support customers in the region and enhance supply chains for the future,” said Preet.

DoraSorter’s core function of sorting parcels based on destination matches the sorting centre’s operation process. Key features of DoraSorter include:

• At approximately 40sqm , the robot can carry up to 10 kilograms of packages, covering up to 100 destinations simultaneously.
• The robot has a special drawer-shaped gripper that can connect with the conveyor belt seamlessly.
• Equipped with a barcode reader that scans package to obtain destination information, the robot uses its gripper to receive a package inward from the conveyor belt and moves it outward to the corresponding destination slot.

 "The use of DoraSorter helps FedEx sort a higher volume of cross-border e-commerce shipments,” said Xiaobai Deng, founder and CEO of Dorabot. “It is the starting point of a global collaboration between Dorabot and FedEx. We hope that we can work together to bring AI and robotics applications to more businesses and consumers."

Indeed, FedEx investment in warehouse automation echoes broader industry trends. Triggered by the global pandemic, logistics players are optimising operational efficiencies, from warehouse management to last-mile delivery, to cater to the soaring demand for e-commerce products, seasonal peaks, and consumers’ heightened expectations for fast delivery.

According to McKinsey & Company, the global warehouse automation market is projected to reach US$51 billion by 2030. By 2025, more than four million commercial robots will be installed at more than 50,000 warehouses.

“Innovation is at our core and is a major factor behind FedEx strategy in China,” said Robert Chu, vice president, Operations, FedEx China. “To meet customers' changing needs, we have been exploring and investing in new technologies to enhance every key aspect of transportation. The rapid rise in e-commerce has led to higher customer demand for timeliness and flexibility in logistics services, creating new challenges and opportunities for the entire logistics industry. Our collaboration with Dorabot is our latest effort to improve operational efficiencies and build an agile logistics infrastructure through robotics technology that will support the growth of China's e-commerce industry."

FedEx continues to leverage advanced technologies to streamline its operations and help customers of all sizes in China and beyond seize opportunities in the global market.

Last October, FedEx teamed up with Neolix to test an autonomous delivery vehicle in China. The company is also testing FedEx SameDay Bot , Roxo  in AMEA to explore the future of contactless, last-mile delivery.

In addition, FedEx also launched a sensor-based logistics device – SenseAwareID, designed to enhance tracking precision, reliability and timely delivery of critical shipments such as life-saving pharmaceuticals and emergency medical supplies.

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Each ‘accident’ would equate to downtime for the entire production line which would, in turn, lead to delays in delivering the final product to customers. You can imagine the behind-closed-door meetings trying to figure what happened and how to avoid similar incidents in the future.

The true cost of downtime

Alain Dupuis, VP Industrial Development at UnaBiz acknowledged that nothing is ever simple when it comes to estimating the cost of downtime.

“It varies greatly, from a minor annoyance to catastrophic proportion. What is difficult to evaluate is the rippling effect of one downtime over a whole process. Sometimes a small downtime can have severe consequences down the line,” he elaborated.

Those were the days when rudimentary controls were the prevailing technology, and any automation would be prehistoric by today’s standards.

Persistent downtime

Advances in IoT and industrial automation have evolved to the point that today there is a potential to significantly improve efficiency and safety through predictive maintenance.

However, Dupuis pointed out that very few aspects are currently addressed by technology.

“It is still a long way before we have implemented across it the board. There is a major cost involved to cover all the aspects and despite the best advancements in technology AI cannot do everything so it will never be 100% foolproof,” he added.

Understanding the AI equation

Given all the technology innovations, particularly the injection of Industrial Internet of Things (IIoT) technology into the production facility, for example, why do downtimes still exist?

For Dupuis, the most important action item is developing a proper digital model of a business operation through the interaction of all the processes involved.

“Then run AI through this model fed by real-time information from IoT nodes to detect bottlenecks early and balance the load between processes to remove potential showstoppers and streamline the operations. After this, use the AI to work on improving the processes themselves,” he continued.

He cautioned that one of the issues with AI is that it needs examples of failures to define what success is. For example, in predictive maintenance for a water pump, the AI needs to know what are the signals that say that the pump will break.

“Not many businesses will want or can afford to break something just to make their AI work faster and better. So, the implementation of AI in most cases can be a long process before reaching its effectiveness,” he opined.

To AI or not to AI

The quest to modernize a production line is not as simple as introducing new software. Any changes will incur costs such as a planned downtime while the new technology is being introduced to the process and the people that need time to learn to use the technology.

Dupuis highlights the very first challenge – complexity!

This is the paradox of modernization: the more you try to simplify the process, the more sophisticated the technology needs to make it happen.

“For AI to work you need a lot of things to be put into place. AI is kind of the last thing you will add when you have already a strong data collection system only when a massive amount of data is collected over time, can insights be drawn, and Machine Learning and AI come in.

“For this, you need IoT to be implemented at a massive scale. Then, you need it to relate to the enterprise IT system. This requires a lot of dedication and know-how which often companies do not have internally and with little external consultancy available for help,” he added.

Dupuis raised the second thing is cost. “All this complexity requires a heavy investment, in capital and human resources. The third aspect is linked to the second, a lack of confidence regarding the return on investment. AI is still a very new thing, and it is often difficult to measure the potential benefits,” he said matter-of-factly.

Questions to ask

Because everything involves an investment – whether it is time or resources – there should be sufficient understanding about what is involved and how it will impact people, processes and the business.

Dupuis agreed that people need to be honest with themselves in looking at the major pain points that affect running their business. He suggested going about this along with a comprehensive risk analysis.

“What needs to be put forward are those with either high recurring occurrences and/or with potential major destructive effects. Then focus on the top pain point and risk and start with this,” he continued.

He explained that this will limit the expenses and maximize the ROI. Only then to approach this effort using both Agile and Design Thinking methodologies.

“Do not look at it as a one-off effort but as a continuous work where improvements will be made along the way through refinement of the model and with the integration of new services as you will be answering more pain points and risks along the way,” he continued.

According to Dupuis, the question they need to ask themselves is: ‘Are we ready and willing to commit to digital transformation?’

“When it comes to selecting their service providers, they should avoid vendors pushing ready-made "universal" solutions even if they look like good deals at first glance. They want to choose a service provider that is listening to them and offering a tailored service because they know that every business is different. Never forget that this is going to be a very long-term work relationship,” he concluded.

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This year will continue to see industry players in the built environment sector focused on finetuning the vision of the Future of Buildings – when space, technology, and people intersect.

“Space” refers to the physical area and the movement flow, such as spatial intelligence (e.g., predictive facilities management), while “technology” would refer to facilities-centric concerns such as building and environmental intelligence (think predictive energy management). Meanwhile, “people” looks at human-centric considerations, including behavioural intelligence (e.g., tenant information analytics), and wellness intelligence (e.g., smart workplace productivity, clean indoor air circulation for better health well-being).

Driving this intersection would be innovation and the identification of smart technologies that have to be developed and rolled out.

Myriad of technologies come together

Realising the vision for future buildings involves the integration of a myriad of technologies from analytics, artificial intelligence (AI) and machine learning, to converged systems and Internet of Things (IoT), as well as data management.

Analytics, AI, and IoT enable buildings to be self-adapting, self-healing and self-optimising. The building will be able to predict and learn occupants’ preferences and usage patterns. It will also be adept at detecting human presence within a space and personalising the environment for improved productivity and wellness – critical when building occupancy is expected to continue fluctuating depending on the government’s directive.

AI would also be useful to further personalise the building as it can streamline maintenance tasks such as load management and fault detection. This includes installing automated air-filtration systems with touch-free controls that detect and reduce airborne pathogens, or using timed artificial lighting that mimics changing natural light throughout the day. This will improve energy usage, increase the commercial attractiveness of the property, enhance its environmental, social and governance (ESG) metrics, and manage risks of viruses spreading.

Visualising cognitive buildings

In future, the value of buildings will not depreciate over time. By leveraging data-driven technologies, buildings will become smarter and able to upgrade its features, thereby increasing their own value.

Such buildings are known as cognitive buildings – and this development has happened as the industry transitions from system insights into platform optimisation that enables data-driven user applications. Focuses are also changing, from energy efficiency to concerns around sustainability and wellness.

While data can provide actionable insights to transform buildings into cognitive buildings, it can be daunting to deal with the massive amount of data that is collected . To overcome this, organisations need to have the right tools to digest the data and the requisite domain knowledge to analyse the information to extract the insights.

Systems and solutions of the future

As we enter the future, converged systems & IoT solutions will lead the way: they are the drivers behind cognitive buildings. Equally important is a unified platform that connects devices and data to deliver a holistic outcome for the occupant. Synonymous to data is security – which needs to be everyone’s responsibility. There needs to be basic cybersecurity awareness across the industry, as well as ensuring all building data are encrypted at rest and in transit using industry-leading protocols. There also needs to be restricted access and secure data protection to ensure user privacy and adherence to existing data protection laws, as well as regular audits to validate security measures to avoid complacency.

In conclusion, as we move into the new year, we can expect a wave of change in the way buildings and spaces are designed, built and utilised in a post-pandemic world. Fast-emerging technologies will help unlock predictive insights from behavioural, building, and spatial intelligence that will be critical to transform the occupants’ experience. 

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Through these investment activities, the three companies expect to stay ahead of the convergence trend within the ICT industry and discover unicorns that can change the industrial landscape, which will lead to valuable business synergies.

The three SK Group companies announced the fund as they launched their newly-created “SK ICT Alliance” at CES 2022 as they strive to make inroads into global markets in the areas of 5G, AI and semiconductor technologies

US entity to target the AI semiconductor market

First on the agenda of the new SK ICT Alliance is the establishment of SAPEON Inc. in the US to introduce SK Telecom’s AI chip. The new US-based company will serve as an outpost for expanding SKT the AI semiconductor business to the global market by attracting U.S.-based big tech companies as major clients.

It will also secure an edge in luring semiconductor development experts and drawing in outside investors. Moreover, as the subsidiary of SAPEON Inc., SAPEON Korea will take charge of business in Korea and the Asian region.

“By proactively responding to changes taking place in the areas of AI, metaverse and 5G, we will prepare ourselves for the next decade,” said Ryu Young-sang, CEO, SK Telecom.

SK Telecom plans to lead the development of SAPEON-related technologies by leveraging its R&D capabilities and service experience accumulated in 5G and AI. In the mid-to long-term, the company will expand its SAPEON model line-up by developing AI chips dedicated to data centers and autonomous driving.

SK Telecom will also promote synergies between its AI semiconductor and SK hynix’s semiconductor memory technologies, while also attracting strategic and financial investors in cooperation with SK Square.

Projecting that the convergence of AI and metaverse will define the future world of ICT, SK Telecom plans to innovate its three key services, T Universe, Ifland and AI Agent, in an accelerated manner. Moreover, it will also introduce new services by adding connected intelligence to future devices such as UAM aircrafts, self-driving cars and robots.

SK hynix in talks with Qualcomm

Meanwhile, SK hynix, the world’s second largest memory chipmaker, and Qualcomm, the world's leading wireless technology innovator held talks regarding collaboration on the development of data centre applications and high-speed memory for PCs.

SKT and Qualcomm discussed cooperation in 5G business areas including metaverse and smart factory.

“With competition intensifying in the global ICT market, cooperation is no longer a matter of choice but an absolute necessity," said Park Jung-ho, vice chairman and CEO of SK Square and SK hynix. “All ICT affiliate companies of SK will lead innovations by pursuing cooperation that goes beyond all national borders and industries.”

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XPeng has already rolled out the new voice assistant technology to P7 customers across China via a major over-the-air (OTA upgrades). In future, the company plans to introduce future generations of the upgraded voice assistant into other production models.

The carmaker worked with Microsoft to overcome several key challenges to create the new cutting-edge voice assistant integration.

To deal with telecommunication network jitter while the car is moving, while reducing data traffic consumption and hardware burden, and ensuring continuous high-quality speech, XPENG introduced context-specific multi-level caches, caching high-quality sound in advance and distributing it to minimise reliance on the network.

To deliver natural-sounding high-fidelity speech, XPeng uses Microsoft Azure with caching and compression to deliver XPeng’s high-quality voice sampling rate of 24K Hz and quantization level of 16 bits, without overburdening the data network or the car’s own CPU. XPENG also worked with Microsoft to minimise ambiguity and to optimise accuracy in voice assistant speech.

"This is a cutting-edge exploration of vehicle voice interaction in the auto industry," said Hao Chao,  senior expert with XPeng Automotive AI Products. “It required months of dedicated work by our team to overcome the challenges, and now delivers a whole new level of natural speech. With a deep understanding of urban mobility, we are finding many more scenarios to leverage AI technology for a high level of driver-machine intuition.”

“With advancements in research and technology, Azure Cognitive Services like vision and speech, will play a pivotal role in defining unique in-vehicle experiences,” said Sanjay Ravi, general manager, Automotive, Mobility, and Transportation Industry at Microsoft. “With speech as a primary interaction tool within the vehicle, Microsoft’s custom neural voice services enable automakers to develop their own differentiated and authentic branded experiences.”

Microsoft research breakthroughs in speech, natural language and machine translation have helped significantly advance the fluency, quality, fidelity and naturalness of voice assistant technology over the past several years. These innovations have been integrated into commercially-available speech and language capabilities within Azure Cognitive Services and other Microsoft products, so that companies like XPeng can bring richer, more engaging experiences to their customers.

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The company is  harnessing the power of AI and IoT to direct urban construction towards a new stage of low-carbon, energy-saving, high-efficiency and intelligence, using revolutionary smart data solutions to add vigour and vitality to traditional industries and economic development.

The ESG smart solutions have been installed in Yichang in areas such as COVID-19 pandemic prevention and control; weather monitoring and early warning; and,  Yangtze River ecological protection. They are also used to care for vulnerable groups, grassroot-level inclusive medical care, animal welfare protection, and  garbage classification.

"Our hope is to use ESG as a guide to offer more digital solutions for the environment, society and governance. We are willing to work with partners in various industries to build a more environmentally friendly, safer, livable and smart city. Furthermore, we have already witnessed such changes taking place now. Changes will continue to happen in the future,” said Sensoro CEO Tony Zhao.

As a city-level data technology service provider, Sensoro has  attracted many research scholars, doctors, and other talents to join its ranks. Through independent research and development, the team has created an end-to-end, integrated IoT and AI technology and product system, including smart sensing terminals, IoT communication base stations, chips and edge computing servers, and a global data visualisation service platform.

A Yichang resident Dazhong Tao said: "These high technologies have provided us with enormous convenience in our everyday life, making our lives more secure. For example, we can easily access health service."

The company expects to replicate the deployment of its ESG smart solutions across China. Sensoro is relying on its independent research and development capabilities in the AIoT field to implement the modern service concept of sustainable development, which contributes to the digital and intelligent development of China's urban and rural areas.

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Today’s supply chain disruptions, labour shortage, and macroeconomic turmoil happening in 2021 and may continue throughout 2022, manufacturers are ready to make aggressive investments to modernize their factories with EdgeAIoT technologies to transform into a “lights-out” factory.  However, is EdgeAIoT ready for the challenge? 

The answer is yes, it is ready for the challenge because of the mass adoption of IoT in the past 10 years.  I am witnessing many manufacturing CIOs inquiring about edgeAIoT as a part of their hyper-automation roadmaps.

What manufacturing CIOs should be doing to embrace edgeAIoT:

1. Speak with your cloud provider to see if they have an edge AI on-ramp capabilities.  What are the data requirements, data sharing transmission costs and types of training and inference is done in the cloud vs the edge?
2. Is IoT installed at key points of the shopfloor and PLC controllers?  Is the digital thread established and its associated governance model?
3. What closed-loop tasks and information are being relayed back to the data lake and machines?  Predictive maintenance?  Asset optimization?

2022 is going to be a wild and interesting year for smart manufacturing.

First published on Gartner Blog Network

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The proof of concept (POC) project is part of Rhenus ongoing strategy to deepen  IT-driven digitalisation by tapping into smart logistics to build a sustainable and robust supply chain.

The company tapped Geek+ as technology partner providing advanced robotics and AI technologies.

The Rhenus Hong Kong warehouse will use Geek+ Goods-to-person solutions. Robots will be used as part of the system to automatically bring goods to the operators, achieving 99.99%  accuracy. The solution also helps maximise warehouse storage as aisle space is minimised.

"Our goal is to provide the best and most innovative logistics service to achieve faster and more flexible movement of goods, to cater to the rapid growth in e-commerce. By working closely with Geek+, we not only realise warehouse digitalisation, but also improve operational efficiency and accuracy, translating to greater cost-savings for customers in the long run,” said Cliff Xu, CEO of Rhenus Air & Ocean Greater China.

With the Geek+ solution, Rhenus Hong Kong can handle large volumes of orders, flexibly meet rapidly changing SKUs, and improve order-fulfilment performance. The Hong Kong site will be the first smart Rhenus warehouse in the Asia-Pacific.

One of the features of the AI-driven system are Geek+'s proprietary algorithms. They optimise order combinations and adjust the inventory layouts in real time, maximising efficiency. In the Rhenus Hong Kong warehouse, over 2,000 SKUs of cosmetic products are constantly arranged according to popularity and expiry date.

"We believe that the smart warehouse upgrade is the only answer to the rapid growth of e-commerce business and growing customer expectations. We will continue to support Rhenus with tailored solutions that best fit their multi-customer business,” said Lit Fung, VP, managing director APAC, UK and Americas at Geek+.

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In addition to eliminating the need for time-consuming manual adjustments, the AI estimates the confidence level of inferences regarding factors such as machining error and then controls the FA equipment based on suitable levels of confidence. The technology is expected to lead to more stable, reliable and productive operations, particularly in agile manufacturing.

“Operating needs change frequently in agile production, so optimum conditions, such as FA equipment motion speeds, revolutions, etc., must be adjusted individually for each type of product,” Mitsubishi Electric in a statement. “Performing such adjustments manually, however, requires labour and time, resulting in decreased productivity. Moreover, declining birth rates and aging populations in many developed countries are resulting in a shortage of skilled workers capable of adjusting FA equipment.”

This is the latest deployment of an AIST AI technology in Mitsubishi Electric’s FA equipment since the two companies  began collaborating on AI development in fiscal 2017.

Moving forward, Mitsubishi Electric expects to increasingly incorporate various forms of its Maisart  AI technology in FA equipment and systems to significantly improve manufacturing productivity.

Key features

• Fast: AI achieves high-speed inferences for dynamic control of FA equipment control

In factories that use FA equipment for agile manufacturing, such as computerized numerical controller (CNC) cutting machines and industrial robots, the movements, operating speeds, acceleration, etc. of the equipment vary during the operating processes. In conventional manufacturing, skilled workers must adjust the operating parameters according to various specifications, such as the required level of accuracy. Mitsubishi Electric has now developed an AI technology that simultaneously performs high-speed inferences and equipment control for real-time FA operation. Incorporating Mitsubishi Electric’s expertise as an FA equipment manufacturer, the new low-load AI control technology performs inferences while simultaneously controlling FA equipment. Although the technology minimises its processing load, it is capable of achieving high-level inference accuracy while simultaneously guiding FA equipment control.

• Adaptable: In-process learning to adapt to constantly changing work factors

The shapes of workpieces change during manufacturing, and this can lengthen manufacturing times or lower processing quality. In addition, changes can vary by workpiece, making it difficult for FA equipment to learn in advance. Mitsubishi Electric’s new technology, however, allows the AI to learn work factors during FA equipment operation and then make real-time adjustments as needed. In addition, the technology formulates physical phenomena, such as friction, and then incorporates these mathematical expressions to enable learning during operation, making it possible to adapt to constantly changing processing factors.

• Reliable: AI performs adjustments according to inference-confidence levels

AI inferences must be reliable to ensure that real-time control of FA equipment leads to stable product quality and efficient processing. Mitsubishi Electric’s new algorithm calculates the confidence level of inferences by learning the machine characteristics of each process and each target device. By using this algorithm to control FA devices, the new AI ensures high reliability.

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The AI speaker called Nugu Candle is fitted with  Amazon’s Alexa voice service to enable users to enjoy both English and Korean based AI services.

SKT plans to continue applying Alexa to its Nugu devices including Nugu Candle SE, which is scheduled to be launched early 2022. The company will continue to work closely with Amazon to make more services available to Korean users.

“As Korea’s first AI speaker, Nugu has been providing diverse services to enhance customers’ AI experience. Now with the addition of Amazon’s Alexa voice service, Nugu will further strengthen customer value and convenience through differentiated content and services,” said  Lee Hyun-a, Vice President and Head of AI&CO of SKT.

Customers can use the wake word “Aria” to initiate Nugu services in Korean, and “Alexa” to enjoy Alexa’s services in English.

Both Nugu and Alexa support basic features like weather, news, chitchat and calendar. Korean content like Flo (music streaming service) and Potbbang (audio streaming service) can be accessed via Nugu, while foreign content such as TuneIn can be enjoyed via Alexa.

To visually show the two independent AI agents, SKT applied two different colours of LED lights to Nugu Candle - Light blue for Nugu and dark blue for Alexa.

SKT’s Nugu Candle users can use the new service by updating the Nugu app and connecting their account via the ‘Connect Amazon Alexa’ menu.

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With  the smart hospitals model, Thailand expects  people in remote areas will have better opportunities to access advanced health care services.

Thailand Prime Minister Prayut Chan-o-cha welcomed the new medical facility saying it will help minimise processes for hospital staff, lower overall risk, and enhance the effectiveness and efficacy of healthcare.

“We understand the importance of technology, and this is an important first step in the utilisation of digital technologies and 5G in the medical field. We hope the project will act as a blueprint for all smart hospitals in Thailand going forward,” he said in a statement.

Siriraj Hospital and Huawei signed a five-year agreement in December 2020 to accelerate the use of 5G and cloud technologies. Currently, Siriraj Hospital has started piloting 5G portable medical boxes, 5G unmanned vehicles, 5G medical carts, and 5G smart hospital beds.

Under the 5G Smart Hospital project,  Siriraj Hospital will be working with Huawei on nine sub-projects. These include Smart Emergency Medical Services; Smart Emergency Room; Pathological diagnosis system with 5G and artificial intelligence; 5G AI Platform for Non-Communicable Diseases; Smart Inventory Management; Permission-based blockchain for personal health record; Smart Logistic with 5G Self-Driving car; Multi-access Edge computing (MEC); and, Hybrid Cloud

Furthermore, both companies will establish a Joint Innovation Lab to incubate over 30 innovative 5G applications that will be promoted nationwide from 2022.

China’s ambassador to Thailand Han Zhiqiang said China will leverage technology to help Thailand fight the pandemic. "China and Thailand's 5G cooperation has become a model in the region, helping Thailand become the first country in Southeast Asia to launch 5G commercial use.”

Abel Deng, CEO of Huawei Thailand, said, "This signifies a model for upgrading Thailand's public health industry in the future and contributes to Siriraj's transition to becoming a smart hospital.”

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“We to learn how they will potentially use the service and how they will have some of the benefits that the service can bring in,” said Mike Tzamaloukas, general Manager of IoT Automotive at AWS.

For over a 10 years now, car manufacturers have been collecting data from standard vehicle sensors to evaluate operational and safety indicators like engine temperature and vehicle stability. However, today’s new car models comes with advanced sensors like radar and cameras. Greater vehicle connectivity gives automakers opportunities to improve vehicle quality, safety and autonomy; but on the flipside, it also generate exponentially increasing amounts of data.

Indeed, by 2030, a study made by the Mckinsey Center for Future Mobility predicts that more than 95% of new vehicles sold globally will be connected to the internet – up  from about 50%  today.

Two-fold data challenge

There are a two-fold challenge in collecting in-vehicle information: data variety and data volume.

A car manufacturer typically has in its portfolio several models in its lineup, with each model producing data in a unique format. This results to an overwhelming volume of unique vehicle data configuration, data structures and schemas. Compounding the problem, most of these data is  not readable by human and is encoded in proprietary formats specific to automakers.

To make the data usable, automakers must first decode it then reconcile it across their fleets. Collecting and reconciling this data across multiple variations of vehicle models requires automakers to build, scale, and maintain custom data collections systems.

Furthermore, with the increasing sophistication and autonomy of new models, there more sensors inside a connected vehicle, which generate more data. In particular, connected vehicles today have multiple cameras and radars fitted with advanced sensors, thus increasing data volume at an exponential rate and making it difficult to manage.

What’s more, this growing amount of data is being transfer to the cloud, so car makers can use it for AI and machine learning training and improvement. However, cloud data transfer is cost prohibitive across a fleet of production vehicles. A single autonomous vehicle can generate up to 2 TiBs of data hourly per vehicle. As a result, automakers often resort to using autonomous test fleets with specially built on-board storage as a work-around for getting the data they need to train AI/ML models.

Faster and cheaper data collection

According to Tzamaloukas, AWS IoT FleetWise is the company’s first purpose-built service for the automotive industry aimed at making data collection easier, more efficient and at scale.

For one, it standardises access to fleet-wide data through its global signal catalog without the need to develop custom data collection systems.

“It takes away a lot of the vehicle model variations that exist today, where different vehicle models have different features, different capabilities, different signals in them, therefore making it hard to collect data across all of the vehicle models,” Tzamaloukas said.

The service also allows automakers to reduce costs and enable more efficient data transfer with intelligent filtering that sends the exact data you need to the cloud.

“We want to create a service that allows automakers to easily focus on the data that they're interested in. And with intelligent data-filtering, achieved this efficient upload to the cloud of the valuable information. Thus, it will allow them to extract high-volume data more cost efficiently,” said Tzamaloukas.

Furthermore, AWS IoT FleetWise Surface delivers near real time access to vehicle health data, which would enable automakers to detect and mitigate issues faster, help prevent potential recalls, and remotely assist customers.

“Today, it takes weeks – if not months – for automakers to detect and mitigate any anomaly in a vehicle. The service’s near real-time access to in-vehicle data would allow them to find the problem that may lead to a breakdown, such as false positives in radar or camera systems.”

How it works:

Complementary to proprietary systems

Acknowledging that automakers today have their own proprietary autonomous vehicle data collection systems, Tzamaloukas said that AWS IoT FleetWise can work alongside them.

“We are looking for working with partners and working with customers, to see how we can complement the existing approach to collecting data, to ingesting data, and to representing data in ways that can be open in ways that can be scalable. And, of course, with all the security, privacy, and other robustness and reliability guarantees that AWS can offer. So, we are just at the beginning of an exciting journey. And looking forward to  working with customers and partners to learn more,” he said.

He noted that, currently, automakers focus primarily on collecting a lot of data with their own test vehicles.

“Their data collection approach so far has been manual, meaning that they retrofit vehicles with a lot of SSD drives, they drive them, they get terabytes of data. And then they upload these terabytes of data to AWS.

With AWS IoT FleetWise, he added that they are complementing that existing approach towards giving the automakers the ability to not collect terabytes of data from one or a few test vehicles.

“But instead, collect something much smaller, just a few megabytes, but from many production vehicles out there on the field. So, we do believe we will be complementary to the current AV data collection approaches,” said Tzamaloukas.

He added: “Coming back to the way that FleetWise works, the first step they have to do is visualise their car models – when an OEM goes to our console and uploads proprietary markings of the data that exist in the vehicle. And of course, that belongs only to them and their account. That's information that we as AWS never seen.

“But once they have done that step, they now have this ability to be collecting data based on the open standards and they are able to now with FleetWise, collect the different proprietary data formats in the vehicle.

“So, they do actually coexist in some ways. But one path one method is going to be very hard to scale. The existing approach today is going to be hard to scale because you will keep on having to fix things that break us you go. Whereas with the FleetWise approach, we believe that you will have the ability to have a flexible and adaptable way, and data structure eventually, that can help you keep up with any number of changes that may happen in future vehicle models, and in future data types that you want to collect.”

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“We have completed 500 smart campus projects around the world, helping our customers achieve business success," said Bob Chen, vice president of Huawei Enterprise Business Group. "We look forward to continuing to work with our customers, to deal with challenges as we build a smart world together.

Huawei hopes to get a lion’s share of the smart campus market in the Asia Pacific, which is currently estimated to exceed US$10 billion in value based on analyst figures.

The difference between Huawei's smart campus and a traditional one lies in the upper-layer brain, which includes the Intelligent Operation Centre (IOC) platform. The IOC platform delivers intelligent asset management of the campus  with digital twin visualisation of the physical space.

Implemented through wired networks, Wi-Fi, 5G, microwave, and IoT technologies, it is built with energy-saving features where IoT used to connect various terminals and sensors to collect energy consumption information. AI algorithms are used for analysis and optimisation, reducing energy consumption and OPEX of campus networks and achieving green and sustainable development.

“With the digital platform integrated with video cloud, IoT, Internet Communications Protocol (ICP), Geographic Information System (GIS) and other new technologies, customers could leverage on the platform to design, develop and verify solutions to create a secure, comfortable, efficient and green campus,” said Tony Shi, CTO of Huawei APAC Scenario-Based Solution, adding that major use cases for the smart campus include  ubiquitous connectivity, integrated management and new service development.

Huawei’s smart campus solution also implements intelligent video prevention and control and AI analysis. It also features office collaboration – where the smart office and smart classrooms implement seamless collaboration, greatly improving remote communication and efficiency during the epidemic, and bringing users new experience in office, learning, and diagnosis and treatment.

Positive feedback

Several Huawei customer at the launch of the smart campus solution expressed optimism about the new offering.

“As ICT advances, system construction gets more and more complex, with campuses getting bigger and bigger. It is therefore becoming harder to manage them and there is an urgent need for us to understand them better and manage them smarter. The launch of this Smart Campus Solution is timely, providing many of our members with the solution that they've been looking for,” said Tony Khoo, president of the Singapore International Facility Management Association (SIFMA).

Kittikun Potivanakul, the CTO of DTGO,  said Huawei’s smart campus helps enterprises integrate digital services, with its customer-oriented approach replacing a functional one.

“With the deployment of smart services — such as an IOC perimeter management, video-based patrol, and device management — the solution deploys big data analytics to support decision-making at the management level. Similarly, it supports business innovation and will, in the future, facilitate multi-campus access.”

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For instance, Pfizer is using AWS to enhance its continuous clinical manufacturing processes by incorporating predictive maintenance capabilities built with AWS machine learning services like Amazon Lookout for Equipment, the AWS’s service for detecting abnormal equipment behaviour by analysing sensor data.

As a result, the pharmaceutical firm can maximise uptime for equipment such as centrifuges, agitators, pulverisers, coaters, and air handlers used in clinical drug manufacturing.

The overall focus of this collaboration is to support Pfizer in more rapidly and reliably producing new drugs and evaluating their potential health benefit for patients.

New PACT initiative

To mark the enhanced collaboration between the two companies, they have created the Pfizer Amazon Collaboration Team (PACT) initiative, which applies AWS capabilities in analytics, machine learning, compute, storage, security, and cloud data warehousing to Pfizer laboratory, clinical manufacturing, and clinical supply chain efforts.

“Our goal with AWS is to expedite the processes for drug discovery and development in ways that can ultimately enhance patient experiences and deliver new therapies to market. Working closely with AWS experts in machine learning and analytics, we aim to provide our scientists and researchers with the insights they need to help deliver medical breakthroughs that change patients’ lives,” said Andrew McKillop, vice president of pharmaceutical sciences, worldwide research, development, and medical at Pfizer.

Both companies are working to develop a prototype solution for detecting abnormal data points in its drug product continuous clinical manufacturing platform for solid, oral-dose medicines. The prototype solution uses Amazon SageMaker (AWS’s service for building, training, and deploying machine learning models quickly in the cloud and at the edge), Amazon Lookout for Equipment, Amazon Lookout for Metrics (AWS’s service for automatically detecting anomalies in metrics and identifying their root cause), and Amazon QuickSight (AWS’s scalable machine learning-powered business intelligence service for the cloud).

The machine learning models used in the prototype were able to provide early warnings for alarms with minimal false positives and direct users to the relevant signals. As a result, Pfizer can process data from the equipment and sensors involved in Portable Continuous Miniature and Modular (PCMM) manufacturing to detect anomalies as they occur, predict maintenance needs, and reduce potential equipment downtime.

Mining insights  from legacy data to develop new drugs

According to Kathrin Renz, vice president of business development and industries at AWS, the past two years have reinforced for the world just how much speed and agility matter at every step of the research, development, and clinical manufacturing cycle when lives are on the line.

“We’re proud to work with Pfizer and lend our deep domain expertise to assist in developing solutions that could significantly improve the lives of patients globally,” she said.

With the new PACT initiative, Pfizer scientists will also collaborate with AWS healthcare and life sciences professionals to explore how researchers in Pfizer’s Pharmaceutical Sciences Small Molecules teams can extract and mine information from legacy documents by leveraging AWS analytics and machine learning services.

Pfizer has an extensive collection of documents that contain valuable data from a variety of drug development processes. The documents include data related to synthetic chemistry routes, recipes, analytical tests, method development, formulation composition, clinical manufacturing campaigns, batch records, technology transfer, and many other types of work.

Housed within these documents are potentially powerful insights that could point Pfizer researchers in the right direction for developing new drugs or repurposing existing ones—if the researchers can identify and link the right information efficiently.

To gain quick, secure access to the right information at the right time, Pfizer’s Pharmaceutical Sciences Small Molecules teams are working with AWS to develop a prototype system that can automatically extract, ingest, and process data from this documentation to help in the design of lab experiments.

The prototype system is powered by Amazon Comprehend Medical (AWS’s HIPAA-eligible natural language processing (NLP) service to extract information from unstructured medical text accurately and quickly) and Amazon SageMaker, and uses Amazon Cognito to deliver secure user access control.

“Our life sciences customers are increasingly looking for opportunities to scale expertise, insight, and secure access to the right information, at the right time, with the aim of reducing the time and cost for drug development and clinical trials,” “AWS’s breadth and depth of cloud capabilities help support Pfizer’s teams through secure, novel research methods as they work to optimize drug development and clinical manufacturing processes.

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Saudi Arabia unveiled plans for the world’s largest floating city this week, as it enters the new phase of the US$500-billion Neom city-state project that covers 10,000 square miles of country's Tabuk province, near its borders with Jordan and Egypt. Neom – a combination of the Greek word neos, or “new”, and mustaqbal, Arabic for “future” – is a flagship project of Saudi Crown Prince Mohammed bin Salman.

Located at the southwest corner of Neom, Oxagon is envisioned to be an industrial district where the city-state’s integrated port and logistics hub will be located. It lies in close proximity to the Suez Canal where approximately 13% of global trade passes through.

“Oxagon will be the catalyst for economic growth and diversity in Neom and the Kingdom. I am pleased to see that business and development have started on the ground and we look forward to the city's rapid expansion,” Prince Salman said.

He added that Oxagon will redefine the world's approach to industrial development in the future, which will have the protection of the environment at its core. It will represent a radical new model for future manufacturing centres.

Nadhmi As-Nasr, CEO of Neom agrees that Oxagon will signal a fundamental shift of how the world views manufacturing centres.

“What encourages us is to see the enthusiasm of a number of our partners who have shown eagerness to start their projects in Oxagon These pioneers of change will establish factories, developed with the latest technologies in artificial intelligence, to achieve a significant leap for this era into the Fourth Industrial Revolution,” Al Nasr.

World’s first fully automated port and integrated logistic hub

Oxagon is being touted as the world first fully automated port and integrated logistics hub that will make use of robots and AI.

The adoption of advanced technologies  of  IoT, human-machine fusion, artificial and predictive intelligence and robotics will be coupled to a network of fully automated distribution centres and autonomous last-mile delivery assets to drive Neom’s ambitions of creating a seamless integrated, intelligent and efficient supply chain.

Furthermore, the port, logistics and rail delivery facility will be unified, providing world-class productivity levels with net-zero carbon emissions, setting global benchmarks in the adoption of technology and environmental sustainability.

The agile and integrated physical and digital supply chain and logistics system will allow for real-time planning, resulting in secure on-time delivery, efficiency and cost-effectiveness for industry partners.

Speaking to Arabian Business, Al-Nasr gave a definitive timeline for Oxagon’s construction: “We expect the onshore development at Oxagon to be completed by 2030. The beginning of the offshore development will be very much underway by that point as well.

“The containerisation of our port is likely to begin in 2022 when we will also be building our advanced integrated port logistics facilities. We aim to have our logistics solutions facilities in place by 2025 as we continue to progress and deploy new technologies such as state-of-the-art high-speed rail and aerial taxis.”

The city’s first residents are expected to move in at the end of 2023,

A net-zero city powered by 100% renewable energy

Oxagon’s octagonal shape is designed to minimise impact to the environment while providing optimal land use. It will be a net-zero city with all industries within its fold to be powered  by renewable energy.

The city has identified seven key sectors for industrial development: sustainable energy; autonomous mobility; water innovation; sustainable food production; health and well-being; modern construction; technology and digital manufacturing,

Oxagon aims to be a showcase of how manufacturing can co-exist with nature and respect the environment, especially the delicate ecosystem of coastal areas.

“We will demonstrate how industry and logistics, powered by 100% clean energy, can redefine manufacturing processes with advanced technology, innovation and the clean use of land and sea areas. What we are doing here in Oxagon is a testament that exceptional liveability and industrial advancement are not mutually exclusive,” Al-Nasr told Arabian Business.

Oxagon expects to welcome its first manufacturing tenants at the beginning of 2022.

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Hence, the flexibility to offer multiple mobility options through a single provider is crucial. In addition,  the need to improve commuting efficiency and effective orchestration of fleets will require the deployment of high-impact technologies such as artificial intelligence (AI)-driven platforms, vehicle-to-everything (V2X) capabilities, blockchain, 5G, and edge computing.

Technology is driving the evolution of the mobility ecosystem and services, enabling on-demand services and integrated solutions. Digital urban mobility management solutions will be key to cities becoming more proactive, smart and liveable.

"Every stakeholder in the value chain of technology providers, automakers, mobility service providers, and cities aim to ensure effective mobility management of passengers and goods. They are increasingly resorting to partnerships/acquisitions to build capabilities and be prepared for the future of mobility," noted Albert Geraldine Priya, program manager - mobility, at Frost & Sullivan. "Public-private partnerships are expected to boost the uptake of smart city initiatives. Open data policies and policy support will catalyse this trend, especially for MaaS and marketplace solutions."

Priya added: "There is likely to be a shift from hardware to software platforms, such as moving from fixed road sensors to floating sensors in cars or cell phones. Differentiated, scalable, and usage-based fee models will require coordinated demand management. The focus on user orientation and convenience will promote free-flow traffic systems, end-user services, and converging technologies."

Urban mobility services providers can expand in a highly dynamic marketplace by making the most of the opportunities offered in the following areas:

• Extensive Collaborations to Develop Capabilities for Future Urban Mobility Management: Collaborations among traditional and new mobility technology providers can result in new business models and Mobility as a Service (MaaS) on a larger scale.
• Advanced Technology and Intelligent Solutions Vital for Smart Mobility of the Future: Solution providers from the information and communications technology (ICT) and automotive sectors should focus on deeper collaborations with various stakeholders, including city governments, to develop a scalable and robust smart city urban mobility management platform that can converge, process, and supply intelligence for seamless operations.
• Urban Mobility Management Systems are Crucial for Future Mobility Operating Systems: With urban mobility management systems central to the design of cities in the future, cities should transition to smart mobility operating systems that can provide a view of the entire city on a single screen.

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“To have sustainable traction in intelligent and innovative technologies development, we need an integrated ecosystem approach and strong partnership with stakeholders in various sectors and industries,” said Denis Yip, CEO of ASTRI. “Our  continuing collaboration with CITIC Telecom CPC will lead to a meaningful exchange of innovative R&D, technologies, knowledge, and insights, which will ultimately increase operational efficiencies of the industries, uplift user experience, and create value to the community.”

“We are enthusiastic about advancing AI-AR technologies with ASTRI and leveraging collaborations and sound technological exchanges to pursue innovative and practical applications,” said Esmond Li, CEO, CITIC Telecom CPC.

The two organisations started their partnership in developing integrated AI and AR (augmented reality) solutions in June 2019, which led to launch of an AR Remote Hand Solution in September the following year.

Boosting field service productivity by up to 50%, the enhanced AR-based vision allowed field engineers to access vital information at data centres and enabled seamless collaboration between frontline and back-end teams to complete maintenance tasks. The solution also demonstrated how companies could facilitate remote work strategies during the pandemic using AR technologies.

Taking AR glasses to new heights

In Phase 2, ASTRI and CITIC Telecom CPC will be working to build innovative new features into the heads-up display of AR glasses.

ASTRI will provide the software platform and customisation, while CITIC Telecom CPC’s team will build an innovative Machine Learning (ML) model in order to integrate virtual, big data, AI, and physical data into the AR device.

The key features include:

• Data Visualisation – Computer vision techniques and machine-learning algorithms enhanced data integration will provide the remote workforce with 2D and 3D diagrams for better data visualisation. Users can use AR glasses to detect, identify, locate, and track objects positioning and project holograms of technical manuals, analytical figures, or even instructions onto the heads-up display to analyse trends or issues for quicker response.
• Cognitive Object Recognition – The AI-AR integrated service will use Cognitive Object Recognition System (CORS), which runs using CITIC Telecom CPC’s algorithm and solution to improve object mapping accuracy. Using AR glasses, users can easily define the correlation between different objects. The AR glasses can further improve workplace safety by projecting the physical (path) and logical relations onto the reality in the form of digital maps, 3D models and virtual information.
• Middleware Enhancement – Both organisations will develop middleware for AR glasses, empowering customers to work with different AR headsets such as HoloLens and Android-based headsets.

The two organisations expect the AR glasses with enhanced AI/AR capabilities will bring more business values in a range of industrial applications, such as:

• AI-AR Remote Hands for Seamless Collaboration From a Distance
• Streamlining maintenance and inspection for Utilities – The AI-AR integrated service will provide field workers with better computer vision capabilities. Field users can access manuals and analysed data or graphs for maintenance using the AR glasses while receiving immediate alerts of any wrong steps. The 5G-enabled cloud connectivity can enable supervisors to guide field users during installation and maintenance verbally.  
• Computer Vision and Cognitive Analytics Solutions for Better Decision Making
• Business Operations planning (e.g., Supply Chain Management) – The integrated service can provide workers with extra information during operations. The frontline staff can use data visualizations and object mapping to identify goods quickly and accurately for loading and unloading.
• Predictive Customer Experience for Maximising Customer Value
• Enhancing customer services experience in all industries – AI and AR allow companies to use predictive and prescriptive data to understand what customers want before they know themselves, delivering exceptional customer experiences.

“We are confident that this collaboration will result in a win-win outcome by creating viable commercial applications that benefit different industries,” said Yip.

Daniel Kwong, CIIO of CITIC Telecom CPC said: “We believe that our strong partnership with ASTRI, together with the development of new technologies, such as AI, AR, blockchain, 5G, IoT and cloud, will ensure that we will continue to find innovative and intelligent ways of helping enterprises to reap the benefits of digital transformation.”

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Under the agreement, Blue Prism will build software as a service (SaaS) offerings on AWS while working closely with the AWS Intelligent Automation team to increase the intelligence and accessibility of Blue Prism’s digital robots. This will allow the digital robots to benefit from the broad and deep capabilities available from the Amazon Machine Learning (Amazon ML) stack.

Blue Prism will speed up its digital robots’ integrations with AWS applications and services, including AWS’s omnichannel cloud contact centre, Amazon Connect; AWS productivity applications, such as Amazon Chime; and AWS artificial intelligence and Amazon ML services, such as Amazon Lex and Amazon Transcribe. Both organisations will align to create workloads supporting industry-specific use cases that drive proven customer business benefits.

“It’s time for businesses to recognise the potential of their workforce through intelligent automation, amid  tactical digital transformation efforts. Our combined offerings provide  a more holistic solution for productivity as businesses continue to transform and expand,” said Dan Ternes, chief technology officer, APAC, Blue Prism.

The increased availability of Blue Prism intelligent automation solutions on the cloud comes at an important time for customers across all sectors. Today, 92% of decision makers see robotic process automation (RPA) as important for driving digital transformation, and 83% agree that RPA and/or automation is essential for their business to remain competitive.

On demand intelligent automation solution

The Blue Prism On Demand offering, available in AWS Marketplace in 2022, will provide one of the industry’s first on-demand intelligent automation solutions portfolios available through a consumption-based pricing model. This new offering will enable companies to assess their intelligent automation needs, unlock value and ROI across business processes, and scale across the enterprise easier than ever before.

For example, Sysco, a global foodservice distribution company, is now able to automate the processing of inbound customer orders received by digital fax by using Amazon Textract, which helps automatically extract printed text, handwriting, and data from any document. It’s been so effective at removing order entry errors that Sysco’s staff no longer have to use overtime to correct them. Sysco’s automation program is realising benefits like this across the business, with 60 digital robots that collectively process 6.2 million transactions and return more than 250,000 work hours to the business.

“As an AWS and Blue Prism customer, our cloud strategy was a critical lynchpin to help scale our automation initiatives. Automation had become a critical need almost overnight and in every area of our enterprise. It was time for us to put what we had planned and theorised into action,” said Kim Meredith, business technology lead, CoE at Sysco.

Meanwhile, Terry Walby, chief executive for Blue Prism Ventures, said:  “The collaboration with AWS will allow us to further enhance our ability to deliver intelligent automation solutions to organisations around the world seamlessly, on demand and at large or international scale.”

“This relationship will give customers even greater access to intelligent automation solutions that can accelerate their business transformation goals,” said Madhu Raman, Worldwide Head of Intelligent Automation at AWS. “Joint customers will have an extensive portfolio of real-world automation capabilities at their fingertips, including business process improvements. Customers will also benefit from more agile and flexible cloud-based contact centre solutions that combine our technologies.”

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The new company  will leverage Johnson Electric's vast knowledge and experience in manufacturing processes and Cortica's unique Autonomous AI Technology to revolutionise the visual inspection market.

Automating quality assurance in manufacturing through Autonomous AI will drive flawless quality and production while enabling simple and fast setup on the production line

"With the power of Cortica's Autonomous AI technology, and JE's vast knowledge of the market, Lean AI will deliver a product that reduces the cost of human error when it comes to quality inspection in manufacturing and address the vulnerabilities in the current market," said Karina Odinaev, CEO of Lean AI.

Austin Wang, senior vice president of Johnson Electric, said they are fully aware of the fundamental challenges in deploying an AI-based quality assurance software in the production environment – especially in terms of speed of deployment and reliability over time.

“However, Cortica’s autonomous AI technology can address a lot of these major headaches and allow for much faster and broader adoption.”

The Israel-based Cortica Group has developed Autonomous AI that simulates the natural processes of the mammal cortex. Its unsupervised approach to learning mimics the way the brain processes information: enabling machines to learn, collaborate and interact with the world without human input.

Wang also pointed out that Johnson Electric's deep experience in a wide range of manufacturing processes offers a unique platform for developing an AI-based quality assurance software for commercial use.

“The joint venture is also opening a new avenue for Johnson Electric to develop and market software offerings. It is therefore both a technological as well as business model innovation for us. There are also opportunities to apply the technology in predictive quality and expert systems as well. This is the second investment of Johnson Electric in Israeli technology, and we will continue to assess such relevant opportunities,” Wang said.

Seizing the opportunity in the global machine market

The newly-formed Lean AI hopes to tap into the growing global machine vision market, currently valued at US$11 billion, but is predicted to reach US$15.5 billion by 2026.

As these numbers continue to grow and AI technology advances, the opportunity for machine vision solutions to positively aid in manufacturers' earning potential with a reduction in defects gives way for a new system that will fundamentally change the industry's approach to quality assurance.

Today, supervised Deep Learning-Based Quality Assurance Systems can take weeks, up to months, to deploy. The existing systems are reliant on a data scientist or AI experts and require large manually tagged training sets with thousands of defect image examples. Requiring constant maintenance and re-training for the slightest variations, the system is unable to adapt to defects, new products, and new cameras.

Lean AI touts its technology surpasses existing challenges of prevalent supervised Deep Learning-Based Quality Assurance Systems with the power of unsupervised learning to process information within a fraction of a second, using unlabelled data, applies predictive quality assurance, and compiles data that increases the speed of deployment and scaling. As an open platform agnostic to camera, defect type and product, Lean AI can collaborate with any integrators, OEMs, and manufacturers of automation solutions.

"Cortica has developed self-learning AI that is fundamentally different from traditional deep learning systems. Autonomous AI Technology operates like a human brain - it's not a fixed system; instead, it continuously adapts itself to various scenarios and learns online in real-time. Its technology requires far less computing power, can be deployed at a fraction of the cost, and provides far superior performance outcomes," said Igal Raichelgauz, founder and chairman of Cortica. "Our technology is robust and generic and applicable within a multitude of signal domains such as visual, audio, time series and other domains; visual inspection is only the beginning. Autonomous AI technology is quickly becoming the benchmark for the industry."

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“While we seek to expand our maritime industry, we have not forgotten our commitment to sustainable development,” said Hong Kong Chief Executive Carrie Lam. “We have already announced the target for Hong Kong to achieve carbon neutrality before 2050. As part of our decarbonisation effort, we encourage industry players to adopt more sustainable shipping initiatives. As you all know, Hong Kong was the first city in Asia to mandate a fuel switching requirement for ocean-going vessels.”

In her speech at the 11th edition of the Asian Logistics, Maritime & Aviation Conference (ALMAC) held in Hong Kong last week, Lam also reiterated the need to use innovative technologies, even as the city continues to enhance maritime services – including  ship finance, marine insurance, maritime legal and arbitration services, ship agency and management and shipbroking – through the provision of economic incentives such as tax concessions and manpower training.

With over 150 years of maritime heritage and robust international connectivity, Hong Kong has one of the top 10 container ports in the world, as well as a transhipment hub in the region. There are some 280 weekly container vessel sailings, connecting to over 600 destinations worldwide.

At the same ALMAC event, Frank Chan, Hong Kong’s secretary for transport and housing, echoed the importance adapting innovative technologies to sustain the city’s leading position as a global logistics, maritime and aviation hub.

 "The future of modern logistics is going to be smart and technology-driven. Automation, AI, big data and digitalisation are instrumental," said Chan, adding that to  help achieve this strategic goal, the Hong Kong government has up a HK$300 million funding scheme to encourage logistics service providers in applying technological solutions to enhance productivity.

COVID-19 and hitting the reset button

Panellists at the “New trade order and evolving intermodal networks in the Asia-Pacific” conference session noted that  current pandemic has amplified seismic shifts in the supply chain where it is becoming more regional than global, a trend particularly noticeable in the Asia Pacific.

Kelvin Leung, CEO of DHL Global Forwarding Asia Pacific, said that a lot of issues, such as port congestion and traffic congestion, were happening even before the pandemic. Even before COVID-19, many industries and companies had been rethinking how to position their supply chain, sourcing models, manufacturing models, and so forth, focusing on enhancing the transparency of their supply chain and the resilience of the supply chain model.

“Digitalisation is going to change the way we operate going forward, and ESG is becoming more important because our industry creates a lot of emissions, and we have to address that,” said Leung.

Raymond Fung, director of trades at Orient Overseas Container Line, said businesses have needed to increase dialogue with each and every customer and have also had to cater for certain SMEs they previously wouldn’t have dealt with over the past couple of years. As service providers, he said shipping lines must live with what the customer wants and adjust accordingly.

“For example, we have been using big-bulk vessels, as long as they are seaworthy, to run short-distance trips for certain customers,” he said. With the growth of e-commerce and the use of artificial intelligence by some carriers and customers, he hoped it would be easier to forecast demand, with shipping lines able to come up with different sizes of vessels and different routings to better cater for customers’ requirements.

According to Joseph Phi, group CEO Li & Fung, supply chain has seized to be “invisible” to shippers, but now stands front and centre.

“We have surging demand, rising transportation costs, manufacturing delays, port congestion, labour shortages, trade disputes, trade policies, inflation, and so on, so the whole supply chain is facing the perfect storm,” he said at the conference’s

“The more progressive companies are doing things to create value in their supply chains. The overarching theme they have adopted is they have hit the reset button, concluding that the pandemic is a perfect occasion to reset their strategies and refresh the way they execute their strategies, so they are trying their very best to make their supply chains more resilient and agile,” Phi added.

The future of smart air cargo

Meanwhile, the same supply chain disruptions are plaguing air cargo segment of the logistics industry amid the pandemic, even while air cargo volume has been significantly up and expected to comprise  nearly a third of the airline operating revenues.

To get transparency across their operations, industry players have been deploying technologies to find their way across their supply chain years before the pandemic hit.

According to Victor Mok, chairman and CEO - Asset Service Platform at GLP China, Chinese logistics providers have implemented digital solutions five to 10 years ago to enhance the digital transparency and safety of cargo movements.

Cross-border e-commerce has greatly accelerated progress in this area, he said.

“Digitalisation is a big word, but it doesn't mean just moving things like processes from paper to online platforms. That is only the first small step,” Mok added. “The key is how you optimise the processes, using technology and data to improve the processes and therefore efficiency and transparency, to make better decisions than in the past.”

Mark Slade, managing director of DHL Global Forwarding Hong Kong & Macau noted that up to 60% of supply chain disruptions come not from direct suppliers, but further upstream from second- and third-tier suppliers.

“We at DHL use an analytical tool to allow companies to get deeper into the supply chain and identify risks with suppliers that are actually two or three layers removed from their operations,” said Slade.

The annual ALMAC is jointly organised by the Government of the Hong Kong Special Administrative Region and the Hong Kong Trade Development Council. It is a is a flagship event of Hong Kong Maritime Week. This year’s conference had more than 11,200 viewers from some 60 countries and regions. They included participants from Hong Kong, Mainland China, newcomers from Mexico, Nigeria, Romania and more, highlighting how the event offered networking opportunities spanning the globe.

A newly added physical and virtual exhibition showcased different logistics technologies, including 5G technology for warehouse management, smart logistics solutions, international payment solutions and the latest smart port developments, connecting participants with the best business solutions

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“You need to integrate data from different sources into one holistic data platform. You also need an open and agnostic data pipeline that forwards your data from the devices to your platform,” said Philipp Redlinger, IoT architect at German-based System Vertrieb Alexander (SVA). “The pipeline needs to be able to integrate data from various sources in different formats. So, it has to be agnostic pipeline that you can expand for other protocols as well. And the platform has to be open on both sides in terms of ingestion as well as output. It must be capable of sharing data and insights with end-users via desktops and mobile clients. And, of course, it needs to be able to connect to other systems via a clearly structured API.”

“In order to enable interoperability and data-driven applications and end-to-end scenarios, such data pipeline in combination with an open platform is crucial,” he stressed.

Redlinger and his SVA colleague, IoT engineer Patrick Nieto Castro, were co-presenters during the  “From Sensor To Cloud” session at last week’s .conf21 event organised by Splunk.

Redlinger added that the data pipeline of the IoT architecture should not only serve as “a simple data funnel that simply ingest all data” that cross its path.

“It should be capable of performing data processing such as transforming and filtering your data in order to increase the quality of your data at an early stage. And by turning raw data to refine data that is optimally prepared for your analytical applications, you will enable them to provide high-value insights for your business cases.”

Consequences of the silo issue

Gartner estimates that there will be 25 billion connected devices by the end of the year. And companies that have long ago deployed devices in various areas of their operations are now connecting them into an IIoT network with the hope mining the data in these devices to gain business insights to deliver new digital services.

According to Redlinger, isolated systems  and fragmented solutions that now exist within organisations create a silo problem that prevent them from getting the total picture ,

“Due to these fragmented solutions, there are a lot of inefficiencies, and the systems vendor ultimately decides what happens to your data. You do not have sovereignty over your data.   Because of this, it is very difficult to correlate data from sources and you cannot perform root cause analysis of multiple workstations, and you are missing the global perspective.”

The challenge of collecting IoT data for analysis has real consequences in terms of inefficiencies, outages and wastage, Redlinger pointed out.

“They are not just theoretical problems of missed opportunities due to the sophisticated use cases that you cannot implement. And there are also real money that is being lost basically every minute in countless ways.”

Citing a recent survey, he noted that people lost 30 minutes to two hours per working shift looking for the right data. On the positive side, a utility company in the US was able to cut the amount of outage minutes by 43.5% and reduce the cost by US$40 million a year after it dissolved legacy information silos and consolidate them in one holistic information platform.

Some ground rules before building an IoT architecture

Redlinger urged companies be realistic about technology, pointing out that architectures oftentimes are being built just for the sake of fancy technologies.

“Try to avoid this. Keep your strategies and business cases constantly aligned to your architecture,” he said. “Start with an MVP approach – start with minimum viable products. Keep it flexible and expandable so you can build on that later on.”

He also advised  companies to accept that their requirements will change as the project progresses.

“Even if you try to get a perfect information upfront, your requirements will change by an estimated 1% per month. That is a rule of thumb. So even if you would know everything at the beginning, after one month of doing the project, your requirements would have already been different, so you need to constantly readjust.”

He stressed that there is no silver bullet, so build on open standards and consider hybrid scenarios. “And keep single parts of your pipeline exchangeable so you can make adjustments later on.”

Needless to say, do not compromise on security, Redlinger said.

“There are many strong mechanisms nowadays such as network segmentation, strong authentication mechanism, encryption and analytics-driven security – which is a strong one at Splunk.”

Connecting to the cloud

According to Redlinger, the quick start  scenario for designing an IoT data pipeline is a direct integration with Splunk Cloud. And these can be done in several ways as shown below:

He enumerated the different components and protocols that are the building blocks: LP-WAN for connectivity when Wi-Fi and LTE is not an option; an edge hardware, which is typically an IoT gateway, but can be anything up to scalable edge-as-a-service platforms; and various legacy and proprietary machine protocols that need to be translated by middleware, which runs on edge Hardware or in the cloud or data centre.

He also listed the new protocols for the open IoT architecture.

“The OPC UA is the silver lining in the horizon because it is the first widely accepted open standard for machine interoperability, supported by most modern industrial equipment and software. So, keep your architecture somewhat compatible OPC UA as possible.

“And at the backend, we have the MQTT protocol, which is the open & lightweight Pub/Sub-Messaging Protocol. It is very useful in scenarios where there are a high number of connected devices or uneven network coverage – i.e., connected cars.

“And then we have the Apache Kafka, which is a fully blown distributed streaming platform. And that is very helpful if you need a central data hub for various applications and backend systems, and if you want to perform heavy workloads on your streaming data.”

Meanwhile, SVA IoT engineer Patrick Nieto Castro, the first step in building the IoT data pipeline is connecting all the actual devices.

“You have to select appropriate sensors for the measurement of your physical data of interest. And already think to exhaust any possibility of edge computing,” he said.

Castro advise that companies should ensure that they clean their data and prepare their data as early as possible before sending them any further.

“Believe me, any data scientist you are possibly working with will surely be thankful if filter out any nulled values, any non-numeric values or any crappy data before handing it to them.”

Castro shared a real-life use case where SVA worked to create the IoT data pipeline for a company that runs electric vehicle charging stations in Germany.

“For the final architecture, I will try to put some name in the architectural building blocks. We use gateways of Insys Microelectronics, one of our partners for connectivity and edge computing, at each production site. The HiveMQ, enterprise MQTT broker as a reliable and scalable data turntable. Also, my colleagues and I developed our very own extension for sending telemetry data from HiveMQ MQTT broker to Splunk Cloud where the sensor data is connected and analysed.”

Onsite at each EV charging station, Castro gave a glimpse of what it takes to physically build the IoT data pipeline.

“We have to convert current and voltage to https. First, we connect our power consumer to a power relay, which is done via an electric wiring. This is an interesting step because of the high voltage. Next, we connect the power relay to a power meter, the sensor that effectively converts  current and voltage into measurement. You all know this type of device because it is used to collect the electricity bill at your home by your local electricity supplier.

“And now we connect the power meter to an energy gateway by one of our partners.  Insys Microelectronics is one of the market leaders in the energy supply markets. They make it possible to encode the data of power meters as serial signals. And we connect the central gateway to HiveMQ, an enterprise MQTT broker that converts digital signals into telemetry encrypted data.  The central gateway has an internet connection and sends the telemetry data via MQTT using our very own extension to send telemetry data into Splunk Cloud.”

Benefits of the holistic approach to data and analytics

Redlinger said that once a company’s IIoT use case has matured enough and  having a good idea of their  analytical algorithms, then you can start deploying simplified versions of them right away on their edge devices.

“You have some kind of limited compute power that might be enough to run the simpler algorithms and then you can start generating insights right from the beginning where the data is generated.  And you can have a very tight feedback loop. So, if one of your algorithms detect an error in your production system, it can halt the production and notify a shop floor operations person in order to fix the error. You have a very fast reaction time with this, and you can also use a lot of pre-processing at the edge that way,” Redlinger said.

Redlinger explained why Splunk is an ideal choice for building an IoT data pipeline: “Splunk has very strong self-service analytics capabilities. It is easy for normal users to learn how to run communities, how to build dashboards, how to explore data. And by hierarchical segmentation of dashboards, you can build apps and dashboards for management reports down to the operational level of having an overview for shop co-operators.

“And you have machine learning capabilities: you have the machine learning toolkit, the deep learning toolkit. You can integrate custom codes for custom app, so you can have all the data-driven analytics capabilities that you need. And in the cloud, it is fast and easy to start. You have low capital expenditure – an upfront investment but you can really start your journey very quickly – see it has proven value, then quickly scale it up and down if necessary.

“And it is also very easy as the data is already globally available in the cloud to share it with other parties and other systems to create third-party services as well.

Meanwhile, Castro identified benefits of adopting a holistic approach to data and analytics in IIoT deployments.

“The digital twins accelerate  your business as never experienced before by increasing transparency of the day to day actions. Instead of sending over technicians to read out measurements, there is constant monitoring of device performance and conditions.

“We have the advantage of AIOps that train models to look for feature combinations which best explain your data. And we have predictive maintenance. You can forecast anomalies, machinery conditions, which effectively decreases unexpected downtime and increases the overall performance.”

The post Building an IoT data pipeline appeared first on FutureIoT.

The alliance allowed the two companies to combine their IoT capabilities – Mindtree Nxt IoT service line and the IoT-geared ServiceNow Connected Operations platform – to help companies in industry sectors such as manufacturing and consumer goods achieve smarter operations and improve their decision-making by tapping hidden insights  in their IoT data.

"The true transformative potential of data can be realised only by using it effectively," said Alex Nicholas, vice president and head of ServiceNow Business at Mindtree. "Siloed data and disconnected systems can undermine the best of IoT programs. The capabilities of Mindtree NxT alongside ServiceNow and their dedicated Connected Operations team position us well to help enterprises better manage critical infrastructure, deliver superior customer experiences, and drive customer loyalty."

Mindtree, a technology consulting and services company, applies its deep domain knowledge to more than 260 enterprise client engagements to break down silos, make sense of digital complexity and bring new initiatives to market faster. The company enables IT to move at the speed of business, leveraging emerging technologies and the efficiencies of “Continuous Delivery” to spur business innovation.

Operating in 24 countries across the world, its geographic footprint in Asia Pacific include presence in Auckland, Beijing, Kuala Lumpur, Melbourne, Shanghai, Singapore, Sydney and Tokyo, as well as several cities in India.

Turning data into actionable insights

Manufacturing and consumer goods companies are increasingly looking to make better use of the data generated through multiple platforms and legacy operational technology (OT) systems.

This means working around operational and data silos between OT and IT, a lack of common processes and tools in floor systems, and an inability to bring all data into a single system of record. Through Mindtree's solutions, these companies will be able to gain greater visibility across the enterprise; mitigate risk; and, reduce cost. They can also harness a single source of truth for collaborative decision-making and leverage advanced analytics, data insights, simulation and modelling for better evaluation of their value chains.

"Across industries, businesses realise the need for digital workflows to deliver greater operational efficiencies and better customer outcomes," said Jonathan Sparks, vice president of IoT and operations products at ServiceNow. "Together with Mindtree, we're helping move customers in manufacturing and consumer goods beyond dashboards to automate issue resolution with IoT. Combining Mindtree's powerful IoT, AI and Machine Learning capabilities with ServiceNow's leading workflow platform will improve decision-making and drive smart operations while helping customers realise new business outcomes based on business-relevant insights."

By connecting IoT data with digital workflows, ServiceNow Connected Operations enables organisations to realise the full value of their IoT investments, help increase customer satisfaction, and access new business models. Together with Mindtree driving actionable and industry-specific insights, these solutions will allow customers to break down data silos, proactively resolve issues, and evolve collaboration between customers, operations, customer service, and field service.

Indeed, with its industry partner solutions,  ServiceNow is able to extend its capabilities to deliver industry-specific applications and services that are tailored to customers' unique digital transformation needs.

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This announcement by the Taiwan-based company coincided with the unveiling of its three electric vehicle (EV) prototypes - a sedan, an SUV and a bus -in a move to diversify into the automotive industry and a goal to become a major player in the global EV market.

The planned R&D centre will work on software innovations around smart gateway, smart cockpit, smart autonomous driving and other software applications.

“As the electric vehicle business develops and matures, Hon Hai will look to launch its open platform and other software. The group will also introduce enhancements on the software platform over time,” said Foxconn chairman Young Liu. Foxconn is formally known as Hon Hai Technology Group.

Foxconn unveiled first three EV prototypes  and the planned R&D centre to support software development for its smart electric car ecosystem  early this week during an event that marked the birthday of company founder Terry Gou.

The prototype vehicles were made by Foxtron,  a joint venture established last year between Foxconn and Taiwanese car manufacturer Yulon Motor.

“With the determination and support from Hon Hai, Foxtron will play a key role in the transformation of the automobile industry, leading the advancement of the automobile production value chain in Taiwan,” said Lilian Yen Chen, CEO, Yulon Motor.

The SUV is set to hit the Taiwan market in 2023 and is expected to be  sold under one of Yulon's brands. The sedan, which was jointly developed with Italian design firm Pininfarina, are planned to be sold outside the island nation by a yet-to be-named carmaker in the coming years.

The bus will carry a Foxtron badge and is scheduled to start running in several cities in southern Taiwan next year in a partnership with a local transportation service provider.

“Hon Hai is ready and no longer the new kid in town,” said Foxconn’s Liu.

Meanwhile, Chi-Sen Tso, vice chairman of Foxtron, expressed hope that the Foxconn’s EV business will worth one trillion Taiwanese dollar (US$35 billion) in five years’ time.

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“The combination of AI, machine learning (ML), and AR is an incredibly potent one,” says Eric Abbruzzese, augmented and virtual reality research director at ABI Research. “At the core, the capabilities of augmented reality get stronger with more data available. This data comes from location data, sensor data, environmental dynamics, and integrated systems such as Internet of Things (IoT). AR can also serve as a data collection enabler for these data types. Weaving AI into these areas brings high value and often critical AR capabilities to market.”

The need for visual and spatial data for AR often relies on AI enabling technologies to capture, process, and contextualise that data in an actionable way. As a result, these two markets continue to overlap and create substantial opportunity.

According to ABI Research, while machine vision isn’t inherently required for AR—in the case of assisted reality hardware and applications—it is increasingly becoming a necessity for most use cases. Machine vision enabling SLAM tracking allows for precise user tracking in space and can also capture spatial data for later use.

ABI Research expects nearly 20 million shipments of AR smart glasses with local on-device AI chipsets in 2026, which accounts for 70% of total smart glasses shipments in that year. Local processing of AI is most common today, but processing location is increasingly moving to the cloud for some AI processing types. For instance, SLAM tracking can stay on-device for reliability and low latency, but semantic labelling can sit on the cloud, sacrificing latency in a non-sensitive latency scenario for that type of data. Cloud and hybrid compute scenarios allow for the best AI processing performance versus device performance and battery life, flexibility depending on application, and environment.

Many companies in the AR space have been leveraging AI in numerous ways for years, and this usage is growing both in number of companies and scope of usage. At the hardware level, Qualcomm has baked in AI enhancements specifically for AR and VR—to improve tracking accuracy and performance, for instance—in their XR chipset line. NVIDIA is leveraging AI in their CloudXR product as well as Omniverse, which most recently announced automated simulation and content creation elements using AI. Enterprise players like PTC and Teamviewer use machine vision for device tracking, as well as for backend processing, analytics, predictive processes, and more.

These elements sum up to a valuable enabling technology that is harmonious with the entire augmented reality value chain.

“Point to a use case, application, service, or vertical, and AI is already being leveraged and its role will evolve substantially over the next 5 to 10 years. The value adds commonly cited for augmented reality, including increased worker efficiency and safety as well as novel collaboration and remote enablement capabilities, are enhanced with AI. More accurate and predictable tracking and data gathering, automated and targeted content delivery, newly uncovered data and usage trends all contribute,” concludes Abbruzzese.

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There is demand for contactless, robust and privacy-preserving devices for detecting temperature with accuracy and wide coverage to safeguard against public health emergencies.  According to a recent research report, the global thermal imaging market is expected to reach USD 4.6 billion by 2025, growing at a CAGR of 6.2%1.

The AI thermal sensing solution powered by STMicroelectronics’ X-CUBE AI optimises bill-of-materials and simplifies hardware and software integration, making it a good choice to deploy for temperature-screening devices and a wide variety of other consumer-grade and healthcare applications.

"Many product engineers find it challenging to deploy AI models in a cost-efficient and robust way to a wide range of consumer-grade, healthcare, and IoT edge devices.  This AI-enhanced solution with STM32 Arm Cortex-M-based microcontrollers offers a pricing advantage and delivers better energy efficiency, making it easier to bring to market the kind of intelligent devices that help individuals and communities stay safe," said Jacky Wan, Arrow's vice president of engineering for APAC.

Arrow's AI-powered thermal sensing solution can achieve a quick and accurate temperature screening, with multiple individuals screened simultaneously.  The integrated solution is comprised of four blocks:

• A STMicroelectronics Time-of-Flight (ToF) sensor which allows absolute distance measurement whatever the target colour and reflectance, providing accurate ranging up to 400 cm and speed up to 60 Hz
• A STMicroelectronics digital ambient thermal sensor which detects ambient temperature and dynamically compensates for differences to allow complex measurements at high speed
• A longwave infrared thermal image sensor developed and fabricated by Meridian Innovation, a Hong Kong-based pioneering developer of advanced CMOS technology
• STMicroelectronics' dual-core M7 and M4 MCU running at 480Mhz which acts as the main processor of the system

A thermal image noise reduction process making use of AI deep learning is deployed in the system.  This special denoise process runs on a convolutional neural network (CNN). With the STMicroelectronics' AI expansion pack - STM32Cube.AI, the deep-learning algorithm can be exported and executed on STM32 Arm Cortex-M-based microcontrollers.  The solution can detect target object distance and human presence.  Images can be displayed in heat map or RGB format.

To provide the best performance, an ultra-low noise LDO with a noise voltage of only 6 micro volt RMS is used for the power supplier of all the sensors. All three sensor blocks are connected to the main processor using an I2C and SPI bus, which will handle processing and calculation of the environmental data collected by the sensors to increase system accuracy.

Adding the wireless connectivity feature for transmitting data to the gateway/cloud, the integrated solution can incorporate Murata type 1YN, a small and high-performance module with Single-Band 2.4GHz Wi-Fi 802.11n and Bluetooth 5.2.

Matteo Maravita, head of APAC AI Competence Centre of STMicroelectronics, said the Arrow team has done a great job in developing this integrated solution.

“This solution takes full advantage of AI techniques on STMicroelectronics microcontrollers and sensors thanks to STM32Cube.AI, a complete development ecosystem from STMicroelectronics that allows easy implementation of complex AI models onto STMicroelectronics products,” Maravita said.

“The integrated solution allows product engineers to rapidly integrate AI and thermal-sensing technology and accelerate the product development cycle of smart, reliable and low-cost temperature-sensing devices, addressing the consumer-grade and healthcare market needs," he added.

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