The Future of Retail? Supply Chain Visibility

When you’re in retail, the supply chain can make or break your business. While waiting on shipments can hinder sales, it’s even more frustrating when you can’t locate what’s already in stock. Not only does this represent lost revenue; it wastes human resources tracking misplaced items and negatively impacts the customer experience.

Fortunately, the fix is straightforward. Retailers can implement edge-to-cloud technology that provides visibility across the product lifecycle, streamlining operations and improving customer-focused strategies. One solution is ytemfrom Mojix, a leader in item-level intelligence solutions—connecting a system of sensors to a cloud-based computing platform.

The company has deep domain expertise in technologies such as RFID, NFC, and print-based marking systems. Mojix builds business intelligence from event-triggered actions tracking billions of unique identities, following item lifecycles from source to shelf.

Edge-to-cloud technology can transform supply chain and inventory management. Retailers can know exactly how much stock they have and where it is, for greater confidence. “You have what is called a unified inventory,” says Helene de Lailhacar, Marketing Director for Mojix. “You can therefore engage into eCommerce with more freedom, efficiency, and accuracy.”

In addition to accuracy and transparency, the benefits of #edge intelligence also include brand protection through traceability. @MojixInc via @insightdottech

Retail Analytics Automates Supply Chain Management

The results can be dramatic. For example, a leading athletic gear retailer implemented the Mojix ytem SaaS platform to improve its inventory accuracy. Before deploying the system, the company contracted an external supplier to manually count items using a barcode scanner. It took 10 people at least eight hours per store. The cumbersome and costly process was completed three times a year, and resulted in an accuracy of only 75%.

After installing ytem, the company needed just two people to perform stock counts, reducing the time required from eight hours to just two hours, while increasing the counting speed from 8.3 to 125 items per minute. Because each item has a unique code, the risk of human error, such as scanning something twice, was eliminated. Inventory accuracy reached 99% and productivity grew by an astonishing 2,000%. Plus, the company was able to reduce safety stock while increasing revenue by 10%.

“When it says on a retailer’s website they have zero items left, technically they still have three or four elements in stock,” says de Lailhacar. “Retailers will not go below this because they can risk being out of inventory due to time lapses in information. That would be horrible for brand image and represent loss of business. Once accuracy is improved, they can reduce that safety stock.”

Gathering Retail Data with Edge Technology

To create ytem for retail, Mojix partnered with Zebra, manufacturer of data collection equipment, such as RFID and barcode scanners (Video 1). “It’s a marriage made in heaven because we need their data capture to get the information, and they need a SaaS platform to make their data capture useful,” says de Lailhacar.

Video 1. Edge technology and analytics help retailers track inventory movement through their business operations for better accuracy and visibility. (Source: Mojix)

The system aggregates items and contextual data from sensors. It also collects data from warehouse management and ERP systems. The information is processed on the cloud-based SaaS platform, which is available to view via an app. The technical architecture is powered by Intel® processors, which speed up the transfer—key to real-time information.

“Processing speed can be very important in stores that have a lot of items and need a lot of people informed at all times of the state of the inventory, or the location of the items,” says de Lailhacar.

In addition to accuracy and transparency, the benefits of edge intelligence also include brand protection through traceability.

“We make the item smart because we create an identity for each individual product,” says de Lailhacar. “We track the left shoe and the right shoe and can even track all the way to the leather, ensuring a pair of shoes comes from the same piece. That’s very important for luxury brands because the leather’s dye baths may result in slightly different colors.”

When you know your item individually, you can also protect sales. “For example, you can certify and authenticate it if you’re a luxury brand,” says de Lailhacar. “And you can fight the gray market because you know if someone’s taking advantage of a difference in prices on the global market. You know where that item is supposed to be sold.”

The Future of Supply Chain Management

As the marketplace evolves and more regulations are put in place, greater inventory transparency will be key for retailers to stay relevant and thrive.

“Right now, retailers are asking for transparency in the movements of their goods and transparency from their suppliers as to as where they had their products made, for child labor and other issues,” says de Lailhacar. “Laws are soon coming out in Europe that are going to make any brand accountable for their suppliers’ production methods.”

Transparency will also be increasingly important for booming secondhand markets. “Companies that are not making their brands available to the secondhand market could be missing out,” says de Lailhacar. “It’s a strategic stance. You can either buy up all of the articles that you find on the secondhand market to protect your brand, or you can decide that you will control the secondhand market. The only way to do it correctly is to be able to authenticate that those products are yours and control it.”

In a global market with so many moving parts, having a traceable, unified inventory is key to succeed in the future of retail.

 

This article was edited by Georganne Benesch, Associate Editorial Director for insight.tech.

Top Tools and Frameworks for AI Developers

AI is disrupting every industry. From enabling data-driven automation to power sustainable smart factories, catching production errors on the manufacturing floor, using robots for e-commerce fulfillment, and even battling wildfires—AI can be found almost everywhere.

Because of this, more and more developers are interested in pursuing or advancing their AI careers. But it can be a scary field to jump into, and many don’t know where to start. While countless number of resources are available out there, we’ve put together a list of the top AI frameworks and tools to help provide developers the necessary building blocks to get started with AI development.

Caffe: Born out of Berkeley AI Research, Caffe is a deep-learning framework designed with a focus on speed and modularity. It is built with an expressive architecture that allows developers to switch between CPU and GPU with a single flag. Its extensive code is meant to promote development. And its speed is perfect for research experiments or industrial applications that need to process millions of images a day. The project also provides developers with tutorials, installation instructions, and step-by-step examples to get started.

Keras: This popular AI framework is a neural network library written in Python. Keras prides itself on making it simple, flexible, and powerful for developers to experiment with machine learning. It reduces cognitive load, minimizes user actions, and clearly indicates error messages during development. You can take advantage of the project’s extensive documentation and developer guides to get started.

MXNet: Currently an Apache Software Foundation incubating project, MXNet is a deep-learning framework well suited for AI research, prototyping, and production. It includes a hybrid front-end that allows developers to mix symbolic and imperative programming to maximize efficiency and productivity. Other features and capabilities are scalable distributed training, support for eight language bindings, and an ecosystem of tools and libraries to extend MXNet use cases.

ONNX: As major technology companies work to make AI more accessible, ONNX makes sure developers can easily interoperate within the AI framework ecosystem. More than a framework, it is an open standard for machine learning interoperability. Developers can work in their preferred framework and inference engine, and ONNX aims to eliminate any implications downstream.

More and more #developers are interested in pursuing or advancing their #AI careers. But it can be a scary field to jump into, and many don’t know where to start: @IntelIoT via @insightdottech

PaddlePaddle: This open-source, deep-learning platform is committed to providing rich AI features for industrial use cases. It is widely adopted in manufacturing, agriculture, and enterprise applications. The platform features support for declarative and imperative programming, large-scale training, multi-terminal and multi-platform deployment, rich algorithms, and pre-training models.

PyTorch: This deep-learning research platform aims to speed up the time it takes to go from prototyping to production. The project provides two high-level features: tensor computation and deep neural networks. It was developed to be deeply integrated into Python. Developers can use it similarly to other popular Python packages such as NumPy, SciPy and scikit-learn. The framework requires minimal overhead to get started and integrates with acceleration libraries like Intel® oneMKL to maximum speed.

OpenCV: The community around this open-source computer vision library aims to make AI easy and fun to work with. The project itself provides more than 2,500 computer vision and machine learning algorithms for developers to get started. The OpenCV team also offers a number of tutorials, courses, and events designed to engage and collaborate with the AI community. Check out its latest AI trivia game show sponsored by Intel® OpenVINO.

OpenVINO: The Intel® OpenVINO Toolkit is designed for optimizing and deploying AI inference. The company just launched OpenVINO 2022.1—the largest update since the toolkit was first launched. Packed with new features , it’s designed to make AI developers’ lives easier. Key features include expanded natural language processing support, device portability, and better inference performance. Developers can get started quickly with pretrained models from Open Model Zoo. Learn more about the latest release here.

TensorFlow: This end-to-end deep learning platform developed by Google targets both beginner and expert developers. The core library is designed to help developers build and deploy machine learning models. But there are also additional libraries for JavaScript, Mobile and IoT, and production development.

For even more AI development resources, visit the Intel® 30-day AI Developer Challenge and learn how to build AI applications at your own pace. To boost your AI skills even further, consider the Intel® Edge AI Certification program.

 

This article was edited by Georganne Benesch, Associate Editorial Director for insight.tech.

Digital Signage Solutions: From Transportation to Retail

When you think of digital signage, you likely conjure images of eye-catching ads designed to entice consumers to make a purchase. Or maybe you think of the screens at the airport that provide you with your gate information. While using the tool for marketing and wayfinding can be effective, new applications can expand on the original vision by promoting powerful ideals like sustainability and community.

Case in point: mass transit. Dynamic digital signage solutions communicate real-time information that can increase use of public transportation, encouraging commuters to choose sustainable transportation options that promote a more carbon-neutral environment.

“One of the main things that’s deterred people from using forms of public transportation systems has been lack of real-time information,” says Jonathan Morley, CEO of Trueform Digital, a provider of digital signage solutions. “You may have a route with static printed information, but if the service has been held up for any reason, that information is out of date. People don’t like to wait. Digital signage tells potential customers when a particular service is due to arrive or depart, giving people confidence to plan their journey.”

Of course, the ability of digital signs to display advertising provides an opportunity to optimize its return on investment by generating revenue that can fund deployments. And as transportation methods evolve, digital signage can evolve, too, serving new purposes.

#DigitalSignage tells potential customers when a particular service is due to arrive or depart, giving people confidence to plan their journey. @trueformgroup via @insightdottech

From Smart City Applications to Retail Innovations

In addition to aiding travelers and commuters, smart signage and digital signs provide retailers with a way to engage shoppers. As stores embrace digital transformation, Trueform is leveraging four decades of experience with smart city applications to create sophisticated solutions that offer new opportunities for store owners and brands.

Today’s retailers find off-the-shelf digital signs to be limited in their number of features. Custom signs, such as those made by Trueform, can enhance branding, meet complex installation requirements, and provide more benefits to the viewer.

For example, London’s Westfield Shopping Centre, a world-leading retail and entertainment destination, wanted a state-of-the-art architectural design that went far beyond the typical flat-sided signs. Trueform deployed more than 170 digital advertising displays throughout the location, including unique interactive digital totems considered to be the centerpiece of the design (Figure 1).

Digital signage kiosks in a shopping mall
Figure 1. Digital signage at Westfield Shopping Centre in London provides shoppers with an interactive experience and real-time information about promotions. (Source: Trueform)

“The shopping mall wanted a particular look and feel that matches their branding and corporate identity,” says Morley. “They employed the services of a creative design agency and architect. Because of our custom design and manufacturing capabilities, we were able to supply a product to their exacting requirements, taking the concept done by a designer and making it a reality.”

One Stop Shop Digital Signage Solutions

Trueform manufactures Intel® processor-based computing systems for its digital signage solutions, including screens, cameras, kiosks, and audio units. And the company provides the digital display interface software that delivers signage content like splashy ad graphics and real-time information.

The company offers its customers a one-stop shop, including audit, analysis, specification, design, and installation. Trueform also provides lifetime maintenance, monitoring the signs it installed with on-the-ground servicing for routine and emergency response.

“In London, we have about 30,000 pieces of infrastructure that we are responsible for,” says Morley. “And we provide a four-hour repair service 365 days a year if anything happens to the sign or a piece of hardware.”

To maximize the value of its displays, Trueform also works with a variety of specialist software partners to help create a customized end-to-end solution. It works with analytics companies that collect data for business strategies as well as information sharing. For example, Trueform recently installed a digital totem infrastructure with software that counts and displays the number of cyclists on a route in real time.

“Anybody that’s driving past that sign can see the numbers per day,” says Morley. “It demonstrates that a lot of people are using these cycle lanes. It encourages more people to ride their bikes and convinced the government to invest more money on bicycle safety options.”

As technology innovations continue, Morley believes that digital signage use will expand, providing more industries opportunities to benefit.

“We know that more and more industries will be making use of digital signage and there will be more technologies that can be used in conjunction with these solutions,” he says. “At the moment, it tends to be used for advertising and that’s not a bad thing. There’s far more that can be done to provide information to the general public. We can only see that increasing dramatically.”

 

This article was edited by Georganne Benesch, Associate Editorial Director for insight.tech.

IT/OT Convergence: More Than the Sum of Its Parts

IT + OT = IoT. Not exactly. But within the world of IoT, convergence of IT and OT is a very important equation. These days, businesses can’t afford to have their IT and OT teams in separate bubbles. But in the past, these groups have operated separately, had different outlooks on how they do their work, and valued different metrics. So how to add them together? What’s the best way to arrive at more than just the sum of the parts? And what does the overall trend mean for systems integrators?

We get insights on this topic from two points of view, that of Jan Burian, Head of Manufacturing Insights for EMEA at market intelligence firm IDC, and Sunnie Weber, IoT Ecosystem Strategy Leader for Intel®. They talk about the challenges of achieving IT/OT convergence, the importance of coalitions in the convergence process, and how even environmental sustainability can be one of its outcomes. And for even more on this topic, check out IDC’s recent report: IT-OT Conversions: A Growing Opportunity for System Integrators.

Sunnie, from your perspective, what’s behind the rise of the IT/OT?

Sunnie Weber: Intel sees a really big shift in digital transformation—this connection of IT and OT. It’s no secret to anyone that IoT is extremely complex. It requires a strong convergence of technologies and people. There are distinctly different players, invested stakeholders, and mutual priorities that are being forced to merge to produce these common solutions. And so Intel sees that operationally focused solutions systems integrators play a significant role in connecting the dots between IT and OT, and so helping to bring holistic solutions to the market.

COVID has accelerated this need for convergence of IT and OT into that digital transformation. There’s high demand for improved user experience—an example being applications-focused, human-machine interfaces. The convergence of IT and OT is able to deliver that kind of value. It fulfills that need around secure infrastructure that gives enterprises the ability to make those fast decisions, increase their efficiencies, improve their resilience, and perform this unlimited scalability.

Jan, why do you think IT/OT convergence is such a growing opportunity?

Jan Burian: IT/OT convergence is definitely expanding in a post-pandemic world. But it’s not just driven by remote work; it’s also driven by various disruptions. We see that especially in supply chain—there is definitely a bigger focus on transparency and flexibility within the whole chain. Manufacturing organizations are also re-engineering their products. They are trying to embed new services to become even more resilient in terms of business, and also securing new revenue streams for the future.

These are the areas where IT and OT are both playing a crucial role. When I look at the outputs of the IDC survey, we see some classic benefits—like operational-performance improvement; like throughput and service reliability at the same or lower cost; like cost reduction in terms of sharing resources across IT/OT.

But what I also see here is something that is appearing quite a lot in the results of several different surveys—the sustainability perspective. There’s a growing importance for that because, though there are different regulations in the different parts of the world, they have pretty much the same goal: to reduce CO2. And the technology and the data from the OT environment is really something that is helping organizations to start that journey. That’s something I see as the next big trend, and also one of the biggest benefits.

Sunnie, what are some key things businesses can do to bring these two teams together?

Sunnie Weber: From an end-customer perspective you literally just need to get those CTO and COO teams in the same room, talking about their objectives and understanding the business experience and use cases that they’re ultimately trying to deliver. So one thing we strive to do is to create coalitions. The coalitions are making sure that both the IT and the OT sides are being represented—as well as the partners that are going to be part of creating the solution together: the software provider, the OEM.

Our partners are being forced to expand their working knowledge in either IT or OT—depending on their original focus—or they’re actually partnering up with some complementary company that is already an expert. That situation has maybe been seen traditionally as a little competitive, or felt like you’re giving away business; it’s actually turning into greater opportunities.

“These are the areas where #IT and #OT are playing a crucial role—like operational-performance improvement; like throughput and service reliability at the same or lower cost; like cost reduction in terms of sharing resources across IT/OT.” –Jan Burian, @IDC, via @insightdottech

One way that Intel is trying to help, especially our solutions and systems integrators, is through our partner program. And when you have this membership with Intel you can get connected very easily to Intel-validated partners through the solution marketplace, through Intel partner connect events, and through specialized matchmaking event opportunities.

And the reason that’s important is because we’re working with partners that have solutions that are vetted and really deployed out there, so we’re able to help companies connect to solid partners with which they can confidently go to market. Bottom line, I guess you could say the partners need to be willing to have those expanded partnerships so that they can come to their end customers as holistic experts. And our end customers need to start getting rid of the silo effect that has been traditional, and bridge those CTO and COO teams to have those holistic conversations.

Jan, how does an IT/OT convergence change key skills and roles?

Jan Burian: First, there’s the C-Suite: decision-makers, budget-holders, influencers. These types of managers should definitely have a better understanding of how digital technology can bring value to their company and help them to reach their KPIs. That’s crucial, because these people typically have quite a big influential power, and if you’re not able to convince them that that solution really brings the value, then it’s very hard to even get started.

Then there’s another role: a Chief Digital Officer. The typical role of a CDO is searching or looking for new technology, for new solutions, and bringing these solutions or ideas into the organization and discussing them with the stakeholders. These people should have an understanding of how to work with systems integrators. This would also be a first point of contact between the company and the systems integrators.

Then you have the IT people, who are the experts in IT security and integration of the IT systems—typically RPA or PLM. But what they really need to do is to get a better understanding of how the OT world works—what kind of protocols that could be; what the cybersecurity threats or potential issues are. And, of course, there’s also the OT group. And these people should really understand how IT works—how the data they are acquiring can then be processed in the learning steps. This is also very important. But as Sunnie already said, these are two different worlds.

And in IDC we see there’s also maybe another group: digital engineers. And they are positioned exactly between IT and OT. It’s like a converged team of the experts who are able to be a partner for the systems integrator, and are also able to be a connector between IT and OT within the company. And these people are typically managing IT/OT deployment projects. They also take care of the logic, and of the overall architecture, and, of course, the data management.

Sunnie, what can you tell us about the convergence from a systems integrator’s perspective?

Sunnie Weber: I think what this really means for the systems integrator is that there’s actually greater opportunity. To Jan’s point, they do need to educate themselves so that they are familiar with both sides of the world—and then be in a position to help the end customer merge those worlds as well. What I see the most is that enterprise customers are in a position where change is being forced on them in order to remain agile enough to stay ahead; yet they may not recognize that. And so the systems integrators are going to be that voice of reason, that voice of consultation.

Jan, what opportunities do you see ahead?

Jan Burian: Companies are always looking for new ways to improve the customer experience and to secure new business. There is a good point with the metaverse idea, for example. We probably know it from an environment like a Fortnite or Roblox, where industrial players have already stepped in and are selling or promoting their products or their brands there—I call it the civil metaverse.

But there’s also an industrial metaverse. That is more digital twin based, which is one of the key solutions when it comes to the convergence of IT and OT. For this industrial metaverse there could be a number of use cases—from simulations to testing to customer experience improvement. These digital twins should be driven by the data coming from a real environment—and this is where convergence between IT and OT is happening. I said at the beginning, the future will definitely be about convergence of IT and OT systems.

Sunnie, any closing thoughts you’d like to leave with our audience?

Sunnie Weber: Sometimes the best way to have this conversation on IT/OT convergence is to start at the end. What is the value that the end customer is looking for? Because you need to be able to help the partners and the end customers define, communicate, and deploy these value-based solutions that really inspire them and their customers to change their business outcomes. And then you can begin the evaluation of both the IT and the OT forces.

So a systems integrator can walk their customer through the conversation, and end up helping to enable those better operational models that buffer the customer from situations like COVID, allowing them to be more agile and responsive. It becomes this holistic-enablement conversation of a greater value and service at the end of the day. It provides greater value to the end customer, and it provides more business for the systems integrator.

Related Content

To learn more, listen to the podcast The Meaning of IT/OT Convergence with IDC and Intel® and read IT-OT Convergence: A Growing Opportunity for System Integrators. For the latest innovations from Intel and IDC, follow them on Twitter at @IDC and @Inteliot or on LinkedIn at IDC and Intel-Internet-of-Things.

 

This article was edited by Erin Noble, copy editor.

Bringing Edge AI to Healthcare IoT Applications

The transition of AI from hospital labs and operating rooms to initial points of care in the field is the next big step for healthcare IoT applications.

Consider an ambulance outfitted with a mobile rugged edge computer. With the right balance of performance and power efficiency, first responders could feed outputs from instruments like portable ultrasounds directly into the computer, where edge AI algorithms analyze the scans for irregularities. Those inferences would then be transmitted wirelessly to hospital physicians while the ambulance is en route, saving valuable time upon arrival that could change patient outcomes for the better.

Equipment like this can unlock a greenfield of opportunities that enhance patient care in countless edge environments ranging from doctors’ offices to rural clinics to pop-up disaster relief efforts.

Traditionally, high-end medical imaging machines­—deployed in major healthcare facilities—analyze a great deal of sensor data. These machines require a lot of computing capability that makes them physically large, very heavy, and power-hungry. They are also quite costly.

Today, most edge devices have limited edge processing capability, which requires transmission of data through the cloud to a data center for analysis. The answer is then transmitted back to the edge device. This process incurs latency and requires a reliable connection that is not always available. It is also impractical and expensive to send large amounts of data in this way. Edge medical devices therefore need their own local compute power, often assisted by AI technology.

These two technical problems are solved by a new generation of microprocessor with expanded raw computation capability, execution efficiency, and wide data movement that is necessary to shrink machine size and lower power draw as a prerequisite for wider deployment.

Rodney Feldman, VP of Business Development and Marketing at IoT solution developer SECO USA, explains: “The traditional edge intelligence computing model doesn’t work for edge medical imaging devices. Transmission of large amounts of sensor data over potentially unreliable communications channels puts patients at risk. And the development of such a distributed processing system is too complex and long. It requires careful segmentation of algorithms, separate implementation and testing of both the edge device and cloud software, and then finally exhaustive testing of the entire system. The solution is to implement as much intelligence as possible at the edge and minimize transmission of data.”

The transition of #AI from hospital labs and operating rooms to initial points of care in the field is the next big step for #healthcare #IoT applications. @SECO_spa via @insightdottech

A Faster Path to Edge AI

Medical use cases are a great example of why IoT developers are turning to off-the-shelf, high-performance embedded computing (HPEC) solutions, with enough computing horsepower and efficiency to move cloud capabilities to the edge. But to provide the same level of service as the cloud, these solutions must also include high-speed I/O to ingest multiple Gigabytes of data per second from high end devices like ultrasound probes and other medical imagers.

Today, medical OEMs and systems integrators can source these features from platforms built on 12th Gen Intel® Core processors (formerly known as “Alder Lake”).

These new processors employ a heterogeneous compute architecture with up to 14 Performance- and Efficiency-cores, and 96 Intel® Iris® Xe Graphics execution units. In use cases like a rugged medical edge server, an integrated intelligent, low-latency hardware scheduler routes complex AI workloads to the Performance-cores and graphics units, while less-intensive system management tasks are sent to Efficiency-cores.

On the data acquisition front, 12th Gen Intel® Core desktop processors represent the first time PCIe 5.0 interfaces are available. With support for 32 GigaTransfers per second (GTps) data transfers, the processors’ x16 PCIe 5.0 connectivity provides ample bandwidth for ultra-high-speed, high-resolution sensor data acquisition from diagnostic and other equipment.

Robust security and advanced virtualization technology are also crucial in these systems, especially considering the nature of medical applications. They must not only ensure critical operations are executed reliably and deterministically but also protect sensitive patient data from leakage or exposure.

All this combines to support multiple demanding applications—like these medical application examples—on the same, integrated edge HPEC platform.

“The performance and level of integration of disparate but complementary technologies in these processors are allowing new applications to be deployed more fully at the edge than before. They’re pushing more intelligence with less hardware, which of course means less size, weight, power, and cost,” Feldman says.

Onto a Board and Into the Field

Despite the processors’ efficiency, developing a compact, rugged edge server comes with serious thermal and electromagnetic interference (EMI) design implications. And the more advanced the processor, the more pins it typically has, the faster and noisier its signals become, and the more power it consumes.

Recognizing these potential challenges and the trend toward HPEC platform deployment, the PCI Industrial Computer Manufacturer’s Group (PICMG) released the COM-HPC computer-on-module standard. Like other COMs, COM-HPC leverages a two-board architecture consisting of a processor module and carrier board, but unlike others it was designed to support high-speed interfaces like PCIe Gen 5 and 25 Gbps Ethernet, processors up to 150 W, and includes two 400-pin connectors which enable a wealth of connectivity.

“More pins and power envelope in a designed and validated module,” Feldman says when speaking to the biggest advantages of COM-HPC. “One of the big things is just being able to utilize the high-speed interfaces through the COM-HPC connector. The development of circuitry utilizing interfaces like PCIe 5 and USB 4, for example, and high speed processors like the 12th Gen Intel Core requires high specialized knowledge of signal and power integrity, and how to apply it to circuit board design. Using a COM-HPC module eliminates the need to design the core computing platform.”

SECO’s Orion solution, a COM-HPC client size A module with a 12th Gen Intel Core H-Series mobile processor, is available off the shelf. But the company also designs and manufactures custom COM-HPC modules, carrier boards, and other solutions based on 12th Gen Intel Core S-series desktop processors that accelerate time to market and minimize risk.

And SECO even has a vertically oriented application software group, staffed by expert algorithm developers and data scientists, that can help get edge AI systems further off the ground.

Redefining the Medical Edge (and Cloud)

It’s been apparent since the early days that IoT applications would demand much more distributed intelligence than was in place at the time. At that point, many of the concerns were related to minimizing the amount of data that was captured and transmitted across a network, but increasingly the reasons have changed. Now it’s about capitalizing on what that distributed intelligence can enable.

In edge AI servers powered by technologies like 12th Gen Intel Core processors and COM-HPC modules, medical OEMs and integrators can consolidate what used to be multiple processors into smaller, cooler, lower-power, lighter weight, and less expensive equipment.

“Once you do that, you can push more diagnostic equipment into the field,” Feldman says. “A powerful, rugged system can deploy in an ambulance, and you have more autonomy for first responders to make quicker decisions and take immediate actions.”

 

This article was edited by Georganne Benesch, Associate Editorial Director for insight.tech.

AI-Powered Smart Buildings Get Schools Back in Session

How do organizations bring people back to the workplace in a safe and comfortable way, while at the same time maintaining profitability? And how do school districts bring students and teachers back into the classroom while meeting safety regulations to protect their well-being?

There’s no one-size-fits-all solution, so understanding some of the priorities and methods is an important step. After almost two years, returning to in-person activities is a top priority for educators, but it may not be an easy process. The good news is that innovative technologies and solutions can help aid facilities in the planning and execution of their in-person return strategies.

One example is Presentation High School, a private school in San Jose, California, the heart of Silicon Valley. After pausing on-campus learning in 2020, administrators sought a re-entry solution for the 2021 school year.

Their goal was to control and monitor access and student flow without making it overly intrusive. The requirements were clear:

  • Ensuring staff and student safety by controlling the number of individuals in their facilities
  • Quick entry/exit screening for large groups
  • Maintaining a log of who entered different facilities, buildings, rooms, and when
  • A human-operated solution or kiosk
  • Easy access to critical data, especially for contact tracing
  • Ease of use for the entire staff

.@OnLogic and @ThingLogix worked together in developing #Workwatch, a pandemic management solution that has been instrumental in bringing schools, businesses, cities, and other organizations back together in-person. via @insightdottech

Developing Smart-Building Technology Through Collaboration

The administration turned to OnLogic, a global industrial PC manufacturer, and its partner ThingLogix, an IoT low-code software solutions provider.

The companies worked together in developing Workwatch, a pandemic management solution that has been instrumental in bringing schools, businesses, cities, and other organizations back together in-person. The successful collaboration between the two companies came about thanks to the AWS partnership program in which OnLogic and ThingLogix are Advanced IoT Technology partners. And the AWS cloud platform is an essential element of the solution.

ThingLogix played a big role in helping Presentation High determine business and technical implementation of the project. And that implementation started just three weeks after their first meeting.

“They had to bring people back safely, and there’s all kinds of emotion and challenges in making a change like that,” says Brett Mancini, Vice President of Sales for OnLogic. “And when you augment efforts with technology, you can do so more quickly and more effectively. It also helps to instill confidence in the staff that they can return with minimal exposure while supporting their students.”

AI-Powered Edge-to-Cloud Health Screening

Workwatch ticked off all the requirements Presentation High had on its list.

“They saw the opportunity to use Workwatch right off the bat, and they created some of their processes around it,” says Mancini. “They use it for tasks such as distributing health survey responses and screening temperatures when people are coming into the building. Rapid screening is important to avoid a line of 100 kids waiting outside the door close to each other.”

Workwatch is an artificial intelligence-powered platform that runs on the OnLogic Helix 500, an Intel® processor-based, industrial-class edge PC. It connects all of the required edge devices—cameras, thermal imaging and other sensors, RFID tags, and Bluetooth—to capture the state of physical locations.

ThingLogix developed the Workwatch software, which handles aggregation and analysis to channel essential information to the AWS cloud for further analysis and future reference. For example, the software reads and analyzes rules-based biometric health screening data, providing immediate feedback. It can flag whether an individual should be allowed or denied entry based on thermal imaging temperature readings.

“You can give folks badges and then with AI and machine vision quickly identify where and when people are in particular areas,” says Mancini. “You’ve got IoT sensors, perhaps recording temperatures, and the use of PPE as they go through different areas where it might be required. This location and time-period data makes contact tracing possible in real time, with fewer errors than if humans had to do all of that monitoring manually.”

Beyond Pandemic Recovery

Looking forward, Presentation High School administrators see a long-term need to know on any given day who’s on campus and where they are.

The school has learned that beyond COVID-19, implementing work task management is a huge benefit. And Workwatch is making it possible. For example, the solution can be leveraged to better understand resource and staffing needs. Who knows what the future of in-classroom and remote education will be, but we do know schools need to be prepared.

Pandemic recovery is just one area where the Workwatch platform can play a role.

“This is one of those things that you could put in place now to be more prepared for a variety of use cases. You can customize it for everyday applications, not just related to the pandemic,” says Mancini. “As additional sensors become available, the uses for Workwatch will continue to grow. Meanwhile, people can feel confident about coming back to work, school, and play.”

The Meaning of IT/OT Convergence with IDC and Intel®

Jan Burian & Sunnie Weber

[podcast player]

As the world becomes more connected, businesses no longer can afford to have their IT and OT teams operate as separate islands. They need to collaborate and communicate to adapt and respond to their ever-changing business needs. But how do you merge these two separate worlds?

In this podcast, we explore how to break down IT and OT silos, the biggest business benefits, and the new opportunities IT/OT convergence creates for systems integrators.

Our Guests: IDC and Intel®

Our guests this episode are: Jan Burian, Head of Manufacturing Insights for EMEA at market intelligence firm IDC, and Sunnie Weber, IoT Ecosystem Strategy Leader for Intel®.

At IDC, Jan focuses on Industry 4.0, digital transformation, and IT in manufacturing environments. Prior to joining the firm, he worked as a consultant for EY and Deloitte in the manufacturing and supply chain space.

Sunnie has worked in the world of IoT for more than eight years through sales and partner enablement, sales operations, and channel scale design. In her current role, she works to simplify the complexity of connectivity in the IoT ecosystem.

Podcast Topics

Jan and Sunnie answer our questions about:

  • (4:39) The importance of IT/OT convergence
  • (7:35) New businesses opportunities stemming from this convergence
  • (12:38) What businesses can do to bring people and platforms together
  • (17:13) How the convergence of IT and OT changes key skills, roles, and responsibilities
  • (22:56) Key considerations for systems integrators
  • (25:40) How IT/OT convergence will play a role in the metaverse
  • (29:20) The best way to approach IT/OT convergence in your organization

Related Content

To learn more, read IT-OT Convergence: A Growing Opportunity for System Integrators. For the latest innovations from Intel and IDC, follow them on Twitter at @IDC and @Inteliot or on LinkedIn at IDC and Intel-Internet-of-Things.

 

This podcast was edited by Christina Cardoza, Associate Editorial Director for insight.tech.

 

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Transcript

Kenton Williston: Welcome to the IoT Chat, where we explore the trends that matter for consultants, systems integrators, and enterprises. I’m Kenton Williston, the Editor-in-Chief of insight.tech. Every episode we talk to a leading expert about the latest developments in the Internet of Things. Today I’m talking about IT/OT convergence.

As the manufacturing sector becomes more connected, businesses just can’t afford to have their IT and OT teams operating as separate islands. But what’s the best way to bring these two teams together? And what does this trend mean for systems integrators? Here to talk more about this is Jan Burian from IDC, and Sunnie Weber from Intel.

Thank you so much for joining us today.

Jan Burian: Hello, thank you for having me.

Kenton Williston: Tell me about your role at IDC and what brought you to the company?

Jan Burian: My current position is a manager, or I’m leading a manufacturing insights team in IDC for EMEA. I’m based in Prague, Czech Republic. And I’m with IDC for about two and a half years, and the role is just like… Besides, let’s say, leading team, I’m also leading the practice which is called Future of Operations, which is very IT/OT convergence–driven. And before joining IDC, I was working for EY and Deloitte for 11 years as a consultant. And I was in charge of performance improvement in the manufacturing and supply chain here in the center of Eastern Europe. But I also used to travel a lot, sometimes in Asia, in Western Europe, and I was, at the very beginning, at Industry 4.0 area.

That was 11 years as a consultant, and prior to that I was working in the factories. These were the suppliers for the automotive industry and these were both based in Czech Republic, or located in Czech Republic but owned by German enterprises. My role there was focusing on the quality management and owner project management. So I was responsible for ramping up the new production—the new parts within the production environment.

Kenton Williston: That’s really cool. I didn’t know you were in Prague. One of my best friends is from the Czech Republic, although not from Prague, he’s from—out in the middle of nowhere. I don’t even know if there’s a town of any meaningful name nearby, but he’s very much a country boy. That’s good to meet a city boy from the Czech Republic. So, Sunnie, tell me about your role, and what you’ve been up to at Intel.

Sunnie Weber: Sure, thanks. And thanks for having me as well. I’ve been fortunate to work in the world of IoT for the last eight-plus years now. And I’ve worked in sales and partner enablement, sales operations, and channel scale design before being able to focus on setting up partner programs for our edge partners, the operational-technology solution and systems integrator. These are those domain-expert integrators who consult and recommend solution hardware and software components, and provide end users that custom solution-deployment integration and those maintenance services. So, over the last two years I’ve spent time focusing on that just-right value exchange for this partner type, and trying to understand and implement the programmatic ways for Intel to be able to support them. But just recently I moved into a broader role in IoT as the ecosystem-partner strategy lead.

And I’m really excited to be able to take everything that I’ve learned and build a bridge across the ecosystem, helping our partners cross over from get- to go-to-market with a goal of getting everyone faster time to market and more service opportunities. So, really connecting our ecosystem is a highlight of our partner programs value exchange, and that’s definitely the focus that I want to be able to bring to the table.

Kenton Williston: Yeah, that’s great. So, a couple quick things that come to mind from hearing both of your backgrounds. First of all, I absolutely should mention that this podcast and the greater insight.tech program as a whole are published by Intel. So, good to talk to a fellow Intel person here, and also everything you’re saying about how important the role of systems integrators is, and how central this concept of IT/OT convergence has become, really are playing out a lot on the articles that we’re publishing on insight.tech. So, definitely encourage all of the folks listening today to go check out all the articles we have over there, because there’s lots of really, really interesting stuff happening. Sonny, why don’t you tell me, from your perspective, what is behind this IT/OT convergence becoming such a big thing?

Sunnie Weber: Actually, Intel sees a really big shift in digital transformation—this connection of IT and OT. It’s no secret to anyone that IoT is extremely complex. It requires a strong convergence of technologies and people. I like to refer to the Merriam-Webster dictionary definition of “convergence”: it’s the merging of distinct technologies, industries, or devices into a unified whole. And that’s exactly what I see happening with IT and OT. There’s distinctly different players, invested stakeholders, and mutual priorities that are being forced to merge and produce these common solutions. And so Intel sees a significant play that operationally focused solutions systems integrators play in connecting the dots between IT and OT, and helping to bring holistic solutions to the market. So that’s why, as I mentioned before, we created these programs to support these partner types in the IoT ecosystem value chain to enable them to deploy faster, offer improved services, and really ultimately grow that business at the edge.

And I think, Jan, you’ll be familiar with this, but some of the supporting research that IDC did in the 2021 IoT spending report on IoT and edge—the global IoT market size in 2020 was posted as $309 billion. And despite the significant effects of COVID that happened after that, the market is actually projected to still grow to $1.8 trillion in 2028. So, in fact, COVID impacts have accelerated this need for convergence of IT and OT into that digital transformation, and it’s now a leading concern for the enterprise, who essentially is captive audience now. So, what we’re seeing is that there’s high demand for improved user experience with, an example being, applications-focused human-machine interfaces. So IT and OT converged is able to deliver that kind of value. It fulfills that need around secure infrastructure that gives the enterprises the ability to make those fast decisions, increase their efficiencies, improve their resilience, and perform this unlimited scalability. And this demand is what I think is very telling and directly tied to that IoT and digital transformation.

Kenton Williston: Yeah, and you mentioned a report, and we actually are hosting on our site right now this really great, very detailed report from IDC on the topic of IT/OT convergence. So if you’re looking forward there, the title is “IT-OT Conversions: A Growing Opportunity for System Integrators.” So, Jan, I’d love to hear some more details of what you saw in that report in terms of why is this such a growing opportunity, and what are the business benefits that are driving so many companies to look into this?

Jan Burian: That IT/OT convergence would be definitely, or the word of IT/OT, would be expanding after the pandemic, in post-pandemic world. But that’s not just driven by the remote work and all the stuff like the service or the focus on our services and so on, but it’s also driven by the different disruptions. So, especially what we see in supply chain—all these, let’s say, the problems with the containers or with the transparency of the whole chain, and also from another angle that’s about the growing or rising prices of the commodities, of the raw materials and components and so on. So there is a definitely the bigger focus on transparency and flexibility within the whole chain, and also the manufacturing organizations—they are re-engineering their products. They are trying to embed the new services to become even more resilient in terms of business and securing the new revenue streams for the future.

These are the area where IT/OT—these both are playing the crucial role. This is framing the situation. When it comes to the benefits, I just look into the outputs of the IDC survey we just run recently, and we see some, let’s say, classic benefits, like operational-performance improvement, like a throughput and service reliability at the same or lower cost, for example, or as a cost reduction in terms of ability to share the resources across IT/OT, that’s improvement in customer service. I mean, personally, what I see here is also one of the—I don’t want to say a new benefit, but something which is now appearing quite a lot in the results of several different surveys, is that sustainability perspective—that IT/OT could be seen or understood as the enabler of the CO2 footprint reduction, for example.

This is something which is going to get, I would say, not just like a big attraction, but also there’s a really growing importance of that because there are different regulations in the different parts of the world, but with pretty much the same goal to reduce the CO2, and the technology and the data from the OT environment is really something which is helping the organizations to start their journey. Sustainability, definitely—that’s something where I see as the next big trend and also one of the biggest benefits. And maybe let me share also one quite important experience.

I mean, typically we see these benefits could be like an OEE, or could be waste reduction, whatever, by 5 to maybe 10 percentage points, which is good. But what’s very important is also to have ROI or Return on Investment, within, let’s say, boundaries of one or two years and to be able to reach this target, one or two years in ROI—this is about the broader connection or integration of the systems. This is not definitely about the pilots or about isolated solutions, but this is about the ability to leverage the whole ecosystem of solutions within the organizations. So we’re talking always about the ability to scale. This is very true when it comes to the building a solution with the one year ROI. But this is also, I would say, one of the most mentioned barriers when it comes to the IT/OT integration in real life.

Kenton Williston: Interesting. So there are a couple key points there I think are worth digging into deeper. One is the issue of sustainability, and I absolutely agree that that is going to become just increasingly important as we go forward. I mean, it’s already a big, big topic, and I think not only will companies desire to be more sustainable, but they’ll be required to be more sustainable over time. So I think this is a very important criteria for everyone to look at. And the other thing that you mentioned here at the end of your very good points was the challenges to actually achieving this IT/OT convergence, and there’s a lot of factors at play there, not least of which is that, historically, these groups have been totally separate from one another, have very different outlooks on how they do their work, and what metrics are important to them.

So, for example, on the operations side very often it’s crucially important to maximize up time. You’ve got to keep the factories running, the containers are being shipped, as we were just talking about. That can be challenging sometimes, so more important than ever. And on the IT side, on the other hand, it’s been more about trying to innovate and keep up with all sorts of new technologies and rapidly deploying things. There’s a very different mindset between these two groups and of course, historically, the technologies they have used have been quite different as well. So, Sonny, what do you see as being some of the key things businesses can do to bring these two teams together?

Sunnie Weber: I think it actually can depend on the perspective. So, from an end customer perspective you just literally need to get those CTO and COO teams in the same room, talking about what their objectives are and understanding the business experience and the use case that they’re trying to ultimately deliver—that’s just from the core side. But really what you see for partners is that they’re the ones—the systems solution integrators, Intel on our side, our sellers—we’re the ones that have to help our end customers start having those discussions. We need to ask the right questions to get our end customers to be thinking that way as well. So one thing we strive to do is create coalitions. The coalitions are making sure that you’re representing both the IT and the OT side, as well as the partners that need to be involved in this conversation who are going to be the ones that are part of creating the solution together—the software provider, the OEM—who at the table needs to be together.

So, for our partners, another thing that’s interesting, just in addition to getting that correct assessment down with the end customer, our partners are actually being forced to either expand their working knowledge in either the IT or the OT depending on their original focus, or they’re actually partnering up with some complementary partners who are already experts. Well, that has maybe traditionally been seen as a little competitive, or feeling like you’re giving away business; it’s actually turning into greater opportunities. So, one example is one of our larger NSIs. They saw some tremendous value in business growth by partnering with one of our OTSIs, and now they’ve grown a huge pipeline together. So while they were traditionally maybe a competitive relationship, they’re now going to business together and excelling. So one way that Intel is trying to help, especially our solution and systems integrators, is through our Intel partner association membership.

The unique opportunity is understanding and having relationships with partners all across the ecosystem. And when you have the membership with Intel, you can get connected very easily to Intel validated partners through the solution marketplace, through Intel partner connect events, and through specialized matchmaking event opportunities that we’re starting to have regionally. And the reason that’s important is because we’re working with partners who have solutions that are vetted and really deployed out there. So we’re able to help partners connect to solid partners that they can go to market with with confidence. So, bottom line, in summary, I guess you could say the partners need to be willing to have those partnerships expand so that they can come to their end customers as holistic experts. And our end customers need to start merging and having those—remove the siloed effect that has been traditionally known, and bridge those CTO and COO teams to have those holistic conversations.

Kenton Williston: Got it. Now you’re going to have to help me with a little decryption. Is NSI a network systems integrator?

Sunnie Weber: Actually, they’re the National System Integrators. So they tend to be the larger systems integrators. A lot of times they will partner up with the smaller, more regionally focused solution integrators or systems integrators on the operations side. So maybe they’re more on the design side, and the operations-technology experts are doing the physical integration onsite.

Kenton Williston: Yeah, that totally makes sense. And that’s something we’ve talked about a lot on the insight.tech program as well, is how there are all these niche markets where the local SI is really going to understand their customer extremely well in a way that a larger SI can’t do. But, conversely, the larger national SI will have technical capabilities and a breadth and scope of expertise that really is important in bringing these very different groups together. And so it is very much a complementary match. Totally agree with you there. So, what I am wondering about at the same time, and, Jan, maybe you can speak to this, is you do need a certain set of skills to be successful in pursuing these relationships and helping your end customers. So, Jan, what do you see in terms of being some of the key skills and roles and responsibilities that might be changing in the interest of putting this IT/OT convergence forward?

Jan Burian: Firstly, let me draw the typical structure or the different groups within the company, within the manufacturing organization. We have a C-Suite, so, decision makers, budget holders, influencers. So these type of managers, they definitely should be having better understanding of what or how digital technology could help to improve their KPIs. How digital technology could bring the value to their company, how this could be helping them to reach their KPIs. So, that’s very crucial, because these people, typically they have quite a big influential power, and if you’re not able to convince them that that solution really brings the value, then it’s very hard to just get there.

That’s the first group of the people within the typical manufacturing organization. Then there’s another group. This other—maybe let’s start with a Chief Digital Officer and people around this person. And I would say typical role of CDO is searching or looking for the new technology, for new solutions, and bringing these solutions or ideas into the organization and discussing with the stakeholders, or with the owners of the processes, with line of business leaders about how this solution could help them to improve what they do.

These people, they should—it’s not just about like a detailed understanding of these solutions, but they also should be having the understanding of—I mean, how to work, for example, with the systems integrators. This would be also like a first point of contact between the company and the systems integrators. They really need to understand what’s possible on a market. Technically you can buy anything, but is the ROI really like one or two years, or is a solution—could it be scaled within, I don’t know, a short term period? And also does the solution comply with the long-term company strategy? That’s also extremely important. So the people around, or the team or CEO, should be really getting that deep understanding of technology, but also of the implementation deployment process. Then you have, let’s say, another group—these are the IT people.

And there’s no doubt that these are the experts in IT security and in the, let’s say, integration of these IT systems—typically RPA, PLM, whatever. So, supply chain–management systems. But what they really need to do is to get a better understanding of how the OT world works, what kind of protocols that could be. I mean, what’s the cybersecurity threats or potential issues that might be happening? So that’s another group. And, by the way, before I get to the OT people, let me share one thing or one thought that a lot of people see IT-OT integration more from the, let’s say, data perspective. So you’ve got data generated on the edge, then they’re being transferred to the cloud or to the on-premise IT systems, and then will be analyzed then—I don’t know what we can do, but a thousand different things with that.

But that’s one perspective. The other perspective is that automation—I mean IT data could be triggering different situations, or this could be controlling the production lines. There could be communication between IT layer and PLC, and PLC is operating, controlling, driving the production line. So there is, let’s say, two-way flow of the data. Also the IT people should understand the logic of this, because if IT won’t work properly, then the production line could collapse. If it’s just, like, about data, getting the data from a line to the system—I mean, sometimes it’s not vital for the systems, but if it goes other way around, this could end up with, like, a catastrophe in production. And of course there’s also the group of the OT. As Sonny already said, these are two different worlds.

So these people should really understand how the IT works. How they could leverage—how the data they are acquiring, providing, could be then processed in the learning steps. This is also very important. And in IDC we see there’s also maybe another group, and we call them digital engineers, and they are positioned exactly between IT and OT. It’s like a converged team of the experts who are able to be a partner for the systems integrator and are able also to be a connector between IT and OT within the company, and these people, they typically are managing IT/OT deployment projects. And they also take care of the logic and of the overall architecture. And of course the data management—that’s another part of what they do.

Kenton Williston: There’s a lot to think about. You’ve given me a lot of good points there, but I’ll see if I can summarize everything you just said by—basically, there’s two key elements. There’s the “what are you doing,” but there’s also really the “why are you doing it.” You need to understand the perspective of the other side of the table, as it were. So, Sonny, something that’s making me think about is, we heard a little bit from Jan just now about how the end customer needs to have people who are bridging this gap. There’s a real good to having people specifically in that role. But what about from the systems integrators’ perspective?

One of the things you talked about was matchmaking between different systems integrators. I’m sure that’s a very important part of it. I imagine also it’s pretty important to be able to identify the right solutions that are already designed with this type of IT/OT convergence in mind. Hopefully I’m not leading the witness here too much. Is that a key consideration? Anything else that you think is really important for SIs to consider?

Sunnie Weber: I think what this really means for the systems integrator is that there’s actually greater opportunity. To Jan’s point, they do need to scale up, or at least educate themselves so that they are familiar with both sides of the world, and then be in that position to help the end customer merge those worlds as well. So there’s this consultative approach that they can take in order to answer this holistic solution. If everybody is able to start having a conversation with the value and the experience that they want out of it first, it’s really going to open up the conversation for that greater opportunity that they can deliver on. What I see the most is that the enterprise customers are in that position where change is being forced on them in order to remain agile enough to stay ahead, yet they may not recognize that. And so the systems integrators are going to be that voice of reason, that voice of consultation that, “Hey, this is actually what’s happening, and why you need to remain agile and be able to stay ahead.”

So they need to be able to improve their operational efficiencies, provide that faster time to market their products and services to meet the demand. And, again, that flexibility to respond to changes in things like product quality and maintenance services using reliable data analytics that Jan was just talking about. But having this greater opportunity—I’m just going to go back to it again—it requires having the best parallel partnerships to be able to deliver and drive more business. So that’s what’s going to allow a systems integrator to position themselves as a trusted advisor and a long-term strategic partner who can support that digital transformation, the IT/OT convergence that the customers are demanding at the edge.

Kenton Williston: That makes sense. And, Sonny, I think one of the interesting things you’re pointing to there is this sense that companies are being forced along in this direction. And I think it’s always helpful to take these changes and look at them more as opportunities than as challenges. I think that shift in perspective can really bring a different thinking. So, Jan, I’d love to hear a little bit more about some of the opportunities you see ahead. So, for example, one of the things that people have been talking about a lot in the last little bit is this idea of a metaverse. Are there new opportunities ahead in spaces like this that companies may not be thinking about already that they can reconceptualize why they need to do IT/OT convergence?

Jan Burian: Yeah, good point with the metaverse. I can get to that a little bit later, but let me just say that what we consider—the organizations need to be more resilient, generally speaking. That means they should be more transparent, more flexible, and be really able to react on almost any disruption that might appear. So, no one knows what’s going to happen. So, even in months or for longer term, it’s almost impossible. So that risk-based approachthat was applied in risk management, that’s already the old thing. So the resilience is probably like a combination between the resiliency concept and the risk-based management, is the best way for the future. And this is where the technology is really helping, through providing the data. It doesn’t have to be real time to be better, but almost in a near real-time data—some of them being processed on the edge, some of that being processed on the cloud.

So that definitely helps the organizations on their transparency, flexibility journey. There’s also so many, maybe not new issues, but I would say maybe some issues which are more important than the others. I mean, from the conversations with the end users, we always hear about capacity issues, people issues, or people and organizations. It’s very hard for them to drive the capacities. So, one day they have too much, and then the other day they don’t have people to produce something.

So that’s a big problem with the supply chain as well. So that’s why also companies are looking for new ways how to improve the customer experience, how to secure new businesses. And this is where we get to that metaverse idea, for example, which is a totally virtual world. We probably know that from the environment like a Fortnite or Roblox on these types of worlds, where also industrial players have already stepped in and they are selling or promoting their products or their brands in that metaverse—that’s one part; I call it “civil metaverse.” But there’s also the industry metaverse, which could be—and this is more like digital twin based.

And, by the way, we didn’t mention “digital twin” during our podcast, but that’s one of the key solutions or outputs wherever—when it comes to the convergence of IT and OT. So, for this industrial metaverse, where the manufacturing organizations could be building the entire virtual production plans, which they can use for—there could be a number of use cases, from the simulations or the testing or customer experience improvement, and so on. These digital twins should be driven, fueled, or powered by the data coming from a real environment. And this is where convergence between IT and operational technology is happening. Definitely, as I said at the beginning, the future would be even more about convergence of IT and OT systems.

Kenton Williston: Yeah, absolutely. I have to say, again, both of you have given us so many great ideas to think about, but unfortunately we are reaching the end of our time. So, Sonny, I just want to give you the last chance here to add anything you think we might have overlooked, or just any closing thoughts you’d like to leave with our audience.

Sunnie Weber: Yeah, sure. The advice that we’ve been giving, and the training we’ve been giving our own sales field is that sometimes the best way to have this conversation on IT/OT convergence is to start at the end. What is the value that the end customer’s looking for? Because you need to be able to help the partners and the end customers define, communicate, and deploy these value-based solutions that really inspire them and their customers, changing their business outcome. And then you can begin the evaluation of both the IT and the OT forces. So, for example, identify what their current capabilities are, how do they source data? What is their end-to-end interconnectivity enablement? What device management systems are they working with? How are they managing compute, and what is their analytic setup? And then you can take that and say, “Okay, are these actually working together in this continuum to be able to provide the information they need that produces the outcome they’re striving for?”

And so, a systems integrator can walk their customer through this conversation, through that continuum—that’s when they can identify, for example, what is their existing quality control methodology? And how is their supply chain for operations management? Does it apply the benefits to the bottom line? All of these things end up helping to enable those better operational models that buffer them from situations like COVID, allowing them to be more agile and responsive. And so when somebody is able to help identify their customers strengths and weaknesses, that’s when they can tap into the just right partners, and then show up as that comprehensive, trusted advisor. So taking that time to dig in during those initial conversations, and then covering the true value and experience they’re trying to deliver—that’s going to take their conversation from stopping at, “Hey, I just need some machine condition monitoring.”

It’ll turn that conversation to, “Oh, actually what I think you’re saying is, you want to improve product quality to drive business revenue and keep your customers coming back.” And that’s when you can bolt on the additional conversations around, “Well, maybe we need to think about employee safety monitoring in addition to this machine condition monitoring. And how can we turn these improved and targeted data analytics for tracking the quality control?” It becomes this holistic-enablement conversation of a greater value and service at the end of the day. So what that does is it provides greater value to the end customer, and it provides more business for the systems integrators.

Kenton Williston: Perfect. Well, with that, Sonny, I just want to say thanks so much for joining us. Really appreciate your time.

Sunnie Weber: Thank you so much.

Kenton Williston: And, Jan, I’d like to say thank you to you as well.

Jan Burian: Thank you.

Kenton Williston:  And thanks to our listeners for joining us. To keep up with the latest from IDC, follow them on Twitter and LinkedIn at IDC. And you can also follow Intel on Twitter at IntelIoT and on LinkedIn at Intel-Internet-of-Things. If you enjoyed listening, please support us by subscribing and rating us on your favorite podcast app. This has been the IoT Chat. We’ll be back next time with more ideas from industry leaders at the forefront of IoT design.

 

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel® trademark information.

 

This transcript was edited by Erin Noble, copy editor.

The Answer to Commuter Chaos? AI Traffic Management Systems

As thousands of Washington, D.C. drivers headed to Arlington National Cemetery for the Armistice Day ceremony, they found themselves stuck in the world’s first traffic jam. On November 11, 1921, the congestion trapped motorists in their cars for hours—along with one very displeased President Harding, whose limousine had been caught up in the middle of it all. People were frustrated, tired, and unaware that they were making history.

Just 100 years later, urban traffic chaos persists. But AI traffic management systems may offer a new solution to this century-old problem, while at the same time addressing the sustainability challenges of the future.

There are good reasons why cities have struggled to solve traffic management challenges.

In an ideal world, urban planning would save us from our traffic woes. But in historic city centers, where the road layout is inherited, this approach isn’t feasible. That’s especially true in emerging markets, where many streets are old and narrow, budgets are limited, and other infrastructure priorities take precedence.

Technological solutions have limitations as well. Loop detection systems are a help, but they’re basically just car counters. They can’t provide the kind of detailed data needed to model and predict traffic. Cloud-based traffic management systems are somewhat better, but suffer from latency issues that make them unable to adapt to sudden changes on the road.

“The crux of the problem is that traffic flow is inherently unpredictable,” says Jonny Wu, Senior Director of AIoT at Ability Enterprise, a manufacturer of edge AI smart cameras. “The bottom line is that if your solution can’t adapt to traffic flow changes in real time, it’s going to be suboptimal.”

AI Traffic Management: A Synergy of Edge and Cloud

The application of edge AI technology to traffic management has opened up new possibilities. In itself, edge computing isn’t new. It was first used in the 1990s to improve web and video content delivery. But processors are now powerful enough to handle the kind of computational heavy lifting needed for AI at the edge.

Ability’s Agile & Adaptive Transportation Management solution relies on Intel® VPUs, which Wu says are “particularly good at performing the types of visual processing tasks required by edge AI camera systems.”

In practice, this means that AIoT cameras like Ability’s can do a lot more than just count cars. They can identify different vehicles by type, use license plate recognition to track individual cars, calculate journey times, monitor changes in direction, and detect queue fluctuations at intersections.

And that’s a game changer, because this is exactly the kind of granular, real-time data you need to model, predict, and optimize traffic flow.

In an AI traffic management system, data is captured and processed on the edge and then sent to the cloud for additional processing. In the cloud, the historical traffic data is used to model flow dynamics. An AI optimizer then runs simulations to create an optimized traffic control plan.

The plan is pushed out to traffic signal controllers in the field, where the edge AI cameras monitor the flow of traffic and send data to the cloud for ongoing optimization. If necessary, the AI system will automatically adjust the traffic control plan in real time to adapt to changing conditions.

 “#Edge #AI isn’t a replacement for the #cloud—but computer vision on the edge, together with cloud AI optimization, offers a solution that’s more than the sum of its parts.”—Jonny Wu, Ability Enterprise.

It’s this combination—AI on the edge and in the cloud—that makes the system work. “Edge AI isn’t a replacement for the cloud,” says Wu, “but computer vision on the edge, together with cloud AI optimization, offers a solution that’s more than the sum of its parts.” (Video 1)

Video 1. Implementation of an AI traffic management system from data collection to full deployment. (Source: Ability Enterprise)

AI Systems Deliver Significant Results

Ability’s Malaysia implementation is a case in point. The company’s AIoT cameras were deployed in the city of Ipoh, on a busy stretch of road that suffered from heavy traffic congestion.

“It’s a series of four intersections right in the center of Ipoh,” explains Erwin Yong, Director of LED Vision, Ability’s partner in Malaysia, “so we’re talking about a part of the city where it’s basically impossible to widen the road.” Compounding the problem: Three nearby schools were causing traffic buildups during student drop-off and pickup times.

Ability and LED Vision installed 12 cameras across the four intersections. After an initial data collection period, the historical traffic data was sent to a cloud AI optimizer. Once the optimized traffic control plan was fully deployed, the results were striking. Benchmarked against the historical data, as well as Google’s commute time predictions, the system reduced the average vehicle journey time in the area by more than 30%.

Smarter, More Sustainable Cities

If you improve traffic flow, you cut journey time for drivers—and idle time for cars. The obvious benefits are fewer hours wasted in traffic jams and a substantial reduction in carbon emissions. And then there are the not-so-obvious benefits. For one thing, an AI system eliminates much of the human effort needed to manage traffic at busy junctions. Traffic officers are freed up to go where they’re needed most.

In addition, says Wu, AIoT camera systems are versatile: “A camera that you use for traffic management, you can use for other things as well: illegal maneuver detection, speed enforcement, and so on.”

In an era of global climate crisis, cities are looking for new ways to reduce carbon emissions and reach their sustainability targets. Effective, economical, and flexible, AI traffic management systems will be an attractive option to traffic engineers and systems integrators building the smart cities of tomorrow.

Traffic management may be an old problem. But thanks to advances in AI, the future is looking bright.

 

This article was edited by Georganne Benesch, Associate Editorial Director for insight.tech.

How Tech Data EMEA Bridges the IoT Partner Ecosystem Gap

Digital is the name of the game these days—for pretty much every game in town, every business, every service. But digital transformation takes expertise and skills, and small- to medium-size companies can’t usually afford a big R&D department. They may not have the right resources in-house to deal with complex and interconnected technologies like computer vision, either. Fortunately, there is an ecosystem of IoT partners that can help.

But who services the service provider? Who sells to the channel reseller? Who integrates the systems integrator? That’s where Tech Data EMEA, a leading IT distributor and solutions aggregator, comes in. Its European Chief Technologist for Data and IoT Evan Unrue talks about overcoming barriers to entry for technology deployment, the solutions Tech Data supports, and its crucial Better Together alliance with Microsoft and Intel®.

What drives enterprises toward AI and IoT today?

Everything is digital these days. It’s forcing enterprise organizations to become more real time, more data driven, more informed, and more engaging across both their southbound channels down to the customer, and upstream with how they interact with their suppliers.

Data is also now absolutely critical to strategy. And rather than data just being something that’s generated as a byproduct of an application, data is driving applications. Look at supply chain, for example. Organizations are now having to deal with the fact that customers want to know where everything is, where it came from, is it ethically sourced, is it going to come tomorrow? All this requires an enormous amount of orchestration, which requires data and intelligence.

How have companies been doing in their efforts to deploy these kinds of technologies?

We’ve seen adoption really springboard over the last couple of years. Five years ago you had to be a Fortune 500, a Fortune 1000 company with an R & D budget to afford to do these projects and then drive them into the core of a business. And the SME market was suffering because it wasn’t able to do that. Or they were creating interesting projects, but they weren’t really driving them towards the business outcomes.

All of the complex things that you can do with #AI or with #IoT at scale should be reserved for where the right budget exists, and where the payoff is big enough.” – @interestingevan, @TechDataEurope via @insightdottech

In the last couple of years, we’ve seen more success in companies being laser focused on outcome. A big part of that is due to the efforts of the vendor community—that’s the likes of Microsoft, the likes of Intel®—driving an immense amount of innovation through their ecosystems. And the ISVs and OEMs are solutionizing off the back of all that. So we’re seeing solutions come into the market that are more clear and concise in terms of the outcomes that you can drive with them.

What is Tech Data and its IoT partners doing to ease the barriers to AI and IoT?

For common industry challenges there should be off-the-shelf offerings that can be implemented by the average business stakeholder. We’ve seen a bit of a democratization around certainly AI, and around some of the application stack that sits in front of these IoT infrastructures. We have a big push towards solutions at Tech Data, and you only have to go on the websites of Microsoft or Intel® for two minutes to see their efforts around driving market-ready solutions, off-the-shelf solutions.

All of the complex things that you can do with AI or with IoT at scale should be reserved for where the right budget exists, and where the payoff is big enough. But if you are a small freight-logistics company, you’ll typically have the same problems of any other small freight-logistics company—whether it’s optimizing your fleet and their routes and their maintenance, or whether it’s tracking assets through the supply chain. Whatever it is, the solutions should be off the shelf and ready to take to market.

I think some of these complex technologies fall into the category of digital transformation as a whole, and attacking that can be a scary thing for a midmarket organization. So you have two approaches. You can either come with a top-down approach and have a uniform infrastructure that all these use cases can plug into; it’s a bit of a larger effort, but the payoff is there. Or you can look at the discrete parts of your business operations where you might have gaps in data, and then start to deploy these tactical solutions.

There’s a spectrum of solutions out there; the Intel® IoT Market Ready Solution program is one. But primarily it’s about taking proven solutions by ISVs, OEMs—companies that have deployed these solutions over and over with customers—and our job then is to provide the reach and scale of getting those solutions in front of a channel partner.

Can you talk about some specific use cases and technologies Tech Data supports?

Smart building is certainly a big area, and there are a few facets to that. Number one is how do you better manage and maintain a building? How do you reduce the cost of doing that? How do you get in front of problems as they’re happening? And within that area, energy is a big topic. Certainly a lot of companies are being tasked with being more proactive with their sustainability efforts.

Another one we’ve seen over the last few years is retail in the High Street looking to reassert its resiliency—giving people more reasons to come, being engaged with customers, and extending those customers’ digital journeys into the physical store. Better planning of store layouts, for example. Better optimization of marketing to the demographics on the ground leading to better conversions. A colleague of mine likes to use the term “phygital,” which is the combination of physical and digital, and this applies particularly well in the High Street. It’s being contextual in terms of how you interact with a customer, and that might be through signage, that might be through interactive displays and putting something in front of a customer that’s relevant.

How does your work with Microsoft and Intel® relate back to these solutions?

Those two organizations have coexisted in the enterprise space for a long time. And with regard to technologies like IoT, for example, there’s been a really strong focus from both of them to be promoting the industry applications around it.

If you look at Intel, it’s really been driving programs to simplify the development process, and help developers and organizations build these solutions at the edge—bringing on technology such as computer vision, using tool kits such as OpenVINO, to create meaningful solutions. And you pair that with all the expertise and experience that Microsoft brings—and not just from the cloud. It ranges all the way from being able to do really complex and difficult, but very powerful and insightful things in very bespoke environments, through to very plug-and-play-type offerings that are really geared towards the midmarket. It’s kind of “one plus one equals five.” It’s a very powerful combination.

How is Tech Data bringing value to this alliance as an IoT solutions aggregator?

One of the big challenges historically, from a technology standpoint, has been understanding and identifying the multiple stakeholders required to bring these solutions together. So part of our job is to aggregate all the different technology players within that value chain, and to simplify the consumption of those solutions so resellers and customers don’t have to get bogged down by the technology.

As far as Intel goes, it’s a little bit removed from the coalface in terms of who’s selling what, and we connect them to that through our interactions with the resellers. And with Microsoft we’ve had a keen joint focus around IoT since the beginning. So I think there’s just strong alignment, a strong execution capability, and we complement each other in all the right ways.

What are some of the trends that businesses should be thinking about going forward?

One of the big things we’re seeing now is leveraging AI to make sure that insight into the data is driving what the action should be. This is what we see from a lot of the ISVs we work with. They’re focusing on what the action should be, what the outcome should be, rather than just gaining visibility and transparency into whatever is being monitored.

Computer vision looks like a really strong trend to me, just because it’s such a versatile technology. It can underpin countless use cases that could range all the way from traffic control and waste management and public safety from a smart city perspective; to gaining richer insights and stronger engagement from a retail perspective; all the way through to improving things like quality and safety in warehouse environments.

Are there any big IoT challenges that companies should be aware of?

I think the biggest thing is getting the support of the wider business. One of the challenges of IoT is that the first use case provided might not actually be the one that delivers the whole ROI. So it’s really important to try to understand who the different stakeholders are that are going to benefit from these solutions, and to bring them to the table. In retail offerings, for example, there are some things that just have to be done, regardless of ROI. Certainly retailers don’t want to have to close stores because they can’t meet conditions around, let’s say, proper social distancing.

But when it comes to looking at digital engagement within the store, when you start to bring it to the planning side of the business, and to the marketing side of the business, and you start to bring in, maybe, merchandising and third parties that advertise, and offer them space and data around footfall—then it helps the payoff become a lot more substantial in terms of justifying the business case.

I like to call it the IoT multiverse, because there are so many different dimensions in terms of the type of companies that play here—whether it’s the connectivity channels, the silicon channels, or the cloud channels.

Anything else you’d like to leave us with?

The importance of edge compute. We’ve seen technology architectures go from distributed to centralized, to distributed, to centralized, and back and forth. But this is one of the things that’s really become critical—certainly with the adoption of IoT, where you have mass amounts of data being generated at the edge, and that data might actually need to be processed, or might impact a process at the edge. Edge computing is becoming pretty critical because of the volume of data that can be created, and with an organization’s ability or need to drive action rather than just deliver data off the back of these solutions.

Whereas the cloud, whilst powerful and important for all of the things that I’ve mentioned in terms of getting a broad view across multiple assets, across multiple locations, having more horsepower behind you to drive deeper and richer insights—all of that’s important, but being able to automate and drive AI locally is also important. Microsoft acknowledges that actually some of the services it provides it needs to be able to push to the edge as well as having in the cloud, which is something that it does hand in hand with Intel.

Also, one of the things I’ve always said is that, as distributors, we have one of the most privileged positions in terms of being able to derive insight from the market. We get to see the hopes and dreams and fears of all of our vendors—what they’re trying to achieve and what their strategies are. And then, at the other end of the spectrum, we get to see what the partners are doing. Where their strategies have evolved or haven’t. Who are the early adopters, and who are the laggards? How do we help them move from one bucket into another and maintain relevance in the market?

And because we’re really sitting in between all of that, we are perfectly primed to bridge the gap between the vendors’ aspirations and their knowledge, their technologies and expertise, but also our understanding of those channels and how to drive adoption into the right technology spaces.

Related Content

To learn more about the IoT partner ecosystem, listen to Into the IoT Partner Multiverse with Tech Data EMEA. For the latest innovations from Tech Data, follow it on Twitter at @TechDataEurope and LinkedIn at TDSYNNEX.

 

This article was edited by Erin Noble, copy editor.

IoT Paves the Way Toward Smart Sustainability

Environmental sustainability is one of the most urgent topics today. At its foundation, it’s about lowering carbon footprint—a stairstep from where you are today to some future carbon neutrality.

In an interview with Michael Bates, Intel® Global Sales GM, Energy and Sustainability, we talk about the leadership role Intel® is taking through its own actions and technologies. For more than 25 years, Michael has worked at the leading edge of new concepts and business models in distributed energy, and the intersection of traditional energy and technology.

Michael shares the innovative ways in which the company enables an ecosystem of partners and end-customers to achieve their own smart sustainability initiatives.

Let’s start out by talking about Intel’s smart sustainability strategy.

The foundation for our strategy is wrapped around our RISE (Responsible, Inclusive, Sustainable, Enabling) 2030 goals and objectives. It is our north star, guiding us into 2022 and beyond. Not only in our own sustainability efforts and practices, but also how we’re enabling sustainability in the market.

We have a sense of responsibility in applying all the goodness at Intel and our partner ecosystem to act and address some of the biggest challenges in sustainability.

We have a sense of responsibility in applying all the goodness at @Intel and our partner ecosystem to act and address some of the biggest challenges in #sustainability. @IntelIoT via @insightdottech

When you talk about customers going down their own sustainability path, what does that look like?

The guiding principle is how to apply technology and solutions to go down that path. Sustainability has become the number-one topic in most, if not all, businesses. It’s a C-level conversation because it has so many implications, across the entire enterprise, all the way from the company brand to cost control. There’s also pressure from shareholders and financial markets that are also creating this sense of urgency.

And I think it has an impact on acquisition of talent. There’s a lot of passion to be part of the drive toward more sustainability and a lower carbon footprint.

When we think about sustainability, alternative energy sources and smart grids are top of mind. What’s happening in this area?

With these carbon-neutral energy sources like solar, wind, battery, the electricity distribution model clearly needs to undergo change, starting at the substation. We’re moving from an always-on, one-way flow of power to a highly distributed network across the other side of the grid. This two-way distributed power requires a level of edge compute that supports making real-time decisions using AI and machine learning tools.

Utilities are looking to develop a platform for the delivery of these new services. In markets like Europe, for example, many utilities are taking a very aggressive approach to this disruption. We are working with companies like Enedis in France, Iberdrola in Spain, and Enel, a utility in Italy. They see this as a great opportunity to expedite the transition to clean renewables. And while they are doing it themselves, they are taking these best practices to other utilities in other markets.

Companies that modernize the grid and their delivery of energy services are going to be the ones that are at the forefront of revenue generation.

What are private and public sector organizations doing to meet their green-energy objectives?

For one, businesses and educational institutions are building microgrids for their own facilities. They deploy these technologies on-site to help lower their carbon footprint, consume more green energy, and be more energy resilient.

And when they generate more power than they can use, it can be shared with the grid and be turned back to the market. Not only does it allow organizations to lower their carbon footprint but potentially open the opportunity to make some money while they’re at it.

This is a massive opportunity from an IoT solutions perspective. Imagine all the data needed to create those algorithms to optimize both sides of the energy equation, the building, the parking lot, the solar panels. We’re not at the very beginning, but it’s still very early. There are a lot of buildings out there that are going to get some funding to update and modernize in this way.

That’s a good segue to talk about sustainable, smart buildings specifically.

Smart building technology of course has been around for a while, and buildings are already fairly well instrumented. What’s needed is to consolidate all those different workloads onto a common platform. Then to look for those insights to drive energy efficiency, lower carbon footprint, and be more energy resilient. The impetus now is adding in the green-energy component, which requires a higher level of systems and data integration, and which a lot of our partners are fulfilling right now.

So same problem, and part of the solution is really driving that edge, computing edge, AI capabilities, high performance needed to do that.

But the amount of workload consolidation is heavy, and it needs significant compute power at the edge to optimize that. More importantly, it’s the almost  instantaneous decision-making that must happen. You can imagine, if you’re really relying on solar power, for example. In one area, the weather changes and it moves from cloudy in one to sunny in another, those changes happen instantaneously. And when you start aggregating a lot of that data, it’s clear to see that AI is the answer. To turn that intermittent, distributed energy into base load, like we were talking about.

Electric vehicles and the infrastructure to charge them is another hot topic. How is this market evolving?

It’s one of those chicken-and-egg conversations. Do you build out a network of fast-charging infrastructure and then the cars will come? Or do you wait for the cars and build it out based on demand?

With so many car manufacturers switching to EV models, the growth is exceeding projections up to this point. But the need to scale requires the certainty of being able to charge your vehicle and travel just like you do today. It must look and act like filling up a gasoline-powered car.

The big trend going forward is fast EV charging—10-15 minutes. On roadways, this will be scaled expeditiously through the funding that we get from infrastructure funding, both in the U.S. and Europe.

But the real driver is going to be the retailers that see charging your vehicles as a service. Just like you get Wi-Fi at Starbucks today. Imagine relying on a similar experience, whether it’s a plug-in or even a wireless EV charging station. Now, there’s a new revenue opportunity where customers pull in and purchase that retailer’s products at the same time.

Another interesting application that’s coming out of Japan is a mobile battery concept being tested. An automated mobile robot plugs in on the outskirts of town or in a dense city like Tokyo, where you can’t put solar panels. It charges up its batteries, and then gets dispersed to the parts of the city where the energy is needed, to fill in the peaks and valleys. And it knows where to go based on AI and real-time decision-making. It’s futuristic, but maybe not as far in the future as you might think.

This has been a great conversation. Is there anything you’d like to add that we didn’t get a chance to go over?

This is a call for action. No one has the ecosystem partners that Intel has, which has been built over 50 years. If we can work closer together and collaborate in this partner network, think about the real impacts that we can make. It could be impactful planet-wide.

We really do have an opportunity to do something here. It’s not theoretical, it’s not prohibitive, it’s needed. And I think the appetite is high for IoT solutions that help make it possible.

 

This article was edited by Christina Cardoza, Associate Editorial Director for insight.tech.