Q&A: Everything AI at embedded world 2021

embedded world is going virtual in 2021. But the event, held March 1-5 online, is now easier than ever for people to attend. And it’s still packed with experiences from the entire world of embedded technology—from AI to IoT.

Kenton Williston, Editor-in-Chief of insight.tech, and Dr. Sally Eaves, CEO of Aspirational Futures, discuss what to expect from this year’s event, where it fits in the broader context of the industry, and how attendees can get the most of their time strolling—that is, scrolling—the show.

Want more? Find links to demos and Q&A sessions from embedded world 2021 on the blog page for this podcast, and learn more about the technologies discussed in their conversation. Or join Kenton and Sally as they live tweet several of the sessions and explore what’s happening there in real time.

Megatrends of embedded world 2021

Kenton Williston: Sally, can you tell our listeners a little bit about yourself?

Sally Eaves: I’m CEO of Aspirational Futures, which basically looks at enhancing inclusion in technology and also education. I’m a CTO by background, and I’m now a senior policy advisor for the Global Foundation of Cyber Studies and Research. I do a lot around emergent technology advisory, and I’m also a professor in that area. I’m really active around cloud computing, cybersecurity, IoT, IIoT, AI, blockchain, 5G, etc., but also the cultural aspects of those topics. And the people factors around sustainability and social impact too.

Kenton Williston: All things very relevant to what is coming this year to embedded world. I think the big trends I am looking at for this year’s show really center around embedded transforming into IoT—and building on that IoT migration trend is a greater and greater emphasis on AI. It seems to be part of just about everything that is happening this year.

From your point of view, Sally, what do you see as the megatrends for 2021 as they relate to the Internet of Things and AI? And just generally, what’s happening in this commercial-technology space?

Sally Eaves: I think it’s really exciting times. There’s a great deal of convergence. And you mentioned two of the key factors there—with IoT and industrial IoT alongside AI and machine learning. But I’d also add 5G into the mix, as that becomes more and more mainstream. We need to look at not just the technology, but the skill sets alongside that. Time-sensitive networking is one to look out for as well—things to make it easier for developers so they can really maximize their time.

Kenton Williston: One of the demos that I’m really looking forward to seeing on this point is what IEI (one of Intel’s partners) has called their AIoT kit, which—as its name suggests—combines AI plus IoT. And of course it brings together the AI and IoT sides of things, but it also brings together with that the 5G technology that you were mentioning.

Another demo from Vecow brings together AI pre-trained models and ROS, the Robot Operating System. It’s like a one-stop shop for everything you need to create an intelligent robot—like an autonomous robot that might be running around a warehouse floor.

Sally Eaves: I love the sound of that demo. I’ll definitely be looking at that.

There are some  challenges I see, as well. I think one would be security and, in particular, safeguarding critical data within industrial and embedded IoT. And also thinking more on the network side of things around timeliness. I think that’s so, so vital for industrial automation, AR, VR, and also robotics use cases.

Making Tech “Simpler, But Not Simple”

Kenton Williston: From your point of view, what should developers and engineers be on the lookout for that will help them actually put together these increasingly complex, multifaceted sorts of applications that folks are trying to build in 2021?

Sally Eaves: We’ve got this increased sophistication that’s offered by convergence, but at the same time it’s this juxtaposition around complexity. So it’s about making it simpler but not simple, for another way of putting it. I think one thing definitely to look out for are the 5G elements. 5G and Edge computing together—connecting more devices, more efficient processing of data.

And agility—I think it’s the key word probably for 2021, as your workloads are fluctuating. Distributed Edge computing is going to give that flexibility to scale on demand, to deploy your applications to any Edge location, conserving memory and power. And because apps are being processed at the Edge, you’re reducing bandwidth as well. I’m seeing some very interesting collaborations in that space—definitely would shout out for that for developers to have a look at.

Kenton Williston: Intel’s got a whole new web presence that it’s launched within the last year called the Intel® Edge Software Hub, which I think is a pretty interesting effort to bring together all of these commonplace technologies. And it’s not just for the things like the AI or the robot operating systems, but even things like the connectivity—pre-packaged modules for 5G connectivity—that allow you to easily configure the Open Network Edge Services Software—or OpenNESS platform—on that Edge device.

So, I think all these kinds of approaches, where you’re almost building things out of Legos, as it were—this is the sort of thing that I think everybody has been talking about for a long, long time. To your point about the agility and how quickly folks are wanting to, not only deploy IoT designs but be able to update them—I think it’s just more important than ever.

Sally Eaves: The example you gave just now about the Edge Software Hub is such a strong one, because you’re right, you’ve got that pillar, that pre-optimized pillar of deployment-ready software packages, which is fantastic. But, equally, you’ve got the ability to customize, so it’s that best-of-both-worlds approach. I think that’s absolutely the way we need to be going.

Making AI Trustworthy

Kenton Williston: A lot of these trends are kind of longer term, but I think something that has changed here is just how pervasive the AI element is in just about every space. I saw a couple of examples from ADLINK, who will be demonstrating how they use AI for everything from inspecting contact lenses to automating palletization and tracking of items for shipping.

Sally Eaves: Absolutely. And supply chain—I think one of the things that’s come to the fore so much over the pandemic is the fragility around that, and embedding a transparent audit trail. I’ve seen some really interesting things with AI and blockchain coming together. So that marriage, for want of a better word, between AI and blockchain I think is one to watch as well. Pharmaceuticals, for example, would be a classic example of that.

The Ethos of Tech-for-Good

Kenton Williston: Another thing that I think is worth adding to the mix here is the safety element of things. As exciting as it is to see this amazing intelligence being applied in all these amazing, creative ways, there’s also a lot of caution that we should exercise about how we’re deploying these technologies—particularly as we’re increasingly automating systems and making them hands off.

One thing that comes to mind for me there as an example is Intel and its latest hardware platforms: the Intel Atom® x6000E series processors incorporates functional safety technology to help protect the physical world. And there’s a really great demo from NEXCOM showing exactly how that works, and how you can deploy that in all kinds of different applications to keep things from causing harm.

Sally Eaves: I think that’s one of the absolute key issues of the entire year. In certain sectors around manufacturing, operational technology, health, education, there’s been such an increase—I think it’s around a 300% increase around identity attacks over the past year, as one example. I think we’ve also seen where there’s been continual investment in infrastructure, but maybe less so around patching and around refreshes. So that’s created an area of security vulnerability.

Kenton Williston: Another thing that comes to mind for me is ethical AI, which is something I know you’re passionate about. I’m thinking about a demo from a company called EverFocus that is offering an in-transit network video recorder box that incorporates analytics—both forward-looking to see what’s happening in traffic, as well as inward-facing to understand what’s happening inside the vehicle.

There’s potential for misuse there, but there’s also potential for really amazing benefit in terms of keeping people safe and healthy, and cities running efficiently and minimizing their carbon footprint. So it’s all about how you deploy it. And I like this EverFocus demo as a kind of example of how to do it the right way.

Sally Eaves: I think leadership in this area is so, so important. And one of the things that’s also impressed me over recent months is a bit of a change in the narrative around this. But what we’ve been able to see over the pandemic experience is some fantastic examples of collaboration. One of those that springs to mind for me would be the HPC Consortium—the High Performance Computing Consortium—of which Intel is a member.

And it’s a great example of leading tech companies coming together—partnering up with research and academia and governments across the world, as well—and really coming together. That ethos of tech-for-good collaboration—basically bringing computing capacity, bringing computing power together to look at how we can better fight COVID-19. I think that’s a great example of turning the narrative on AI as something for good. Supporting that further, building that momentum of greater trust around AI, I think is really, really important

I also think this comes down to education. People have to be empowered to be able to ask the right types of questions, and we need to get better diversity of teams into who’s building AI, as well. And that goes beyond aspects like gender, to all sorts of different characteristics. But diversity of experience—it matters so, so much. And every piece of research going—and our practical experience as well—says that the teams that are diverse are happier, they’re more creative, they’re more satisfied, and you get so much more innovation, and you reduce the risk of implicit bias as well. So that has to be the way to go forward.

embedded world 2021 vs. embedded world 2020

Kenton Williston: I’m very excited to see for myself where things are going as the industry gets more complicated, more sophisticated. But I think there’s an overriding theme here of bringing together so many different technologies that have been in development—whether it’s AI, whether it’s 5G, whether it’s safety and security—bringing so many of these things together in ways that I think really are noteworthy, and notably different than what I saw last year at this time. How about you? What are you looking forward to?

Sally Eaves: I think there’s a real acceleration in innovation, and around the actualization. The speed of change has been unlike things we’ve seen before, absolutely. So I think there is a real change this year vis-a-vis the one before. That’s really, really exciting.

There are so many sessions. Fourteen sessions on Internet of Things, platforms and applications. But I think what I like about this year’s event is it’s five days long—you can really tailor it to your particular organization and also what you want to learn about. There are so many opportunities to really dive in deep and ask questions.

I also like the matching application they’ve put together. It feels like a proper personalized experience. Because if you can’t be there in person, then making an event feel like a true interactive experience matters so much.

I really miss the socialization aspect of events and things, but I must admit I’m really impressed by how the agenda for this has been curated. There’s a really strong attention to detail there, and opportunities to build that network connection and match people together. So I really like what’s been done in terms of curating the event.

Kenton Williston: Should our listeners be coming to this podcast after the fact, where can they find you online?

Sally Eaves: I think the one to go for, number one, would be @sallyeaves on Twitter. But I’m on all major channels— LinkedIn, my own website, etc.

Kenton Williston: That just leaves me to thank you for joining us today. Really appreciate all your insights.

Sally Eaves: Absolute pleasure. And really looking forward to the event.

Everything AI at embedded world 2021

A conversation with Dr. Sally Eaves @sallyeaves

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With embedded world 2021 going all-digital, attending the world’s premier IoT event is easier than ever. And it’s one of the year’s best opportunities to get up to speed on the latest in AI and advanced programming techniques. You won’t want to miss this chance to discover the trends that will define the year.

In this podcast, multitalented IoT and AI expert Dr. Sally Eaves joins insight.tech Editor-in-Chief Kenton Williston to preview the show, pick out must-see conference sessions, and highlight key trends attendees should look for at the event. We explain:

  • Why AI will play a critical role at embedded world 2021
  • How new tools are changing the way IoT applications are created
  • How developers and engineers can get the most out of the event
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Transcript

Kenton Williston: Welcome to the IoT Chat podcast, where we talk about the trends that matter to developers, engineers, and system architects. Today we’ll be talking about the upcoming embedded world 2021 show, which of course has now gone all virtual. Kind of sad and disappointed myself not to be going this year, because I love taking a flight out to Germany every year around this time. But the great thing about it is now it’s going to be easier than ever for folks to attend. And so, on that point, I’ve invited our guest, Dr. Sally Eaves, to join me to talk a little bit about what’s going to be coming up in the show, where it fits in the broader context for the industry, and how attendees can get the most out of their time. So, Sally, welcome so much to the show.

Sally Eaves: Oh, thank you so much. Pleasure to be here. Really looking forward to our conversation today.

Kenton Williston: Excellent. And can you tell our listeners a little bit about yourself?

Sally Eaves: Yeah, absolutely. So, I’m CEO of Aspirational Futures, which basically looks at enhancing inclusion in technology, and also around education as well. I’m a CTO by background, and I’m now a senior policy advisor for the Global Foundation of Cyber Studies and Research. I do a lot around emergent technology advisory, and I’m also a professor around that area as well. So, really active around cloud computing, cybersecurity, IoT, IIoT, AI, blockchain, 5G, etc., but also the cultural aspects of that, and the people factors around sustainability and social impact too.

Kenton Williston: All things that people are very much focused on these days, I think. Very relevant to what is coming this year to embedded world. So, on that point, I think two of the big trends that I am looking at for this year’s show really center around, of course, the longer-standing trend of Embedded transforming into Internet of Things, or IoT, technology. And I think that what really distinguishes those two is a combination of the connectivity. Of course, you can’t have an Internet of Things without having an internet.

And then I think also the intelligence, and I think what’s becoming particularly prominent, and building on that IoT migration trend, is a greater and greater emphasis on AI. It seems to be part of just about everything that is happening this year. So, I’m wondering, from your point of view, Sally, what you see as the megatrends for 2021 as they relate to the Internet of Things and AI, and just generally what’s happening in this commercial-technology space.

Sally Eaves: Yeah, absolutely. I think it’s really exciting times. There’s a great deal of convergence. And you mentioned two of the key factors there, with IoT and industrial IoT alongside AI and machine learning. Absolutely. But I’d also add 5G into the mix there as well, as that becomes more and more mainstream. A lot of the advantages that brings—particularly, for example, building low-latency applications—I think that’s going to really have an influence as we move to the latter side of this year as well. So I’m excited to see what happens there.

I think, just generally, the latest predictions are something like 41 billion connected devices by 2025, and the whole market around embedded software is set to increase to something like 130 billion by two years later—so, 2027. So we’ve got a huge demand for this area. So we need to look at not just the technology, but the skill sets alongside that. And maybe some of the challenge trends I see as well. So I think one would be security and, in particular, safeguarding critical data within industrial and embedded IoT, and also thinking more, maybe, on the network side of things around timeliness. I think that’s so, so vital for industrial automation, AR, VR, and also robotics use cases as well.

So, things like time-sensitive networking, which I know is one of the sessions at the upcoming event as well. I think it’s one to look out for as well. So, really exciting times, and AI specifically—things to make it easier for developers so they can really maximize their time. So I think there’s some interesting things we can explore there in depth as well.

Kenton Williston: Yeah, absolutely. I feel like you’ve almost read my mind there on several points. So, one thing for sure I should mention up front here is that listeners can visit the blog page for this podcast, and they will find there links to a whole bunch of different demos and Q&A sessions that folks can attend to learn more about all of the technologies we’ll be discussing today. And that’s very much inclusive of one of the first things you mentioned—that a lot of things are converging together. I had already mentioned there’s AI plus IoT; you talked about 5G, security, and I absolutely agree.

This, of course, is nothing new, to say that applications keep becoming more and more complicated. It’s almost trite to say that. But I think there’s a truth to that that is different from how things used to be complicated in the past—that the kinds of complexity people are dealing with is quite a bit different than in the past. And bringing all of these different technologies together, I think, really has a meaningful impact on what kinds of applications you can even consider.

And one of the demos that I’m really looking forward to seeing on this point is, there’s a really cool, what IEI—one of Intel’s partners—has called their AIoT kit, which as its name suggests combines AI plus IoT to get AIoT. And of course it brings together the AI and IoT sides of things, but it also brings together with that the 5G technology that they were mentioning, which I do agree is going to be a very important part of where the application space is headed this year.

To another point that you made about the challenges and the complexity—I’m wondering, from your point of view, what developers and engineers should be on the lookout for that will help them actually put together these increasingly complex, multifaceted sorts of applications that folks are trying to build in 2021.

Sally Eaves: Yeah, absolutely. I love the sound of that demo, by the way. I’ll definitely be looking at that. That looks fantastic. I think, for me, you really touched on it around convergence. So, for me, it’s—we’ve got this increased sophistication that’s offered by convergence, but at the same time it’s this juxtaposition around complexity. So it’s about making it simpler but not simple, for another way of putting it. So, I think one thing definitely to look out for—which I think is going to really help, and I’ve just been part of an incubation program along this very basis—are the 5G elements. So I think that’s really exciting in terms of speed and the new possibilities that’s going to create.

So, 5G and Edge computing together—connecting more devices, more efficient processing of data. And agility—I think the key word probably for 2021 as your workloads are fluctuating. Distributed Edge computing is going to give that flexibility to scale on demand, to deploy your applications to any Edge location. So that’s really exciting, and conserving memory and power, and, because apps are being processed at the Edge, you’re reducing bandwidth as well. So, looking out around opportunities for that, I’m seeing some very interesting collaborations in that space.

So, definitely would shout out for that for developers to have a look at. But on top of that there’s a range of tools supporting alternative software-development paradigms, and they’re becoming more available. Using graphical programming methods or domain-specific languages. So that’s an exciting area. It’s very much model-based software development, but also in particular—and we’ve touched on it a little bit already—but opportunities for almost, like, all-in-one Edge development offerings. So you’re integrating software and hardware with pre-trained AI models and comprehensive tools. So it’s all around that help, that seamless help, for developers to take care of that baseline to a certain extent, to give you more time to do the actual innovation and agile development.

So that’s really exciting. Anything that’s going to help you with—or active prototyping, experimentation, get up and go and running quickly—those are the things to look out for. And I’ve seen a lot of things in the agenda coming up that really touch on that in depth. So I’m really excited to see where that goes.

Kenton Williston: Yeah, I’m seeing much the same. And I mentioned already that there’s this IEI kit that they’ll be demoing that brings together a number of things. And another one that really struck me from this angle is there is one from a company called Vecow that brings together some AI pre-trained models, like you were describing, as well as the ROS—that is the Robot Operating System platform—and I think this is a really good example of the sort of thing that you were laying out as the path forward.

You need to have pretty robust platforms that have got a lot of the basics done for you. And more than that, I think, shared platforms, whether they be open source or at least open APIs. I mean, I’m thinking, for example, like the way the big cloud players like Microsoft and AWS have these APIs you can leverage. I think using the standard methodologies and approaches to design your IoT devices is going to be increasingly important, just because you’re trying to combine so many complicated technologies in one single device, in one single software package.

So, again, the one that was really interesting in this regard was this demo that Vecow will be showing that’s kind of like a one-stop shop for everything you need to create an intelligent robot. So—think an autonomous robot that might be running around a warehouse floor, or something like that, would be a good example of where this would be really useful.

Sally Eaves: Absolutely. No, I spotted that as well. I think that looks excellent and really reducing time consumption, and particularly around challenges of integration of various software stacks as well. I think it’s so strong on that, but also things, maybe, around stable and reliable version management as well. I think that’s an excellent example.

Kenton Williston: Yeah, absolutely. Absolutely. So, and in fact, some of the links we’ll be providing on our site will be to exactly those sorts of things. I briefly touched on the way that folks are increasingly doing development in a fashion that resembles what you would see in the IT world. So, doing things in containers, developing in the cloud, and pushing to the Edge, make it a lot easier to—to your point—maintain versioning, make it a lot easier to maintain visibility across distributed systems, make it a lot easier to—as I was saying earlier—take a bunch of standardized things and package them together in a platform that everybody else is already using, so you don’t have to figure it all out for yourself.

Sally Eaves: Absolutely. Absolutely. I couldn’t agree more.

Kenton Williston: And there’s even a really interesting session that’s talking about some of what Intel’s doing. It’s got a whole new web presence that it’s launched within the last year called the Edge Software Hub, which I think is a pretty interesting effort to bring together all of these commonplace technologies. And it’s not just for the things like the AI or the robot operating systems, but even things like the connectivity—pre-packaged modules for 5G connectivity—that allow you to easily configure the open network Edge services software—or OpenNESS platform—on that Edge device.

So, I think all these kinds of approaches, where you’re almost more like building things out of Legos, as it were—again, this is the sort of thing that I think everybody has been talking about for a long, long time. And I think there’s nothing new conceptually about this, but I think, just given all the many different things, and—to your point about the agility and how quickly folks are wanting to, not only deploy IoT designs but be able to update them—I think it’s just more important than ever.

Sally Eaves: Yeah, I think the example you gave just now about the Edge Software Hub is such a strong one, because you’re right, you’ve got that pillar, that pre-optimized pillar of deployment-ready software packages, which is fantastic. But, equally, you’ve got the ability to customize as well, so it’s that best-of-both-worlds approach. So, it’s so strong on the actualization side of things, and what you mentioned there about continuous integration, continuous deployment—I come from a telco background; I’ve just been doing some work specifically on this area, and I think it’s so, so strong for that granular changeability, which I think is fantastic to move into the IoT space. So, absolutely. I think that’s absolutely the way we need to be going.

Kenton Williston: Yeah. And I think one point that I can’t overemphasize is, I think when I’m thinking back to the past years and—I have to say, I have so, so loved going to this show. Nuremberg is just such a beautiful city. I really love the old town. The last time I went, in fact, we stayed in the old part of the city, right on the river. We were on the bottom floor of the building that was who knows how many hundreds of years old, and there are all these ducks swimming about, and I could just about reach out and touch them. And, oh, so lovely. I really miss that.

Sally Eaves: Oh, me too. Me too. I’m used to remote working, but I’m used to mobile remote working, if you see what it means? So that’s—

Kenton Williston: Exactly. Yes.

Sally Eaves: But, yeah, absolutely. I really miss the socialization aspect of events and things, but I must admit I’m really impressed by how the agenda for this has been curated. There’s a real strong attention to detail there, and opportunities to build that network connection and match people together. So I really like what’s been done in terms of curating the event.

Kenton Williston: Yep, absolutely. Absolutely. And the thought that got me on our little rabbit trail here was thinking back to previous years. A lot of these trends, like I’ve been saying, are kind of longer term, but I think something that has changed here is just how pervasive the AI element is in just about every single space that we’re looking at. And there’s some really fun and interesting examples. I’m finding AI cropping up in places that I wouldn’t even expect, despite the fact that I’m constantly in this space thinking about IoT applications. It still surprises and delights me to find out where and how it’s being deployed.

So, I saw a couple of examples from ADLINK, where they’re going to be demonstrating how they use AI to inspect contact lenses. And as a guy who’s just going out to get their latest prescription, I really appreciate that. Someone is making sure those are very well made. And even things like palletization of items for shipping, and automating that process, and automating the tracking of things within a pallet. It’s just—no matter what kind of application, big or small, it’s like AI has a way to help out it seems like just about everywhere.

Sally Eaves: Absolutely. I couldn’t agree more. And supply chain. I think one of the things that’s come to the fore so much over the pandemic—and in some cases the fragility around that—and embedding a transparent audit trail. I’ve seen some really interesting things with AI and blockchain coming together. And, again, we were talking about actualization earlier. I think in blockchain, in particular, it’s something that has been associated with particular use case studies more than others, but it’s shown the real art of the possible now, and really tangible, actionable case studies. So that marriage, for want of a better word, between AI and blockchain I think is one to watch as well. It’s been really heightened. I think trust has been built over this process. So pharmaceuticals, for example, would be a classic example of that.

Kenton Williston: Yes, absolutely. Absolutely. Another thing, too, that I think is worth adding to the mix here—speaking of the trust—there’s also the safety element of things. So, as exciting as it is to see this amazing intelligence being applied in all these amazing creative ways, there’s also a lot of, I think, caution that we should exercise as technical professionals about how we’re deploying these technologies.

And, I think, particularly as we’re increasingly automating systems and making them hands off. So here in the States, for example, there was just a story where someone had accessed a water treatment plant and increased the amount of lye that was going into the water, which normally would just handle the acidity and get it to a reasonable pH balance, and they had increased it to—it was either 100- or 1,000-fold the desired amount. And it was just a coincidence that someone happened to be in the plant looking at a screen while someone was in there maliciously mucking about, that they caught that. And that sort of thing is scary, right? And I think reasonably so.

So, I think for all of us to be thinking about putting the safeguards around this amazing technology is also a very important consideration going forward. And one thing that comes to mind for me there as an example is Intel and its latest hardware platforms: the—what’s been known as Elkhart Lake, now as the—Atom 6000 Series incorporates some functional safety technology to help in the physical world keep things safe. And I think that’s very, very important. And there’s a really great demo from NEXCOM showing exactly how that works, and how you can deploy that in all kinds of different applications to keep things from causing harm.

Sally Eaves: Absolutely. No, I think that’s one of the absolute key issues of the entire year. And I think in certain sectors around manufacturing, operational technology, health, education—there’s been such an increase, I think it’s around 300% increase around identity attacks over the past year, as one example. But I think we’ve also seen where, for example, there’s been continual investment in infrastructure, but maybe less so around patching and around refreshes. So that’s created an area of security vulnerability as well. So, so much lookout there, so that sounds a really, really excellent investment and advance. So it’s great to hear that.

Kenton Williston: Another thing that comes to mind for me is, I know that ethical AI is something you’re passionate about. And I think, just on a personal level, it’s something I care about as well. So, I’m based in Oakland, California myself, which is known as a hotspot for, let’s say, socially progressive sorts of movements. And there has been just recently here, in the past week or so, some movement among the activists in this community to stop the Oakland Police Department from using automated license plate recognition—which I’ll leave whether that’s a good idea or not for the listener to decide—but I appreciate very much the ethical challenges there.

I mean certainly these kinds of technologies have been abused already, and there’s potential for abuse for sure. Facial recognition has also been, I think, a really, really hot and hotly debated topic. And I know we’ve been talking about software packages that can help with AI. And Intel, I think, has done a really fantastic job with its OpenVINO platform, pre-packaging a lot of commonplace AI workloads together. And they took the step of actually removing any of the facial recognition elements from those packages, just to really say, “Hey, let’s take a pause here and think about how these technologies can be best deployed. And see what we can do to address issues of things like racial profiling, and the differences in how well these things perform depending on your gender and ethnicity, and so forth.” So I’d love to hear some of your thoughts on these issues.

Sally Eaves: Absolutely. And one thing I’d also applaud there is Intel have done some really good work about building an ethical AI toolkit, and they’ve got some really great examples there, and it’s backed up by research with Stanford and other places as well. So, really, really impressed by that, because I think leadership in this area is so, so important. And I think one of the things that’s also impressed me over recent months is a bit of a change in the narrative around this.

So, in the past when we talked about AI there had been quite a lot of headlines that were quite scary. It would focus on—if a research report came out—it would focus more around words like “destruction” and “elimination” around certain types of jobs. But what we’ve been able to see over the pandemic experience is some fantastic examples of collaboration. So, one of those that springs to mind for me would be the HPC Consortium—so, the High Performance Computing Consortium—of which Intel is a member.

And it’s a great example of leading tech companies coming together—partnering up with research and academia and governments across the world as well—and really coming together, and that ethos of tech-for-good collaboration—basically to bring computing capacity, to bring computing power together to look at how we can better fight COVID-19. So, I think that’s a great example of turning the narrative on AI as something for good. And to support that further, to build that momentum of greater trust around AI—I think for me it’s ethical development and aspects like the explainability of AI which I think is really, really important. I’ve seen a lot of work—and I contribute to some of this myself with some of my research—about value frameworks to build common understanding, common language, common commitments about the development of AI, but I also think this comes down to education.

People have to be empowered to be able to ask the right types of questions, and we need to get better diversity of teams into who’s building AI as well. And that goes beyond aspects like gender, to all sorts of different characteristics—but diversity of experience, it matters so, so much. And every piece of research going and, you know, our practical experience as well—the teams that are diverse are happier, they’re more creative, they’re more satisfied, and you get so much more innovation and you reduce the risk of implicit bias as well. So that has to be the way to go forward.

There’s been a lot of research by groups such as Endelman—they benchmark trust, for example, over at least 17 years now—and even before the pandemic it was a low ebb across all sectors, even around charity, for example, as well. So there’s always been a lot of work to do here, but I believe that the positive things we’ve seen coming out over the last year—let’s harness that. Let’s build a contagion of change around these types of subjects. I’m really, really super passionate about social impact and around inclusion. I think we can really build on what we’ve seen here, and some of the collaborations and the movement forward, and really make this a change for good.

On the technology side, I’ve also seen some developments, for example, helping end users have a better understanding about why a specific result’s been generated, helping developers be able to more easily debug and tune and optimize their models. So we’ve always had a trade-off between accuracy and explainability in driving model selection—particularly obviously in highly regulated environments as well. So seeing enhancements around interoperability, and with bias and explainability tools across all stages and model development, I think is hugely important. And things like shapely values—the ethos of that around visibility and transparency into model decision-making is so, so important. I think it can help shorten the path to success for us all.

Kenton Williston: Yeah, absolutely. And obviously—even from my own personal experience I have found the diversity of folks that I work with on this insight.tech program to be really wonderful in terms of opening my eyes to all kinds of possibilities, and just having people come from such different perspectives. Currently I’ve been saying, as much as I am really deeply immersed in this world, there’s just so many things that constantly surprise me nonetheless. And I think having this diversity of perspective is just incredibly valuable for that.

Sally Eaves: Absolutely, absolutely. It’s enriching in every aspect, isn’t it? It really is, and the foundation of Aspirational Futures I mentioned at the top, that’s what we specialize in a lot—really democratizing access into tech careers, which I think is so, so important for the future and building those skills and skills confidence as well.

Kenton Williston: Absolutely. And so I want to just mention in passing—all of these different factors—I think there’s some really good examples of how they can be applied. So, there’s a demo from a company called EverFocus that is offering an in-transit network video recorder box that incorporates analytics—both forward-looking onto the road to see what’s happening in traffic and help the driver perform at their best, and to help the folks who are routing all the transit vehicles understand what the situation is on the ground. As well as inward-facing to understand what’s happening inside the transit vehicles and help make sure everything is secure and everyone is doing just fine. And of course these days lots of new concerns—like making sure everyone’s masked up.

So, I think this is a really good example of, you could take some of these things that are potentially problematic, like the forward-looking cameras potentially doing some things that you may or may not like—to recognize people and cars and such on the road—as well as the inward-looking, recognizing people in the vehicle. I mean, there’s potential for misuse there, but there’s also potential for really amazing benefit in terms of keeping people safe and healthy, and cities running efficiently and minimizing their carbon footprint. So it’s all about how you deploy it. And I like this EverFocus demo as a kind of example of how to do it the right way.

Sally Eaves: Absolutely. That sounds fantastic. And I think enabling all voices to be heard in that as well. There’s a great example coming out of Helsinki at the moment, which is very much like that demo you were describing there, but ensuring, for example, different voices—so, citizens inputting to the development of their city. So, the example you were saying there about the city development environment and mobility—I think we’re seeing some great things. So what you were just describing there, I think, would be a great fit for that use case.

Kenton Williston: Yeah, absolutely. Absolutely. So, to just kind of wrap a bow around all of this, again, for me as I look forward to this show—and I should mention, too, for our audience that you and I will be live Tweeting some of the sessions. So, absolutely—let me try saying that again. So I should mention, of course, that you and I will be live Tweeting some of these sessions, and I absolutely invite our listeners to come join us on Twitter—follow along as we explore what’s happening as it goes down.

Sally Eaves: Absolutely.

Kenton Williston: Yeah, absolutely. So, on the whole, I’m very excited to see for myself where things are going as the industry gets more complicated, more sophisticated. But I think, for me, there’s an overriding theme here that I opened with, of bringing together so many different technologies that have been in development, on the horizon—whether it’s AI, whether it’s 5G, whether it’s safety and security—bringing so many of these things together in ways that I think really are noteworthy, and notably different than what I saw last year at this time. How about you? What are you looking forward to?

Sally Eaves: Absolutely, absolutely. As I said earlier, I think there’s a real acceleration in innovation, and around the actualization. The speed of change has been unlike things we’ve seen before, absolutely. So, I think there is a real step change this year vis-a-vis the one before. So I think that’s really, really exciting.

One of the sessions I’m going to definitely be looking at is Peter Fang—who’s talking about bridging Orchestrator and hard, real-time workload consolidation. I think that’s a really interesting one—with Edge computing, smart factories. It’s really pushing that demand for consolidation orchestration across mixed and critical workflows. So that’s definitely a session I’ll be looking at in detail.

But there’s so many. It really is a kind of smorgasbord really, isn’t it? Fourteen sessions on Internet of Things, platforms and applications—just fits into a lot we’ve been talking about in our conversation today. But I think what I like about this is it’s five days long—you can really pick and mix this, tailor it to your particular organization and also what you want to learn about. There’s so many opportunities to really dive in deep and ask questions.

I also like the matching application they’ve put together as well. So you can really tailor it. It feels like a proper personalized experience. So that’s really exciting because, if you can’t be there in person, then making an event feel like a true interactive experience matters so much. And I think there’s been a real effort around that curation. So I love to see that.

Kenton Williston: Fabulous. Well—should our listeners be coming to this podcast after the fact, where can they find you online?

Sally Eaves: That’s a great question. Well, I think the one to go for, number one, would be @sallyeaves on Twitter, but I’m on all major channels, basically. But Twitter is the easiest starting point. But LinkedIn, my own website, etc., as well. And I’ll share details after the podcast.

Kenton Williston: Lovely. All right. Well, that just leaves me to thank you for joining us today. Really appreciate all your insights.

Sally Eaves: Absolute pleasure. Thank you so much. And really looking forward to the event.

All right, we’ll see you there.

No-Code Platform Automates Supply Chain Efficiency

Global supply chain executives have long struggled to gain visibility across suppliers—and to translate that visibility into action. The COVID-19 pandemic has only intensified that challenge. For example, some vaccines must be shipped and stored at extremely low temperatures, prompting companies to seek new cold chain monitoring solutions.

As lockdowns and travel restrictions continue to disrupt supply chains around the world, companies are scrambling to find solutions that allow them to deal with interruptions before they cause problems. IoT sensors and data management platforms hold great promise but can be difficult—and time-consuming—to build and integrate. To yield the most value, companies need solutions that are simple to deploy and can integrate easily with existing systems and data streams.

D.W. Morgan Company and its technology subsidiary ChronosCloud make these solutions a reality. Morgan has long been a leader in transforming supply chain efficiency with better data. Its all-in-one automation platform ChronosCloud, paired with Intel® Connected Logistics Platform (ICLP), provide a flexible solution for companies that need better supply chain visibility and control. The solution gathers data from IoT/ICLP sensors, carrier sites, APIs, and a mobile app, allowing managers to build a clear picture of their supply chains.

Perhaps the most advantageous aspect of the automation platform is its ability to give companies a comprehensive understanding of their supply chains, with partner updates, documents, photos, and IoT device data all in one place. That can be an overwhelming amount of data, but it’s easily customized to the needs of different professionals on a team.

While it may be a struggle just to integrate data, ChronosCloud achieves this as a baseline and then focuses on solving real-world problems. The solution proactively manages exceptions and potential issues—accelerating the supply chain by coordinating partner actions, speeding revenue recognition, and reducing insurance costs and claims.

The solution gathers data from IoT sensors, carrier sites, APIs, and a mobile app, allowing managers to build a clear picture of their supply chains.

IoT Sensors Track Goods Along the Way

Companies have different needs when it comes to supply chain visibility. Some want to monitor the entire route of a product’s transit from Singapore to New York, for example. Others may choose to focus on one portion of that journey, such as the last few miles from the airport to the warehouse. Because supply chain managers need different information, automation platforms must allow users to request personalized dashboards based on particular data sets.

The solution also includes automation features, making it easy for supply chain professionals to manage by exception—creating alerts that notify them of a potential issue so it can be addressed quickly. For example, a user could ask to be notified of any order that has not seen an update for 48 hours.

“Having access to real-time alerts allows supply chain managers to be proactive in addressing problems,” says John Hoyt, managing director at D.W. Morgan Company. They can also use the solution to communicate across their supplier base, sending automatic notifications to key people about pertinent events in real time.

Using ICLP sensors, managers can track changes in shipping conditions along the route, such as tilt, light, and temperature. “You can take corrective action right away if a shipment is damaged rather than finding out after it’s traveled halfway around the world,” says Hoyt. And this type of data helps paint a clear picture for insurance claims.

No-Code Integration

Supply chain managers look for solutions that can integrate easily with other business systems, such as ERPs, and require minimal coding efforts to adapt. For example, ChronosCloud users can choose to access data through the solution’s system and dashboards—or import the information to their applications and systems. “Because it was created by supply chain professionals, our solution is built to be flexible in the right places,” says Hoyt. “We can tailor it to meet our customers’ needs.”

Cold Chain Technologies in Action

How does a supply chain automation platform work? First, a company must decide which type of IoT sensors it will attach to pallets or shipping containers. While individual IoT devices that detect conditions such as light and temperature are often expensive, ICLP uses a general communication gateway paired with low-cost tags that are attached to shipping pieces. “The tags are all independently monitored and fed through the gateway device,” says Hoyt. “This arrangement is a unique and cost-effective alternative that gathers the same data.”

The company must then decide which other data streams will flow into the platform. That additional data might come from business systems, directly from carrier sites, or through a mobile app. For example, the ChronosTouch app allows truck drivers to enter information from their smartphones, including GPS data and other reports. Users can also add photos of shipments en route. If a box has been damaged or mishandled, it can be documented with a picture and added to the platform.

Once data is flowing into the platform, supply chain managers create dashboards and set tolerance levels to manage automation and alerts. For example, if food suppliers are shipping ice cream, they need to make sure temperatures do not rise above 35 degrees in the shipping containers. They can set the tolerance level to the needed range and will receive an alert if the temperature climbs above the threshold.

“It’s a single source of truth for everyone,” says David A. Morgan, sales and marketing manager at D.W. Morgan Company. “Users can hit ‘follow’ and receive only the alerts that apply to them.”

Platforms such as ChronosCloud that integrate easily with other data streams make the adoption process very swift. “One customer had us integrate five different partner interactions between mobile, IoT, and connected tracking with carriers from a manufacturer in Malaysia to a final destination in California,” Hoyt says. “It was set up and ready to go in less than two weeks.”

Maximize Efficiency, Minimize Loss

Amid a pandemic, an effective supply chain with the potential to get life-saving materials where they’re needed and on schedule is paramount. And with improved visibility, companies are better equipped to monitor shipping conditions and anticipate problems like spoilage, damage, and delays—and deal with them in proactive ways that minimize loss.

Quantum-Resistant IoT Security

A conversation with Louis Parks @Veridify

[podcast player]

Many IoT systems remain in the field for years or even decades, creating major challenges for security. Building automation and industrial systems are prime examples. Conventional IoT security techniques may be sufficient for now, but advances in technology like quantum computing will soon break popular methods like ECC and RSA.

What’s the best way to protect valuable infrastructure in the long term? Join us as we dig deep into this question with Louis Parks, the Chairman, CEO, and co-founder of Veridify, the creator of quantum-resistant, public-key security tools for low-resource IoT environments. We discuss:

  • Why technologies like firewalls are difficult to deploy in multi-vendor IoT systems
  • Why device authentication is a critical element for building and industrial IoT security
  • How to use bump-in-the-wire security to retrofit legacy infrastructure
  • Why quantum-resistant encryption is needed for long-term IoT security
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Transcript

Louis Parks: We need to be thinking about: we can keep a building safe today, and certainly for the next five, six, eight years, but how do we keep it safe for the long term? And that’s where you will need to turn to quantum-resistant methods.

Kenton Williston: That was Louis Parks, the Chairman, CEO, and co-founder of Veridify. And I’m Kenton Williston, the Editor-in-Chief of insight.tech.

Every episode on the IoT Chat, I talk to industry experts about the technology and business trends that matter for developers, system integrators, and end users.

Today I’m talking to Louis about the security challenges for smart buildings and industrial automation, and some cool new ways you can lock down your assets—including the quantum-resistant cryptography Louis just mentioned.

Louis, welcome to the show. Can you tell me a little bit about yourself and what Veridify does?

Louis Parks: Sure. Good to be here. Veridify is focused on security for very, very low-resource devices, and really has been since its inception. And what I mean by that, since security’s a very big landscape, we’re focused on identification and authentication—which, not always working—but we take it for granted when we do our banking and do things on large, powerful platforms like PCs or smartphones. But when you have very, very low-resource processors—perhaps in an embedded device or in the Internet of Things—authenticating them and knowing they’re your device can be difficult. So we develop methods for doing that type of authentication identification.

I have three partners who are mathematician-cryptographers and specialists in the area, who helped develop these very efficient protocols. And I’m a co-founder of the company, who helps in figuring out how we take these things to market and turn them into the products that we market today.

Kenton Williston: So, this is a really interesting topic and a timely topic, I think, because the just general security landscape has been—it’s an ever-shifting landscape, to be sure. But I think last year, with the pandemic and people moving to remote work, there’s been just a real, I think, significant shift broadly on the sort of threats people are encountering. So I’m wondering, when it comes to the areas you specifically are looking at—things like industrial IoT and building automation and control systems—how you see the landscape shifting in those specific areas.

Louis Parks: Sure. Well, so first of all, the change in how we work has really brought attention to the whole idea of security. Privacy, of course, is something that comes out of that. But the idea now that—whether it’s your video call on whatever platform you’re using, the ordering, banking, what have you—suddenly we’re all aware that it’s a very digital world, from retail to socialization. So that’s a heightened awareness that we’re operating against.

What we see now, and what has continued as a level of sophistication—because as we’ve tried to connect more things together to make it efficient, so we could work remote, work from home, make the supply chain more efficient, whatever—has given a broader horizon for the hackers and attackers out there to infiltrate and/or go after things. Our focus, again, is on the small devices that run these things.

Specifically, we’ve been very busy the last year in the area of building security. That’s not getting into a building or the cameras on a building, but rather the fact that for years, and even more than decades, buildings have relied on processors to manage the heating system, the HVAC systems—more recently, the lighting systems and the elevators. So even before the term “smart building” came into vogue, buildings relied on processors.

And in fact, unfortunately, as those have been now connected to the IoT, it’s given another access route for an attacker to get to the IT systems in the buildings, and places where valuable data may be. So, really, as we’ve gotten so much more connected and better at operating digitally, so have the attackers.

Kenton Williston: Yeah, absolutely. And, like I said, this is not exactly at an all-new trend—it’s something that’s been happening. This example’s getting pretty dated by now, but people have been talking about, like the Stuxnet attack as an example of how the security landscape is not just about the servers, but it’s about all the equipment that’s out there.

I think it’s fair to say there’s a broad sense that, hey—you’ve got to protect your IoT systems. But I think it’s also the case that people don’t really fully appreciate all the time just what exactly the threat landscape is. So I’m wondering, from your point of view, are you seeing some significant risks that people generally are not aware of?

Louis Parks: Oh, absolutely. When you talk about attacks, and what have you, the threat landscape goes back before we got the label “IoT.” I remember well over 10-plus years ago being in Washington at a meeting where they were discussing technologies to help with border security. Many people listening to this and maybe on the podcast have a car where you can look at the air pressure in your tires on a dashboard or in a display to know if the air pressure’s good or not.

That technology comes to you courtesy of RF (radio frequency), little broadcasters in the wheels talking to your cars that have been paired. And if anybody’s had a damaged wheel, like I have, you know that the dealership will charge you dearly to pair a new wheel to your car. But because it’s RF (radio frequency), it’s not only talking to your car, but it’s broadcasting outbound too.

So the discussion was, “Gee, people are driving across the border. Perhaps we could use that broadcast, that radio-frequency broadcast, as metadata to identify a vehicle.” So, that’s arguably a friendly use, if we believe in border security. But the point being is: that is what would now be considered an IoT device. A car itself is probably, to many people, an IoT thing now. So, these threats have been around for a long period of time. And probably a lot of people have not thought about their wheels on their car betraying them to somebody for the purposes of location, or tracking, or other nefarious activities.

Kenton Williston: Yeah, that’s a great example. I’ve got a pretty old beater myself, so no RF in my tires, but I have to admit that that was a security risk I was completely unaware of until you mentioned it just now. Now, having said all that, our audience is probably smarter than me, very well aware of the many different security risks that are out there, and doing a really good job of trying to secure their IoT systems. So, I’m just wondering, from your perspective—to the extent that there ever is any such a thing as a standard approach to anything in the world of IoT, where every system is a little bit different—what the standard/typical approach to security looks like today. And where you see it being strong, and where you see there being some gaps in the current approaches.

Louis Parks: There’s a couple of things that you want to do, or people are doing. And, in general, there’s a lot of attention being paid now, unfortunately again, because the news is not always great. And we always get reminders—although not IoT—things like SolarWinds remind us that if we’re going to be digital, we are all potentially susceptible to various types of attacks.

The challenge in IoT is significant, in the sense that we have a really wide range of devices—whether you look at industrial, whether you look at a commercial building, or a home—because the devices, number one, may come from many vendors. We’ve all seen the value of a single-vendor solution and the ability to control your world if you come from Apple. And then the value from a marketing perspective if you allow many players to play, like in the Android world. But at the same time, ensuring that all those players are good people.

So in the IoT, when you have a mix of technologies, it becomes a challenge. People are understanding that more and more. So there really isn’t one security thing that you should do. There’s probably many. Certainly the first thing is to know if you have an issue, and there’s a lot of really good anomaly detection, network-monitoring technologies, that are being developed. So that people who want to know, or should know, if they have an issue can know. That doesn’t prevent an attack, doesn’t prevent somebody from stealing data. But, arguably, a very critical issue to know is—is it happening? So that you need to increase or improve whatever it is you’re doing.

Of course, all the other technologies have been around for years and decades. Whether it’s malware protection, firewalls—on and on the list goes—you need to employ when you’re talking about networks. But the IoT and a lot of devices, number one, operate outside of these very controlled networks—the three floors of your office building. A lot of these devices are out in the open.

The other thing is that a lot of these devices are engineered or designed very eloquently to use absolutely the smallest processor that will deliver all the features. So one view of some of the audience might be, “I have all the tools I need. I’m using them today.” They might be on a tablet, or a gaming PC, or a smartphone.

But when you go down to a very, very small 32-bit, or 16-, or even 8-bit processor that’s been optimized to provide a single function in a building or embedded platform network, you don’t have the luxury of the computational capability to put that authentication technology on it—to put that digital certificate and all of the signing and verification capabilities on it that you take for granted—the TLS or SSL solutions you use when you’re on a network.

So there’s a lot of attention being paid to that. There’s a lot of innovative technologies: from how do you take public-key or asymmetric technologies, as we do, both legacy things like ECC or ECDSA—which some of your viewers will know are 30- 35-year-old technologies that still lead the way for legacy—to upcoming quantum-resistant methods. How do you shrink them and make them work? As well as other technologies like PUFs—physically unclonable functions—which are fingerprint technologies, and enable you to provide unique identification on a per device basis, or a seed of identification, a root of trust.

So there’s really a lot of areas that are being brought together, again, because you have a really, really broad mix of devices. And a lot of them need to be out there by themselves, which again is why we focus on device-to-device as an area. But you would not look to us as a single solution. It would be us in combination, arguably, with some of these other technologies to make yourself secure.

Kenton Williston: Yeah, so let’s talk about your solution a little bit, because, like you said, I think when everything’s said and done one of the biggest challenges you really pointed to is—whether you’re talking about an industrial setting or a building-automation setting—you’ve got a landscape with a lot of existing legacy devices that aren’t going to go anywhere anytime soon. You’ve got a landscape with a lot of things that were designed for minimal cost, minimal power. So, what are you bringing to the table to help protect this very diverse, fragmented landscape that’s not really set up, like you said, for the kind of things you would think about in, like a data center or your own home PC kind of setting?

Louis Parks: So, pretty interesting, and we’ve been immersed for about a year now with our platform, DOME, that we developed a few years ago as a platform for device management, not unlike many IoT-product or device-management platforms that are out there. The difference, again, with ours was we were using, or we are using, the ability to shrink protocols, asymmetric or public-key protocols, that allow authentication capability down to fit on the actual device. So a device in the IoT, or a device out there, can actually manage its credential, manage its authentication, without the need to connect to a cloud or a server to do that.

Of course, connecting to a cloud and server is a very valid way with larger devices that come embedded with URLs to authenticate them. But, again, if you have a very small device it’s only going to operate in a limited network, but could provide an exposed platform. That was something that we were focused on.

So we developed DOME, a device ownership and management solution, where we manage a credential in the cloud in a blockchain for the device. But the device actually challenges and ensures it’s talking to something authentic. We took that and translated it to the building-automation world, where a building, again, as I mentioned earlier in the podcast, for years has run on processors managing elements of a building’s operation today.

And, of course, it’s getting even more sophisticated. There’s some really brilliant use of technology to make building smart, more comfortable, more adapted to our use. All of that involves introducing more processors on the operational-technology side. To manage them you connect them to the IT side. Of course, in the IT side is where we find the networks, and then the databases, and the back offices of the people in the building. That’s where the danger emerges. So that has been an interesting challenge and a great use.

There’s one additional element you alluded to, or may not realize you alluded to, and that is that 99% of the market that we’re talking about protecting exists. It’s already there. The buildings have been built, they’re running. So if you’re designing a brand-new smart building today, and if you were just fresh on the plane back—well, you wouldn’t be fresh—fresh off your Zoom or digital call from CES with ideas for all the new technology going to put in it, likely there’ll be some good security tools.

But if your building’s only two, three, five years old, you probably still want to use that very expensive air handler cooling system, what have you, you have installed, but it probably has not got the protections you need. So retrofitting security to a preexisting infrastructure is also a challenge, and something that we’ve addressed with something we call bump-in-the-wire technology, that we’d looked at for a period of time. And, in fact, developed some solutions with our partner Intel to deliver to industrial IoT, and have now adapted it for the building-automation protocols like BACnet, and later Modbus and KNX, to retrofit security to a preexisting infrastructure—in this case a building—which is another challenge in making things secure in current days.

Kenton Williston: Yes, I want to dig into that a little bit more, and here is just a little shameless plug. We’ve got an article that corresponds to this same conversation over on insight.tech, so I encourage our listeners to go check it out. You can get more details on this bump-in-the-wire solution, how it works, and why you might be interested in it. But, just to look a little bit closer at that here and now, can you tell me a little bit more about what this architecture looks like? And you mentioned that it’s got some Intel technology—what kind of technology is incorporated there?

Louis Parks: Sure. So bump-in-the wire’s not a unique solution to us; many industries and areas have it or contemplated it. What we’ve done here—a couple of things that are unique. Number one, we’ve based our initial solution on an Intel FPGA—a small, very powerful, low-cost FPGA. So not only does it ensure that we can address the security issues today, but an investment in this relatively low-cost device will give us the adaptability going forward—because the horizon for the attacks, the nature of the attacks, is continuously evolving.

And, typically, as you’ll see in many, many articles when they talk about buying something that’s connected, or the IoT, they always say, “Make sure you have a way to update to the latest patches and fixes, and what have you.” So not only do we have a very powerful platform to provide the technology, but we have one that’ll allow adaptability.

For the building space what was critical is that we had a relatively simple plug-and-play solution. So it’s a simple plug in plug out between the controllers and the Edge devices that are already installed—typically running on some sort of IP platform or network in the building-automation space. Our initial solutions are designed for the BACnet world, which, again, is a building-automation standard for how devices and buildings communicate.

So, our device is running; it runs the initial ones, NIST-approved, legacy—what I refer to as legacy protocols and methods for certification purposes. But other versions of it will run a quantum-resistant crypto—and we should talk about that for a minute—which is critical for long-term protection. And of course, finally, this is BACnet, which is a building standard. It runs over BACnet IP. We’ve developed other technologies that coordinate with it to ensure that you can also monitor the discussions that are going on.

The summary is: we were creating a secure tunnel from the controller to this bump-in-the-wire device with encrypted data flowing over a BACnet-compliant communication. So we don’t replace anything that a building currently has, or anything in the standard. Then it protects the device it’s plugged into behind it. So, that’s a very simple description of this device. It’s designed to be flexible in the protocols it manages, and what have you. A lot of that power and flexibility, again, comes from the ability of having this FPGA-background platform that will allow us to adapt it. And so, unique functionality capabilities, as we move through the building space.

Kenton Williston: You’re talking about this bump-in-the-wire solution protecting the device that’s behind it. So, are we talking about something where you would need to deploy, like a one-to-one everywhere you’ve got a device you’d want one of these bumps-in-the-wire? Is it per floor, per building? What’s the architecture look like?

Louis Parks: The architecture needs to address a couple of different scenarios. We would suggest the ultimate protection, of course, would be one-to-one, and ensure that every device has this secure, encrypted element—authenticating all the inbound traffic, and encrypting and delivering back all the outbound data back to the controller in the building. That’s not always possible, or feasible, and sometimes it’s just probably not the right architecture.

So, although we do have these relatively low-cost, powerful, FPGA bump-in-the-wires, we also have a similar technology in a router form. Again, the secure connectivity—which we call S Link—so we can run it to a router, which then could have several devices. So it could be a one-to-one, or one-to-many configuration—as is exactly what you find in the building spaces today.

Kenton Williston: That makes sense. I do want for sure to ask you about the quantum cryptography. So, this is certainly, if you’re up to speed on the latest and greatest security, a hot topic. But in some ways it kind of feels like, “Gee, if we’re just talking about a building-automation system, isn’t this really kind of overkill?” So, what’s the rationale behind this, and why have you taken this really hardcore approach?

Louis Parks: Sure. It’s not overkill. As a matter of fact, in addition to providing DOME with NIST-approved methodologies, we—ourselves and my partners, their background is in the mathematics of asymmetric and public-key methods—we’ve developed and published methods which are quantum resistant, as well as we are working with several methods that NIST now has under review for the purposes of standardization.

But focusing just on the question about quantum resistance—again, many of your listeners will be aware—but quantum computers since the late ’70s, early ’80s, were a white paper/physics idea that was out there. And about three, four years ago, actually maybe five now as I think about it, IBM and MIT simultaneously managed to create working prototypes. Now, these are not full-functioning, or were not at the time full-functioning, but proving the science, the technology, behind a quantum computer.

And again, these computers are not in the future going to replace our current computing. It’s a different type of computing. You’re probably not going to have a smartphone running on quantum. But they do manage and process data differently than our current conventional computers. And, again, there’s a lot of articles—it’s years later—many of your readers would be familiar with it. But the reason we’re talking about it—and they have evolved, and they’re getting better, and they’re getting more stable, and they’re getting larger, which is a key element. So they become more practical to use—likely in a data center-type fashion. So they will be great for solving DNA-sequencing issues, discovery of new drugs, etc.

And, unfortunately, there are at least two algorithms that have been developed to run on quantum computers that have been mathematically proven that will attack a weakened—and in one case, break—the legacy methods which I’ve referred to a few times—elliptic curve, RSA, Diffie-Hellman—when you have a large enough quantum computer. So, the part I can’t answer—and it’s hard for anybody—when will that be? It’s not next year or the year after. Could it be five years out, or seven years out? Don’t know. People commercially are working on it, as are nation states. So, it will happen, but we don’t know the timeframe.

Which brings us back to the discussion today on a building, where you put up a building—not unusual to stand for decades, if not 100 years-plus. Arguably the systems get replaced, but they get replaced every 15, 20 years. So a system going in today will likely be around when there’s a large enough quantum computer. And that quantum computer will break the ECC or the public-key methods. You cannot increase the security of ECC or RSA to avoid it. They will actually be broken by Shor’s algorithm in particular, and weakened by Grover’s algorithm.

So we need to be thinking about: we can keep a building safe today, and certainly for the next five, six, eight years, but how do we keep it safe for the long term? And that’s where you will need to turn to quantum-resistant methods.

Kenton Williston: Makes sense. Then the follow-up question there, is: why use FPGAs for this role? Is there something particularly advantageous that they offer?

Louis Parks: I guess the fair answer is, yes and no. So, there are equal processing-capable technologies and microcontrollers and ASICs, and one could even argue in some cases even more optimizable technologies than an FPGA. But the critical element for what we’re doing today—and I think for a lot of the building space, which we have found to be years behind where the general processing community is, and certainly years behind a lot of the new IoT—is we’re providing the tools that we believe and think are critical today, and that landscape is shifting.

I think the key characteristic of the platform that we’re operating with is that it’s field programmable. So, we’re delivering solutions that are going through third-party testing and all the verifications you want to make sure that they’re secure, but will also give us the capabilities to adapt these devices, not only to different building and industrial IoT operations, but also to adapt to the market, and the threats, and the nature of what we’re looking to address, as we’ve been discussing.

So, although in some cases—certainly people are probably familiar with FPGAs—they can cost 1,000s of dollars, the ones we’re working with—and in particular with our partner Intel— are still powerful but are a fraction of that cost. So there is not a penalty from that side, but there is a significant dividend from the flexibility and our ability to address the market.

In some cases, even specific projects that we’re working on, where we’ve had discussions with building owners—sophisticated building owners, who have very extensive networks operating already within their buildings, understand all the operational technologies—and they have several requests that frankly we hadn’t contemplated in the basic platform, but because we’re working in the FPGA world we can answer, we can deliver. So we think it’s an ideal solution that the cost benefit—there is significant benefit from this FPGA approach.

Kenton Williston: So, I’m glad you mentioned the cost aspect, because I think historically there’ve been two big factors that have caused people to shy away from FPGA solutions. So, one is certainly been historically the cost—although, like you said, today there are a lot of very moderate-cost solutions that are available. The other, though, has just been the programming model. The way you configure an FPGA is very, very different from how you would program a microcontroller, for example.

So, if I were considering how I wanted to secure my building or my industrial systems, the thought of adding an FPGA in there I could see making me a little nervous, like, “Is this going to be something that I’m going to actually be able to manage? Or is it going to require me to learn a whole new skill set?” So, what do you say to that?

Louis Parks: So, first of all, to a lot of the industry this process will be obfuscated because we’re working with other partners, and this is their area of specialty—developing products and solutions based on FPGA technology. So, again, where the functionality of the device does need to be provisioned—whether it’s a microcontroller or an ASIC, and the other partners and other areas where we are doing similar solutions at a microcontroller setting—the FPGA, when it’s being provisioned both with the functionality of the platform will also be provisioned with the security technology.

So, again, it may not have the overall efficiency en masse for deployment, but the vendors who are working with it have the basic tools for doing the volumes that we’re talking about here. So, again, I think it’ll be proportional. If this was a high-volume consumer, low, low, low, low cost—yes, this would create probably a larger component of the cost of the device. So, we’re not in pennies; we’re 10s of dollars to low-100s of dollars in some of these cases.

So the provision and costs, I think, are proportional to the device. And certainly, again, the overall payback for this type of platform—I think certainly in the early stages of this industry—is easily there. This has not been an issue so far in the projects that we’ve been looking at or working with.

Kenton Williston: Got it. Great. So, I think we’ve covered a ton of ground here. So I’m going to ask you a very challenging question, which is: if you could wrap this all up and leave our audience with like one key takeaway, what would that be? What would be the one message you would want to convey?

Louis Parks: I think the message I’d want to convey is that we all need to have a realization that behind the things we’re using today there are processors. And just because it doesn’t have a screen and a keyboard, or it’s something that you’re not entering your credit card information into, or your banking, you still need to be thinking about security and protection because of the interconnectivity.

And, again, there are many, many examples—way beyond the couple of simple ones I gave, and much more eloquent ones. But I would suggest that everybody needs to stay aware that, whether it’s you’re working from home, or the fact that you can find a car spot easier in a car parking lot because of some new technology, it’s because things are connected and they’re communicating. And when they’re doing that it’s a convenience, but it’s also a threat platform. And they should recognize that just because, again, it doesn’t have your credit card in it, doesn’t mean that it can’t possess an equal threat. We should all be aware, and hopefully be seeking these solutions to try and stay even—maybe even get ahead of what’s happening in the world of attacks and hacks.

Kenton Williston: Very good. Well, with that, listen, I want to thank you for joining us on the program today. Really appreciate your insights.

Louis Parks: Great. Well, thank you for having us.

Kenton Williston: Absolutely.

And thanks to our listeners for joining us. If you enjoyed listening, please support us by subscribing and rating us on your favorite podcast app.

This has been the IoT Chat podcast. We’ll be back next time with more ideas from industry leaders at the forefront of IoT design.

AI Robots Navigate the Smart Factory

By now we’re all familiar with Industry 4.0, and the ways in which connectivity and analytics are being used to revolutionize productivity and efficiency in automation environments. But you might be surprised to learn that Industry 5.0—a world in which humans work with and alongside smart robots—is already on the horizon. And that horizon is emerging in the form of collaborative robots.

These industrial or service robots are independent and operate freely within complex, semi-structured environments.

This is a big step forward from the automated guided vehicles (AGVs), which are still widely deployed today—a common sight in factories and warehouses—often used to transport goods and materials from one location to another. The major limitation of AGVs is that they are “guided,” meaning they follow predetermined paths outlined with lines, wires, tape, lasers, or even computer vision that recognizes landmarks along a specified route.

This makes AGVs excellent at performing repetitive, fixed functions, but not much else. In the evolution to collaborative robots, the first step is the autonomous mobile robot (AMR).

From Automated to Autonomous

AMRs leverage cutting-edge intelligent vision systems and simultaneous localization and mapping (SLAM) software to afford freedom of movement and operational flexibility. The advanced robotic platforms are able to recognize their surroundings, navigate them accordingly, and even identify and avoid objects in their path.

In short, AMRs are more mobile, efficient, flexible, and safe. They can even collaborate with other AMRs to increase productivity, and decommission themselves to recharge when their batteries are low.

Of course, the ability to achieve mobile autonomy is the result of more sophisticated AMR technologies. For instance, SLAM technology requires higher-precision sensors, which in turn require more compute resources to process data and act on it. And building an AMR from scratch based on these components is a complex undertaking that presents systems integrators with many hardware, operating system, and protocol engineering challenges.

“There are a lot of systems integrators that build their own AMR frameworks,” explains Kev Wang, a product manager at Vecow Co., Ltd., a developer of innovative industrial automation products. “But they have to test and verify from the very beginning, which alone could take a team of five to eight people more than three to four months to do so.”

With VHUB ROS, @VeCowCo worked with Intel® and Virtuoso Robotics to deliver a standard framework that gives SIs a better understanding of how to approach AMR design.

Accelerate AMRs with an All-in-One AI Kit

An alternative is to get a head start with a rapid prototyping platform. For example, The Vecow VHub Robot Operating System (ROS) is a turnkey AI development kit that provides systems integrators with a fully integrated hardware, software, and tools stack for accelerating AMR design (Figure 1).

IPC and industrial AMR
Figure 1. The VHUB ROS AI development platform includes a complete autonomous mobile robot (AMR) development stack. (Source: Vecow)

VHUB ROS is the result of a collaboration between Intel®, Vecow, and Virtuoso Robotics, and is compatible with select hardware starter kits based on 11th Gen Intel® Core i7/i5/i3 processors—also known as Tiger Lake UP—and Intel® Movidius VPU accelerators. A Perception software development kit (SDK) layers on top of those hardware targets, and includes ROS 2, control firmware, and an AI engine.

“With the VHUB ROS, we cooperated with Intel and Virtuoso Robotics to deliver a standard framework that gives systems integrators a better understanding of how to approach AMR design,” says Wang.

The AI engine within the SDK gives developers access to more than 200 of the most commonly used AI models, including SLAM, object detection and recognition, and other algorithms. And it works with industry-leading training platforms like Caffe2, mxnet, and TensorFlow.

To prepare these models for use on resource-constrained AMR platforms such as the Vecow EMBC-5000, models trained in these frameworks are passed through the Intel® OpenVINO Toolkit, a cross-platform model optimizer and inference engine.

“We’ve tested the VHUB ROS SDK using CPUs, CPUs with the Movidius VPU, and now CPUs with integrated Intel® Xe graphics with Movidius VPUs.” Wang says. “When we test these platforms with OpenVINO, we see at least twice the performance.”

Deeper Insights for Collaborative Robots

The biggest differentiator of an AMR design today is certainly its on-board AI, which means developers will spend a great deal of time and effort training and labeling AI models in the cloud. To facilitate this, the VHUB ROS SDK can be hosted as a containerized instance on cloud services like Amazon’s Elastic Container Service (ECS).

But since the process of refining AI algorithms is based on capturing inferences from an AMR and feeding them back into the VHUB model training instance, systems integrators need a mechanism for transmitting edge data into cloud containers in real time. To accomplish this, Vecow leverages Intel® Edge Insights for Industrial (Intel® EII).

EII is a containerized software architecture that collects, stores, and analyzes time-series and vision sensor data, then orchestrates and manages it across a variety of operating systems and protocols from the edge to the cloud. It does so securely, and in a near-real-time (<10 ms) closed-loop.

Vecow engineers have extensive experience deploying EII in AI inferencing optimization. They are adept at leveraging the software’s capabilities to maximize the performance of multiple AI functions running simultaneously in real time. The team has already performed research, implementation, testing, and verification of all the AI capabilities, tools, and platforms that comprise the VHub ROS.

This eliminates large swaths of the evaluation and integration lifecycle, allowing AMR systems integrators to move immediately into application design and reducing their time to market by several months.

AMRs: Toward a Collaborative Future

AMRs are poised to transform the automation market once again and usher in an era of never-before-seen partnership between people and machines.

But to reach the potential of these early collaborative robots, organizations will first have to work with technology partners who can simplify the growing complexity of AMR hardware, software, and connectivity stacks to open the door for disruptive application engineering. With turnkey platforms like the VHUB ROS, fast-paced AI innovation is within reach.

Optimize IT and OT at the Industrial Edge

As compute and networking increase at the industrial edge, it can be tempting to deploy off-the-shelf hardware to meet production needs. And with many workloads finding their way to the edge, the temptation can be especially strong. Using equipment that IT departments are already comfortable with—like standard server hardware—is often the simplest solution.

But in the end, this approach is expensive. An IDC survey of Fortune 1000 companies suggests that IT equipment failure can cost organizations upward of $100,000 per hour.

What companies need are systems that combine the performance of commercial offerings with the reliability of an industrial platform.

The latest processors like the Intel Atom® x6000E Series processors and Intel® Pentium®, and Celeron® N and J Series processors—previously known as Elkhart Lake—make these systems possible. As just one example, the processors support a broad temperature range from -40 degrees to +100 degrees Celsius, while operating a sub-12 W thermal design power (TDP).1, 2

This advanced technology opens the door for industrial PCs to function as high-reliability IT infrastructure—eliminating the excessive overhead of planned obsolescence, reducing maintenance requirements, and delivering maximum system uptime.

Designed For the Industrial IoT

The dual- and quad-core processors incorporate a range of improvements over previous-generation devices, and can optimize both IT and OT infrastructure, particularly at the edge. With up to a 1.7x improvement in single-threaded performance and up to a 1.5x improvement in multi-threaded performance3, systems based on the platform can handle a variety of demanding networking workloads efficiently and without any throughput degradation.

In part, these gains are possible thanks to hardware innovations introduced with this generation of processor (Figure 1). These include security integration via Intel® Platform Trust Technology (Intel® PTT) and the Intel® Programmable Services Engine (Intel® PSE), an offload engine that relieves CPU cores from a range of task overhead.

Intel Atom® x6000E Series processors and Intel® Pentium® and Celeron® N and J Series processors Block Diagram
Figure 1. New Intel® Atom® x6000E Series processors and Intel® Pentium®, and Intel® Celeron® N and J Series processors offer a balance of performance and reliability. (Source: Intel)
  • The Arm Cortex-M7-based Intel PSE offload engine provides low-DMIPS computing horsepower and support for Arm-based applications. This enables functions such as remote out-of-band device management, network proxy, low-speed I/O, and real-time processing. It also features time-sensitive synchronization capabilities.
  • On new devices, Intel PTT integrates a Trusted Platform Module (TPM) 2.0 block, which offers cryptographic key generation and storage that pair with the crypto acceleration faculties of Intel® AES New Instruction (Intel® AES-NI).

In addition to the capabilities mentioned above, the Intel PSE enables time-sensitive synchronization, a feature that pairs with Ethernet time-sensitive networking (TSN) support on new processors. This combination is essential for IT infrastructure deployments in many operationalized use cases, since it allows systems based on Intel edge compute platforms to maintain synchronicity with control devices while exposing their data to the broader enterprise network via standard IP packets.

Manufacturers need IPCs that combine the performance of commercial offerings with the reliability of an industrial platform. @onlogic

Translating TDP Into MTBF

Because the devices operate at a TDP as low as 4.5W, they can easily be deployed in fanless, solid-state systems.

For example, OnLogic, a global industrial PC manufacturer and solution provider, uses Hardshell Fanless Technology for its line of industrial and rugged computers. The industrialized system design approach delivers high ruggedization, ingress protection against environmental contaminants, and passive cooling. As a ventless system composed of a 100 percent metal chassis, Hardshell-based platforms use heatsinks to dissipate thermal loads. And because they contain no moving parts, the systems can be certified to shock and vibration standards such as IEC 60068 and MIL-STD-810 (Figure 2).

OnLogic Karbon IPC hardware form factors
Figure 2. The Karbon Series of rugged computers are ideal for industrial IoT deployments. (Source: OnLogic)

“The Karbon series is part of our rugged line, designed for tough environments,” says Maxx Garrison, Product Manager at OnLogic. “The Intel PSE is key to some of our new Karbon 400 unique features, allowing us to provide support for a host of connectivity and power management functions, including CAN bus and automotive power control for in-vehicle applications.”

Testing has shown that Karbon Series IPCs achieve an MTBF of up to 512,681 hours, or more than 58.5 years. “A big part of what we offer is peace of mind so that customers don’t have to worry about replacing systems,” adds Garrison. “They buy our hardened, solid-state systems that allow them to set it and forget it.”

Lower Cost of Operations With Rugged IT Infrastructure

Although MTBF is not a precise measurement of when a given system will fail, it can provide an accurate indication of the level of reliability. And even with a margin of error—the MTBF and cost of a platform like the Karbon Series versus the amount of unplanned downtime with traditional IT equipment—some quick math will prove there is no comparison.

As more and more IT infrastructure makes its way to the edge, network engineering professionals will have to face the realities of environments that aren’t conducive to their traditional infrastructure deployment strategies. But upon experiencing the benefits of industrial-grade IT infrastructure, they may see opportunities to use this equipment in settings other than just the “far edge.”

What do they have to lose—besides hundreds of thousands of dollars per hour in equipment failure?

 

Disclaimers
1 Not all SKUs include every feature.
2 Not all SKUs support real-time computing, time-sensitive computing, or time-synchronous networking.
3 Source: Intel®. Claims based on (a) SPEC CPU 2006 metric estimates based on Pre-Si projections and (b) 3DMark11 estimates based on Pre-Si projections, using Intel® Pentium® J4205 as prior generation.

 

Configurations
Performance results are based on projections as of September 1, 2020
Processor: Intel® Pentium® J6425 PL1=10W TDP, 4C4T Turbo up to 3.0 GHz
Graphics: Intel Graphics Gen 11 gfx
Memory: 16GB LPDDR4-3200
OS: Windows 10 Pro
Compiler version: IC18
Processor: Intel® Pentium® J4205 PL1=10W TDP, 4C4T Turbo up to 2.6 GHz
Graphics: Intel Graphics Gen 9 gfx
Memory: 16GB LPDDR4-2400
OS: Windows 10 Pro
Compiler version: IC18
Performance numbers are Pre-Si projections and are subject to change. Results reported may need to be revised as additional testing is conducted. The results depend on the specific platform configurations and workloads utilized in the testing, and may not be applicable to any particular user’s components, computer system, or workloads. The results are not necessarily representative of other benchmarks.

Fast-Track IoT Functional Safety

The electronic subsystems used in today’s healthcare, industrial automation, and transportation applications are incredibly complex. In addition to demanding exceptionally high performance, rapid time-to-market is also a critical requirement.

One example is the ventilators that provide artificial respiration, delivering oxygen to patients unable to breathe on their own. The COVID-19 pandemic has been driving an instantaneous demand for ventilators in hospital intensive care units (ICUs). But regardless of the need for speedy deployment, safety-critical systems must still adhere to safety standards.

Functional safety (FuSa) involves operating correctly—or failing in a predictable (fail-safe) manner—in response to a wide variety of scenarios. These include problematic input signals such as human errors, hardware failures, software glitches, and stress caused by environmental and operational conditions. To address these issues, safety-critical systems must comply with complex FuSa standards like IEC 61508 and ISO 13849.

A Safety Island for FuSa Compliance

The latest Intel Atom® x6427FE and x6200FE processors—previously known as Elkhart Lake—provide designers of safety-critical systems with enhanced features that simplify FuSa-capable designs combined with multicore high compute performance. This provides the ability to consolidate both safety-related and not-safety-related workloads in a single platform.

The integrated Intel® Safety Island reduces customer overhead for implementation of safety mechanisms, orchestrating HW and SW diagnostics, and monitoring customer safety application.

In addition to the FuSa features integrated in the Atom x6000E processors and orchestrated by Intel Safety Island, the Intel® SoC supports works in conjunction with networking technologies like Ethernet time-sensitive networking (TSN)—bringing deterministic, real-time communications to functionally safe IoT deployments. This matters because TSN determinism is important in FuSa applications where a complex distributed processing environment must work in a synchronous manner.

“In the healthcare industries, applying FuSa standards can enable healthcare and biomedical machinery to prevent dangerous situations.” – Lorenzo Veltroni, @SECO_spa

Reducing IoT Development Complexity

Even while facing time-to-market demands, developers must take into account the need for future-proofed designs to meet the increased computational requirements of new and evolving applications. One solution for equipment manufacturers who want to ride the wave of an increasingly competitive marketplace is to adopt a strategy based on Smart Mobility Architecture Computer-on-Modules (SMARCs or SMARC COMs).

Unlike a traditional single-board computer, a SMARC COM is not designed to use standard connectors for input/output peripherals to be connected directly to the board. Instead, the SMARC COM is plugged into a carrier board, which contains any additional components and subsystems. This allows it to provide the core compute capabilities, while the carrier boards provide the “secret sauce” that allows system designers to differentiate their products from competitive offerings.

The ability to replace one industry-standard SMARC COM with another while keeping the same carrier board allows scalability, fast time-to-market, and upgradability—while maintaining low costs, low power, and a small footprint. And using industry-standard SMARC COMs enables second-source options that are simply not available with proprietary designs.

SMARC Modules Meet Safety-Critical Systems

When creating safety-critical products, leading embedded hardware manufacturers like SECO package the safety and security of Intel Atom x6000E processors in SMARC COM modules, such as the SM-C93 (Figure 1).

Image of a SMARC module PCB layout
Figure 1. The SECO SMARC module is specifically designed for FuSa in safety-related IoT systems. (Source: SECO)

“Increasing demand on performance and connectivity is particularly challenging due to the additional design impact related to functional safety constraints,” says Lorenzo Veltroni, HW R&D Manager at SECO. “In principle, this affects both integration and certification. This is the great benefit of the SECO SMARC module: being able to provide functional safety on a small factor.”

Marco Sogli, Head of Software R&D & DevOps at SECO, adds, “With the Atom x6000E-based, many FuSa features are ready to use and easily certifiable as they come from Intel. In this way, the SM-C93 helps reduce complexity and shorten development time to as little as six months.”

By including qualified FuSa components directly in the SMARC module, alongside complete documentation, SECO makes it easier for customers to more quickly pass the IEC 61508 and ISO 13849 certification process.

FuSa Integration Opens the Door to New Applications

“In the healthcare industries, applying FuSa standards can enable healthcare and biomedical machinery to prevent dangerous situations,” says Veltroni. “In these scenarios, detecting failures and anomalies can help prevent injury to patients and users.”

But Atom x6000E processors with FuSa features—and systems such as the SECO SMARC module—apply to use cases well beyond healthcare. They are applicable to a wide range of safety-critical and mission-critical applications, including industrial control, robotics, transportation—and the list goes on.

For example, SECO is now working for further integration of its SMARC Module for an industrial application. “Keeping workers and the environment safe is a key priority when designing automated equipment and processes,” says Veltroni. “And in this environment, functional safety is the technology needed to remove unacceptable risks in the presence of possible fault. The Intel Atom x6000E is key to making this possible.”

Disclaimers:

Not all SKUs include every feature.
Not all features are supported in every operating system.
Not all SKUs support real-time computing, time-sensitive computing, or time-synchronous networking.

“Cloud in a Box” Puts Azure API Into an On-Site Appliance

Hybrid cloud infrastructure is booming thanks to its ability to combine the best of the cloud environments and on-premises data centers. But for some organizations, hybrid clouds fall short in terms of security, compliance, and performance.

Public sector applications are a prime example. Because these applications handle highly sensitive data, connecting them to the public cloud is out of the question. Many commercial applications run into similar constraints due to data sovereignty regulations like GDPR.

Or consider applications that require extreme performance at the edge. Many video processing applications, for example, have such high bandwidth requirements that data must be processed close to the source. Other scenarios are constrained by limited network connectivity. These include environments like oil rigs, mines, and geospatial imaging

How can applications like these take advantage of the cloud?

Cloud Platform in a Box

For Dell Technologies, the answer was to create a “cloud in a box” that delivers the Azure API for on-site deployment. Known as the Dell EMC Integrated System for Microsoft Azure Stack Hub, this appliance challenges the existing hybrid cloud model. By presenting neither a traditional CAPEX-heavy private cloud infrastructure play nor a network-dependent public cloud model, this is a different hybrid cloud option that gives the customer a new choice.

Handle highly sensitive data? Need extreme performance at the edge? @DellTech says to bring Azure on-premises—no network connection required via @insight.tech

The appliance can be placed almost anywhere—on-premises, in a third-party data center, or even in the field. It can even operate in disconnected environments with no network access. The upshot is that organizations can achieve:

  • Rapid data interpretation and visualization at the edge
  • Cloud-like scalability and economics with the highest security and real-time response
  • An on-premises appliance that features Azure-consistent APIs

This model eliminates the need to segregate computing workloads between on-site and off-site infrastructures based on data classification and sovereignty laws. It also eliminates the need to separately manage orchestration, IT environment monitoring, and application portability between public and private environments for their end-users.

A Look Inside the Box

Customers can choose to acquire Azure Stack Hub from Dell Technologies as a traditional hardware appliance or install the device and pay only for actual applications and workloads usage. Dell Technologies has also integrated advanced management functionality like monitoring, patching, system updates, and life-cycle management into Azure Stack Hub’s advanced automation services.

While the hardware stack is an appliance with “no user-configurable parts inside,” customers can choose from a variety of configurations for various needs. The integrated system is based on proven PowerEdge servers with:

  • Powerful Intel® Xeon® Scalable processors with a total of 96 cores per server
  • A choice of performance and capacity options to support Azure-based services
  • Cloud-native workloads running on-premises, and PowerScale storage technologies that can hold data at petabyte-scales

As an all-flash system, the Azure Stack Hub design and configurations support high-performance and data-intensive workloads. Upcoming enhancements will unlock valuable, real-time insights from local data using GPU-accelerated AI and ML capabilities.

New Operational Models

Operationally, this model opens a world of new possibilities. For artificial intelligence, this means pairing algorithm training with test data on the public cloud with the ability to run inferencing workloads with sensitive data in the on-premises private environment.

From oil rigs to natural-disaster sites, remote operational locations can avoid the need for gigabyte network connectivity to the public cloud due to local accessibility issues and still deliver powerful video and geospatial processing capabilities. The solution can also locally store and process the petabytes of data needed for mining and energy-related scenarios. This versatile platform can even support military forward operating bases with the environmentally hardened Tactical Azure Stack Hub.

Azure Stack Hub customers receive real competitive value to their organizational business challenges through the integrated system’s ability to deliver exceptional GPU performance to IaaS and PaaS services across a hybrid cloud platform. It also offers business agility and the flexibility to run any workload (on-premises or in the cloud) while effectively addressing scenario-based data classification and data sovereignty laws.

A New Approach to Data Center Administration

As mentioned before, this stack is not like a traditional data center infrastructure appliance. Managing services from Azure Stack Hub is more akin to the management of cloud services.

As a member of the acquiring organization’s staff, the administrator’s focus will be on delivering quality cloud services to internal customers. The role is to ensure Azure services are highly available on the private infrastructure and that all internal customers have self-service access to provision, configure, and consume those services.

While this evolution may require additional training, this new hybrid cloud model encompasses the cultural, mindset shift, and operational changes that leading companies are embracing today.

The Future of the Data Center

This solution challenges the current definition of a hybrid cloud. It also provides a glimpse of the future of enterprise IT. Imagine a private data center fully provisioned with zero cash outlay. Where even though every piece of hardware and every bit of data remains in your private data center, but you pay only for the services you use when you use them.

Preetham Mukhatira, Director of Product Management at Dell/EMC, says, “You will go to a catalog where you’re able to order your Dell EMC Integrated System for Microsoft Azure Stack Hub. Dell Technologies will deliver the integrated system to you on-premises. You would then flip a switch to turn it on. Dell Technologies will manage it for you and accurately meter usage. The organization will pay one bill that includes Azure, the Dell EMC storage, and the advanced Dell Technologies management services.”

PDM Keeps Smart Factory Robots on the Move

Manufacturers rely on predictive diagnostic maintenance (PDM) to reduce downtime and costs by ensuring production machinery is running in optimal condition, solving problems before they happen. But what about the robots that work inside and alongside these machines, performing welding, assembly, inspection, and other precision tasks?

With more than 2.7 million industrial robots in factories around the world, it’s not surprising that PDM has become an essential requirement for these systems. While regularly planned maintenance helps, manual processes can’t identify all problems or ensure that a robot is working within spec.

“Just like any other asset on the production line, robots need predictive maintenance. But factory managers may not know how to diagnose or predict when a robot may have a problem or be on the verge of going down,” says Kurt Chen, Project Manager at NEXCOM.

Though it’s sorely needed, developing an automated, AI-based predictive maintenance solution for robots is complex and challenging. That’s partly because robots don’t necessarily run consistently, as conveyor systems, overhead cranes, or packing machines do.

Their complex, three-dimensional movements – which can include starting and stopping at odd intervals and rotating on multiple axes in dozens of positions – emit greater and more complex vibrations than other machines. That can lead to problems like loose screws, worn gears, overheated motors, or even collisions with other robots. In addition, robots are customized with special tools and configurations susceptible to failure.

Standard factory PDM models for quality assurance, for example, typically lack the AI models needed to accommodate robots’ unique and varied tasks.

The system offers advice about problems that could occur and recommendations for preventing them.

Ideal for Smart Factories; Ideal for SIs

NEXCOM, a global provider of industrial computing and predictive maintenance solutions, solves these challenges. Its PDM300-RBT Intel® IoT RFP Ready Kit addresses a wide range of robot-specific challenges, and offers systems integrators (SIs) an easy way of customizing the solution to individual factory operations (Figure 1).

PDM visual reporting views and the PDM300 robot controller hardware with cloud connectivity.
Figure 1. The PDM300-RBT has all the software, hardware, and AI technology that SIs need to get robot predictive maintenance POCs up and running. (Source: NEXCOM)

The NEXCOM kit includes four primary elements:

  • A computer vision system running on the Intel® OpenVINO Toolkit, which performs LED object detection to accurately guide the robot.
  • A predictive maintenance vibration kit with sensor arrays that operates in a similar fashion, alerting factory operators to abnormal vibrations before robots break down.
  • A secure Intel® processor-based gateway that sends detailed information about robot performance to the cloud, where factory managers can slice and dice the data to track trends.
  • A seven-axis demonstration robot that runs the predictive maintenance software to perform common factory tasks. SIs can use it for critical proof-of-concept trials at client facilities.

The NEXCOM solution can detect the output and health of many kinds of robots, including delta robots, selective compliance assembly robot arms (SCARA), and articulated robots. After a computer vision camera and vibration sensors capture baseline data about a robot’s normal operations, the software monitors ongoing patterns to detect anomalies. Its three-dimensional capabilities allow it to inspect robot performance from multiple angles and pinpoint a host of potential issues.

Standalone, magnetic sensors attach to any surface near a robot, which eliminates the need for permanent fittings. And its adaptive AI can handle PDM requirements in as little as three minutes to begin formulating patterns for a specific robot chain.

“We have large computing engines doing the analysis and can get a lot of information from every sensor. The system offers advice about problems that could occur and recommendations for preventing them,” Chen says.

A Path to Smarter Factories

Out of the box, NEXCOM’s PDM kit allows factory managers to address many issues that plague robots. It also gives SIs the tools they need to solve customers’ more specific problems. The result could be a sea change in the way factories manage robots.

For plant managers, real-time alerts will nip problems in the bud, while cloud-based analytics will improve decisions about future operations and purchases. For SIs, a wealth of pre-loaded information speeds the development of custom solutions and facilitates expansion to new markets.

As more manufacturers adopt robot PDM solutions, machine learning systems will sweep in more data, broadening knowledge about the workings of these complex machines. SIs and factory managers will find new ways to make their robots more capable, responsive, and resilient, avoiding problems and outages and making factories more efficient.

15 IoT Twitter Influencers to Follow in 2021

What better way to kick off 2021 than with 15 hot follows in the IoT Twitterverse. Whether you’re looking to keep your finger on the IoT pulse or interested in keeping up with industry trends, these are the influencers to follow.

1. Kevin Jackson

@Kevin_Jackson

A Top 5G Influencer and a Top 20 Tech Blogger, this DC-area author is a globally recognized cybersecurity and cloud computing expert. Take his crash course in digital transformation on this recent episode of IoT Dev Chat.

2. Sarah-Jayne Gratton

@grattongirl

One half of the tech power couple The Grattons, Sarah-Jayne Gratton is a digital strategist and technology influencer who covers AI, 5G, AR, and Big Data. Catch her on our UK-focused podcast mini-series: Retail Tech Chat.

3. Dean Gratton

@grattonboy

The second half of this London-based power couple, Dean Gratton is a tech influencer, analyst, and futurist, covering AI, IoT, IIoT, SmartHomes, SmartMeters, Energy, and Digital Transformation.

4. Neil Cattermull

@NeilCattermull

This London-based analyst and tech influencer is fluent in tech, IoT, cloud, blockchain, and AI. His Twitter feed is curated from across the IoT and embedded space. Bonus: He’s into balloon animals and pasta.

5. Diana Adams

@adamsconsulting

Looking for digital transformation, IoT, 5G, AI, ML, big data, and automation? This Atlanta tech journalist is the follow for you.

6. Antonio Grasso

@antgrasso

A big-picture thinker, Antonio’s feed is a great place to track the trends that matter, like AI, blockchain, FinTech, and IoT.

7. Ajit Jaokar

@AjitJaokar

Ajit is your go-to for all things AI, IoT, and Bioinformatics, plus he’s Course Director of Artificial Intelligence: Cloud and Edge Implementations at the University of Oxford.

8. Rob van Kranenburg

@robvank

Rob is the founding member of IoT News and voted one of IoT Day’s Top 20 thought leaders in industrial IoT. Follow his feed for all things IoT.

9. Peggy Smedley

@ConnectedWMag

Peggy is a podcaster, influencer, and futurist educating the world about the IoT and emerging tech in an effort to inspire next-gen women and men as innovators.

Unleash your inner geek with @insightdottech’s top 15 IoT influencers to follow in 2021.

10. Chris Isak

@chrisisak

Into tech, gaming, and geeky things? Chris is your man. He also dabbles in all things AV and IoT.

11. Beverly Eve

@BevEve

This London-based co-founder’s feed is the place to be for tech, innovation, IoT, AI, Cloud, 5G, Big Data, and Digital Transformation.

12. Shawn Hymel

@ShawnHymel

Believe that education is the best form of marketing? You’re in good company with this freelance content creator. Added bonus: his quirky videos.

13. Evan Kirstel

@EvanKirstel

This Boston-based B2B Tech Influencer supports Enterprise Clients with virtual events in telecom, 5G, IoT, and Cloud.

14. Ronald van Loon

@Ronald_vanLoon

A Top 10 Influencer, follow Ron for the latest on AI, machine learning, and Big Data + live coverage of IoT shows around the world.

15. Dr. Sally Eaves

@sallyeaves

Professor Sally Eaves aka the torchbearer for ethical tech, has recently been ranked 8th in the world in blockchain impact and is ranked in the top 10 for digital disruption and across frontier technology subjects.

 

Have more influencers to add to the list? Share them with us on Twitter: @insightdottech.

Catch our top influencers from 2019 and 2020.