IoT Podcast Logo
https://youtu.be/ZQ9y12B1AXE

In episode 45, Chris Slee – Principal AWH and CTO Include Health Inc. tells us how IoT is being used for fitness🏋️ & recovery💪 and explores life-changing AI use cases 🤖 .

Sit back, relax, tune in and be the first to discover

  • Can you talk a little bit about your background, how you came to found AWH? 00:3605:49 💪
  • We are entering a world where devices and objects are becoming more and more connected and companies are innovating new digital products every day. What is the most innovative use cases you have developed/have seen companies develop for IoT / web user experience? 05:4909:29 🏋️
  • What are the most prominent changes AI has brought about for software products and applications? 09:2914:07 💪
  • What are the key challenges AI and machine learning need to overcome in your opinion? 14:0718:17 🏋️
  • You’ve recently entered a new venture at IncludeHealth, I’m interested in learning more about this and how the company is innovating musculoskeletal care via machine learning and algorithms? 18:1731:28 💪
  • What most excites you for the future when it comes to AI, Machine Learning and IoT? Will we be in a utopian or dystopian world? 31:2833:57 🏋️

Episode Transcript

Tom White
Welcome to The IoT Podcast Show. I’m your host Tom white. Today we’re joined by Chris Slee. Chris is the founder and CEO at AWH an Ohio based software engineering firm celebrating its 26 year in business.

Chris has been instrumental in a number of projects over his 30-year career and has built over four and a half 1000 applications. Chris is also the CTO at include health, a venture that he has started alongside Google io. Welcome to the podcast. So Chris can you start by just explaining a little bit about your background and how it is that you came to found AWH?

Chris Slee
I can the story happened a long time ago, because we’ve been we’ve been out there for about 2627 years now. In my background, I ended up as the global information architect or a chemical company called Borden chemical. They don’t exist anymore, but that was not my problem. So but while I had that job, so my job was essentially to travel around the world, to our manufacturing plants, and make sure they’re connected and you know, do those kinds of things. It was the early 90s. And my brother came back from the military and said, Hey, I was looking for you on the internet. And I was like, what’s that? And so then he was like, so he showed it, you know, he was like, okay, and this was the time when people really didn’t have dial up connections, the internet didn’t really exist yet, Delphi and some other systems out there you CompuServe and so we decided to make an ISP. So you know, racks of modems and, and that kind of thing and phone lines. And, and we started out in sort of rural Ohio, because there was you know, there were isbs in large cities but not out in the country.

And we ended up hearing about you know Roadrunner and Time Warner and high-speed internet to your house and decided to sell that business, but then kept our consulting business. And so that was the mid to late 90s. We ended up then doing a lot of e-commerce work for Microsoft. So one, one point we had done, I think, nine of their 11 e-commerce sites we ran and built-in that kind of thing. So we build a product and took it to market and did an exit in the early 2000s. And it just been doing consulting Ever since then, for clients building digital in IoT projects for them, and helping them take it for the market and do exits. 

Tom White
Crikey, that’s an extensive history. It’s often funny when people start talking about the early days of the internet. And obviously, Tim Berners Lee being a British guy. I actually don’t remember anything pre dial-up, right? Oh, yeah. In fact, I think I think the first I think it was CompuServe, which was the first ISP that we had here in the UK. But I remember coming in on a 28-bit live dialling into that before 56k became the norm.

Chris Slee

But I had rooms of Digi boards connected to modems with blinking light,

Tom White
You know, people don’t pay the internet. Yeah, it was a fun time, way back then. So yeah, yeah. But it’s always come full circle, right, when we’re talking about it, because it needs to transmit, you know, a lot of information really isn’t there? Right, you know, you don’t need that much. And it’s interesting that you’ve merged back into the space, we’ll put the business and now you know, it’s fantastic, isn’t it? You know, what, what is it? What is it? They bought you more into it than obviously starting back in, you know, in the, in the early days of the internet, while the the the every software developer who, who writes code wonders what it’s like to build a piece of hardware, right?

Chris Slee
I mean, that’s sort of like, you know, there’s, there’s, if you look at sort of the mountain of developers, the mountain of developers, you know, from a bell curve perspective, the majority of them are in the middle and they’re writing some sort of, you know, web application, mobile application, those kind of things. I would say almost all that I talked to have some sort of initial vs NES for people who understand how to do firmware and make hardware things work, and how to make a solenoid fire. And you know, the fact that a piece of code can control some real-life thing, that there’s never get the chance to experience that.

And so as we sort of went through, you know, building products for customers over time, we ran into that more and more. And so we had a team specialise in that particular aspect, not only the firmware, but also the connectivity and, you know, whether you’re doing amp plus or Bluetooth or you know, IP connections, or radio, and then sort of understanding, you know, all the different ways you can solve real-world problems with a piece of hardware, beyond just someone running a web application is a really exciting space for developers to get into.

Tom White
Yeah, yeah, I completely get it. Yeah. I understand. Chris, so Well, obviously, we’re entering into a world with devices and objects are becoming more and more connected. Clearly. You know, and this is what the whole show is about, right? companies are innovating new digital products every day. What is the most innovative sort of use case you have developed to have seen companies develop for IoT? Be curious to understand that?

Chris Slee
Yeah. And I sort of take that question into, what’s my favourite? Because, you know, that’s sort of how I wrap my world, right? We had a, so we do a lot of commercialization. Obviously, if we’re, if we’re doing, you know, Product Development and Engineering and go to market strategies, we do a lot of commercialization. And here in Columbus, we have Nationwide Children’s Hospital, which is a large Research Hospital. And they do a lot of commercialization work in one of the projects that we did from them for them was it was actually on a Netflix documentary called babies. But yeah, one of the products we did for them was this concept of an infant in neonatal intensive care needs to hear in interaction with its mother, because it’s had that this whole time, but a premature baby doesn’t have that because the mother is not there all the time.

So then we help them build a system with Ohio State University that was essentially looked like a dinosaur egg. It’s called the fact that the early name was dynamic. And that actually went in and isolette. And the, when the baby would use a pacifier, we would have a transducer, send a Bluetooth signal, and then that egg would be able to play the mother’s voice at a decibel level low and, you know, safety for an infant in that space. But that way, the baby still had that connectivity with its mother in that isolette. And it’s projects like that, that have a real impact that you know, that you go, okay, you know, this is really helping someone that we really like to do.

Tom White
Yeah, I think that’s fantastic. And it’s often the thing that I say, we have guests on the show, that, you know, my journey in tech has come from entertainment, doing a lot of work in a pay-TV field. And advancements in that field, from video, compression, audio, etc, is fantastic. But ultimately, it’s just TV, it’s just entertainment. And you can’t change that. Whereas with IoT, when you start looking at sensors, and you start looking at people that are, as you mentioned, they’re around health care, we’ve had people talking about wildfire, early detection systems, there’s a really feel good feeling there isn’t there that you’re actually doing something that is genuinely wholesome. And you know, what better feeling is there than that?

Chris Slee
When we look at projects that we want to take on as an organisation, we really have two sorts of ramps, one of them is it has that this particular project has a sort of a definite impact on somebody’s life, you know, or community of people’s lives, right? Or the other projects we’d like to do our very technically challenging pipe have never been done before. You know, moonshot, how would you even do that? And when you can sort of combine those into projects where you’re getting both sides of that equation, that those are really the projects that that team gets jazzed up about?

Tom White
Yeah, absolutely. So, what are your thoughts on AI then Chris? So in terms of the most prominent changes that AI has brought forward, in software, products and applications? 

Chris Slee
Yeah so like, for instance, that first example right, there’s no AI there. I’m getting a transducer signal, okay, I’m going to go do some action. I’m going to record how long we’re playing, you know, those kinds of things. The other IoT projects that we’ve been in the AI component is about, what are you doing with that particular data set that you’re getting? You know, if I’m streaming data from an IoT device over a period of time, you know, there’s an easy sort of low hanging, well, you could do sort of maintenance predictability, and you can do you know, runtimes, and those kinds of things. Like, those are, those are, I think, the bread and butter of sort of predictive AI inside the IoT space.

But one of the things that that we’re looking at now is understanding sort of the AI in the machine learning, not only on predictive maintenance, and those kind of things, but actually how can it come in and help somebody do work. So if for understanding something, so we have a concept out there, with a client that we’re working on, that is, if I have a mobile device, and I can work with a clinician, and it’s just listening to our conversation, like this conversation you or I are having right now.

We worked with the Children’s Hospital at Cincinnati, Ohio, to build a model that then could take that, transcribe it through Watson, get the NLP back, and then start doing marker scorings for suicide ideation. So are the things you’re saying, starting to trip some of the NLP around, you know, suicide, you know, thought processes and those kind of things. And then we were able to expand that into the baseline.

So let’s say at the beginning of a school year, we can bring students in and have conversations with them, that system could rank them, you know, and then, over a period of time, as we have more communication with them, we can understand the changes in their mental aspects, you know, and then we were able to expand that into depression and some other types of scoring mechanisms that allowed us to then understand how is this person doing mentally over a large sort of segment of mental illnesses. But that all came from being able to build models that understand, you know, language processing, and what is the person saying and cadence of speech? And yet, there are about 503 separate markers that are involved in those model outputs, that then we start to use and, and that’s just all based on, you know, having a phone in your body?

Tom White
Yeah, yeah, it’s incredible. I mean, we had someone recently Jan Jongboom for Edge Impulse talking about machine learning and embedded right, and how, traditionally, they haven’t been coupled together. But when you talk about AI, NLP, for suicide prevention, basically, right, yeah. And understand and understanding how that can actually trigger early points. Yeah, I mean, it kind of takes my words away, right?

Because it’s such a, it’s such a massive cause and something that unfortunately troubles a lot of people, both in North America here in the UK, but also quite, quite young people as well. Right? Yes. And there’s a big problem of that, you know, going into schools, etc. It’s just, it’s a one, it’s a wonderful thing to be able to try and help and use this for good. People talk about tech for good. But I think it’s overused sometimes. But that really is a real poignant case, isn’t it?

Chris Slee
Yeah, we are. You know, we’re trying, like I said, you know, the types of projects that we’d like to get involved in, most of them are predicated on the fact that it’s an actual human, you know, impact like those kinds of projects.

Tom White
Yeah. And we’d like what, you know, we like working and speaking to people that are doing that type of thing as well. You mentioned obviously, Watson, right, which is IBM as that was doing NLP, Trent that was doing translation for us. Yeah. So just on that note of the sort of, you know, quantum computing and things that that, you know, you know, you’re probably going a little bit off course here, but it’s taking me on a bit of a tangent and what do you what are your thoughts? What are your thoughts on that, in terms of is this a limiting factor in and a key challenge in AI and machine learning that we need to kind of overcome the use of, you know, the vast amount of processing power and you know, yottabytes of information as this is something that you know if trailing the vision of some of these projects that we see in machine learning, etc.

Chris Slee
I think in when we have internal conversations that matter, or like, I’m the host of Columbus machine learners group where people come together and talk about different you know, aspects of ml and its application. The sort of direction that’s going is people have this thought that machine learning models are all-encompassing it does all kinds of different things. And what we found is that the best way to deal with these is, it’s not one model. I’m actually building multiple models that pass data amongst themselves. So I get to componentize. Sort of the thinking.

And if you if you think the nature like even if you think that like the human brain, the human brain does not do one thing it’s compartmentalised in each compartment is managing different parts in it, right? So our vision is managed in a different place than our frontal cortex, which is managed in a different place than the things that control our autonomic systems. When you start thinking about machine learning in that, in that sort of venue is I don’t need one master model. What I need is to be able to compartmentalise and componentize those models and let them all talk back and forth together like a biological system really would, versus a massively trained model that can figure everything out on its own. That approach, I think, will always hit a computational boundary that you just couldn’t do it. Where is his I would rather have multiple models that are specialised that are dealing with specific things, communicating amongst each other. And again, I think that’s a more biological approach to solving that problem.

Tom White
No, I agree. I agree. And it’s nice to know you’re involved with this, you know, actively within the community, you run this, you run this group, and it’s set with the Ohio nl to meet alumnus, machine learners. Yeah. I need doing that online at the moment because of obviously the pandemic. Yeah, it’s a meet up. It’s all online at this point. So. Okay, and can people okay, and it’s on meetup.it? On meetup.com?

Chris Slee
Yeah, so Okay, you know, you can Google or search now. Now, Google is just a term for searching.

Tom White
Yeah. Wow. Yeah.

Chris Slee
Yeah. Yeah, Columbus, Columbus machine learners. And we once a month, we get together and we either have a host or while we either have a presenter, or we’ll do a breakout session on, you know, you know, TensorFlow versus, you know, pie torch or you know, any of those kinds of things. But, so it’s really from businesses, sort of having a conversation about what is machine learning to engineers and data scientists. And so we sort of bridge that spectrum back and forth. So everyone’s Welcome to go.

Tom White
Yeah, that’s great. It’s interesting, isn’t it? Because many of the comments have been fantastic for actual physical meetups. But what we’ve seen a lot recently is that you’ve got people dropping by, right? Yeah, cuz it doesn’t necessarily need to be around the corner anymore. It’d be interesting when they see people back in, you know, in a physical space, how many of these people would take the journey, you know, and actually go over there?

Chris Slee
We had, we had about 10, first-time people last night at that event already. And they were not in Columbus. And they were people in from Pittsburgh. And there were some people from Texas and it was just because now you know, the internet is sort of an equaliser from a well, if I want to learn about some topic. I can go to all kinds of different places that are not geographically bound to go learn about

Tom White
Yeah. Well, it’s the quality of the content and the quality of the speakers, you know. And from small acorns, you know, exactly. It could be, it could be really big. So you’re like fingers, fingers crossed. But we’re talking about socials near the end of the show. Yeah. And, Chris, I want to, I want to understand a little bit more about include health. So this is a new venture that you started. I’d love to learn a little bit more about that and how machine learning and algorithms are working with include health care.

Chris Slee
That is a great story. So include health I got involved with I met the founder, Ryan eater, about six years ago. He did aim his mat, his thesis coming out of design school engineering in Cincinnati on a functional trainer. And by that I mean a 900-pound machine, right? He watched a guy in a wheelchair go up to some regular weightlifting equipment with just this bag of accessories and you know, trying to do sort of weight lifting, and turn that into his design thesis. And he kept that over a period of time started winning awards for the design. And it was a, like I said, it’s a 900 pound functional trainer that is neutrally balanced.

So you don’t have to have fingers or even arms to be able to work out and using this functional trainer. It was wheelchair accessible, you know, high accessibility. I got involved when we wanted to cloud-enable that so someone could schedule a workout. And then it would sort of tell you how to set the machine up for benchpress or how to set the machine up replies or how to set the machine up for you know, whatever you’re doing, and then this the machine was smart enough To change solenoids, and adjust the weight stack for you, and do all those kinds of things.

So you didn’t have to do really anything except walk up to the machine, you know, RFID into the machine, it would find out who you were and come back with your current schedule workout and then walk you through it, and then it would take that data and then it would store it, and then we would give you sort of long term results and trending of how you’re doing.

Tom White
That is awesome. Yeah, I’m just envisioning it. Now. I’ve come surprised. No one’s done that before. Right. Smart gyms, you know?

Chris Slee
Yeah. So what’s interesting is that that machine, so that’s that our target market was predominantly into health care and recovery, right? physical therapy, occupational therapy. The then what happened was, the organisations came in and said, Hey, we this, this is awesome. We love the platform, we love the fact that our clinicians could come in and schedule, you know, therapy for you know, you, Tom. But we have other machines on our floor. Besides just this one, you know, functional trainer, we’ve got leg press machines, we got regular flying machines, we’ve got bikes, we’ve got skiers, we’ve got all kinds of other stuff going on. And sort of at the same time, we were dealing with the Air Force, who wanted to use this from a performance perspective to track the capabilities of people in their performance fitness labs, right? Because we could do that, too.

So we ended up building a sensor platform that would tie in and we could actually have sensors that we can put on any piece of physical exercise equipment, and either through LIDAR or gyroscope, or accelerometers, right. So essentially, I can stick it on to a leg press machine. And as you do leg presses, I can count your reps, I know your range of motion. I can tell you know, from a resistance perspective, how much work you’re doing, what’s your velocity, all those kinds of sort of things. But now we can wire up any piece of equipment in a facility. We did that essentially by having an iPad nearby. So that became your screen. So you can watch the you know, ROM gauge and rep counting. And it would tell you what you’re supposed to do on this machine. And you know, those kinds of things. So now then we have this functional trainer, we had this IoT platform that got wired up all that data, then was streaming back to our, our cloud platform. And then we ended up doing some commercialization with Children’s Hospital out of Cincinnati on something called anime, which is they had noticed a problem where girls who were athletes were getting ACLs at higher rates than boys who were doing similar kinds of sports, and they wanted to know why.

So research sort of kicked out. And it turns out, girls land differently when they jump in the air than boys do. They went in with their knees in, which creates more stress than boys who land with their sort of knees straight. So then they started, you know, sort of trying to understand that problem and realise that they need coaches needed to be able to train girls to do activities differently than boys. And then they did, some additional research was done. So this is over a period of, you know, half a decade.

And what sort of came out of that was, you know, understanding that there’s a third type of memory that we have, you know, everyone talks about short term long term, but there’s something called procedural memory. And procedural memory is, if you’ve ever learned how to ride a bike, you will know how to ride a bike. And it’s that one moment that it sort of clicks in your head, that you understand the mechanics of riding a bike you’ll never forget. So you can not ride a bike for 30 years, and within seconds, you’ll be riding the bike again. And that’s, that’s a special type of memory that you have for procedural memory. If you can train somebody to activate their procedural memory, then you can train them to jump and land correctly. What you can do, however, is if you’ve ever tried to describe how to ride a bike to someone you realise No words can ever let them understand that feeling when your procedural memory sort of clicks in right?

It’s sort of like when you go to play golf and they give you like 5060 sort of work on this and change this and rotate here and move this sweep through and you know, backswing and then the instructor look at you and go just forget all that and just swing at the ball. Well, which one is it? Do I need 50 instructions or am I just going to swing at the ball, right? So, they had a 40 mocap camera system and they recorded people doing activities and then what they did is they distilled that down into a simple concept that says, hey, I’m going to give you a square and I and they were using HoloLens. So we’ve got a square in front of you. And as you do the activity, if you don’t deform the square, you’re doing the activity correctly, but I’m not going to tell you what the activity is, or how to do the activity. Now, we may go, well, the activity of squats, let’s say, for instance, but I’m not going to tell you how to do a squat, you just start moving. And if you don’t perform the square, you’re doing it correctly. And so through trial and sort of, you know, you realise, okay, if I do it like this, that I’m not deforming the square, and then you’re actually doing the movement correctly, no one’s told you how to do it and your procedural memory or lock that in, and you will do that correctly every time from that point in the future.

So then, we did a commercialization include health with them to be able to take that out into the, into the market for physical therapy. The, we had, essentially Azure Kinect cameras, we wire them up, we built the software, and then the pandemic. And we realised, Hey, no one’s buying functional trainers be no one’s buying sensor platforms, because we don’t know when we’re ever going to be in a gym again, and no one was buying cameras that you had to ship to people’s homes for remote patient care.

So we transition completely over to machine learning models and camera-based input that didn’t have LIDAR. So this was a 2d camera system like our webcams. And through the webcam, we built enough models that now I can watch you, and I can tell you what your range of motion is. And I can tell you what, how flexed your knee is and what angle your knee is at just by looking at a camera. And in fact, today, as it turns out, at Google iO, they’re announcing a new model that we’ve been working with them on over the past eight months. And that is part of our commercialization.

But we’ve been working with Google research on training that those sets of models and commercialising the output of those models into our platform. So we now have a platform where we can fire up any webcam over the web, sort of, you know, like, you know what we’re doing right now. But I can want I can tell you exercises to do, I can watch you do those exercises, I can count your reps, I can look at your range of motion of all your joints, I can give you warnings if you’re not doing it correctly. And then I can store that all back for the clinician to be able to do that. And that’s how we’re going to be able to help people progress, whether fall prevention or hip, knee and hip replacements or other physical therapies in people’s homes without having to send devices to them. They can use any device, they have to be able to do that. 

Tom White
Yeah, that’s fantastic. I was just thinking that actually because it can be somewhat perhaps prohibitive to work online, as everyone’s got webcams. Right. Exactly. In terms of adoption and engagement. Maybe that’s a good thing, you know because you’re gonna get more people using it and more people working with you on that. And I think sometimes we can overlook the simple webcam and what we can do from that. Another example of that is, I know there are a few apps out there at the moment that will use a camera phone to identify potential cancerous moles and what have you. Right, yeah, and infections of the skin. And I think I think that’s a really poignant point that you’ve made there, that, you know, often in the race for bleeding-edge hardware and tech, sometimes we can overlook things that are already there that we can use, but perhaps we just haven’t thought about yet.

Chris Slee
Yeah, and I think, you know, going back to a part of our previous conversation around, you know, the advantage of machine learning and artificial intelligence, it’s not necessary to replace things, it’s to enhance and augment. Right? So if we can understand someone’s body position, you know, in a camera, I can use that then. And then understand is that person standing or sitting or laying down, I can use that then to understand, and, you know, I can ask you to stand straight and then do a squat. And then, you know, trigonometry can tell me what your, you know, angle of your knees are, and, you know, all those kinds of things that a clinician would want to be able to see if you’re recovering correctly. And going through your phases of recovery. And yeah, some The, the pandemic really sort of pushed us into, look, we’re not going to send hardware to people. So we need to be able to go to where they are on the devices that they have, and what’s the way to do that. And that’s really where Matt ml shines.

Tom White
Yeah, absolutely. And I think that’s been seen several times with other businesses from a logistic standpoint, you know, companies sending hardware To people laptops and what have you, now, there’s a lot more VPN says a lot more secure connections. Because you don’t necessarily need to do that. And I think there’s an environmental impact on that sometimes. Yes, well, right. You know, you know, naming no names, but we know some businesses recently that have been shipping out 10s of laptops from the UK out to Greece, you know, for interim projects, and you just think, would you really need to do that? You know, really, you know, you could do a remote build on their current year, you could get it via a VPN, just a good fibre connection, or what have you. And yeah, okay. So, yeah, I completely agree.

Chris Slee
I think sometimes people, you know, have a hammer in their hand, and then everything has to be a nail because they know how to hammer a nail in place. But sometimes, you know, you want to start thinking about spot welding or some other way, right? Or maybe these things don’t even need to be joined together. Right. Right. So yeah, yeah, you gotta, you gotta sometimes just go way back and sort of think about the problem-solution that you’re trying.

Tom White
Yeah. Yeah. And I’m saying kudos to you guys. Right, for working with Google on that. I mean, that’s, that’s really impressive. You know, clearly, it’s about the provenance and what you’re doing and some of the ideas that you’ve had. So that’s fantastic. We would love to see what happens in the future within

Chris Slee
Google. I know it’ll be announced a little bit later today. There’ll be Oh, really?

Tom White
Yeah. Okay. Okay. Oh, amazing. So at the time of recording, it’s the 18th of May when for people listening to this, so check back through the comments and have a look. And you can see the release. So yeah, congratulations on that next. And final question. And I’ve really enjoyed having you on the show, Chris, what excites you? So, you know, for the future of AI, machine learning IoT? And what is your view on this whole utopian, dystopian view of the future? Where do you see it all going?

Chris Slee
I do not have a dystopian view of the future, I really look at it as a positive thing. And I, you know, we, as humans go through paradigm shifts, right. And we talk a lot about, you know, that, you know, when cars came along, what happened to the buggy builders, and Hey, hey, farmers, and I mean, there will be changes in how things work. But on the other side of those changes, is society more capable, better? You know, there’s some, there’s some question about, you know, would we have more leisure time or not? Or do we work more than in the past? I think I think we all, we will do different things than we do now. But I think that there’s an advantage to building better tools we have since the very beginning, since we learned how to make fire and then we learn how to chip Flint, and then we learn how to make you know, you know, houses, and we have always been on it on continual progress of tool enhancement. And this is just another tool of enhancement along our, our evolutionary path.

Tom White
Yeah, yeah. Completely agree. Completely agree. Chris, where can people find you online? social social media, find out more about include health and other things that you’re doing? Where should they look you up?

Chris Slee
Yeah, so the best place to find me is LinkedIn. Chris Slee on LinkedIn. And, and while I sort of have a love-hate with LinkedIn, I don’t accept everyone’s like, Oh, hey, let’s connect. But if someone tells me Hey, I saw you on a podcast, it was really good. I want to talk to you about it. I will definitely connect with you. The other side is my public tweeting and it’s just @Chrisslee. So those are really the two best places if you do want to have a chat to get hold of me.

Tom White
And if you’d like to find out more about Chris and the ventures he’s involved with, please check the comments below. Sign up to our newsletter for the latest releases of The IoT podcast Show, get involved in the conversation, and we hope to see you on the next episode.

 

The IoT Podcast Team

The IoT Podcast is powered by Paratus People, a leading organisation in IoT Talent Solutions.

Innovation is at the heart of IoT, it is our passion to explore and learn more about this fast paced and transforming sector.

Connect & Get Involved

Your subscription could not be saved. Please try again.
Your subscription has been successful.
Subscribe to our newsletter to be amongst the first to find out exclusive information about The IoT Podcast.

We use Sendinblue as our marketing platform. By Clicking below to submit this form, you acknowledge that the information you provided will be transferred to Sendinblue for processing in accordance with their href="https://www.sendinblue.com/legal/termsofuse/">terms of use