Edge Computing is the Foundation for Scaled Smart Cities. How Can the Industry Accelerate Adoption?

Hello, everyone, and welcome to another episode of Experts Talk Market Scale's premier debate and discussion round table where we sit down with the top voices in your industry to talk shop on the major topics, technologies, trends, you name it, that are shaping your voices, the experts, the thought leaders, the professionals that are making it happen in your industry every day, getting them together. And again, getting actionable with analysis around these trends, how to overcome the challenges, how to really take advantage of the opportunities that are shaping your market, and again, getting actionable with that analysis. So I'm happy to be here with a great panel, which we'll introduce here shortly. Per usual, I'm your host, Daniel Litwin, the voice of b two b. Welcome to another episode of the show. If this is your first time joining us on Experts Talk, welcome. We are happy to have you tuning in to some great expert led discussion. If you're a returning member, welcome back. But regardless of if you've been here before or not, head to market scale dot com to tap into some of our previous conversations. We've been going live several times already this month and have several great expert led discussions primed for the rest of May. We wanna make sure that, you don't miss any of them. So go check out some of the previous discussions we've already had this month published live on market scale dot com, and check out our live page, again, on market scale dot com to see some of the the upcoming discussions that we're gonna, host here throughout the rest of the month. Alright. Let's jump into it, folks. I'm gonna go ahead and give you all a little run down on today's discussion, which you can see previewed below. But we're gonna be talking edge computing and its role in smart city development, its current use cases, and where edge computing is going to take smart city use cases and development moving forward. So as more cities embrace the power of smart city projects, from data driven safety projects to connected museums, to next gen emergency services, smart water and transportation initiatives, you name it. Right? Every layer of the modern city is likely going to find some benefit from a smart city initiative, whether now or in the future. And it's becoming clear that scaled smart cities are going to present a massive computational challenge. Right? Each IoT sensor, each intelligent node, each, zone of data capture is, again, capturing constant and unprecedented levels of data. Meaning that reliable computers, that can capture and process that data in real time are going to be the bedrock of any successful smart city project. This is where edge computing comes into focus. Right? Edge computing, specifically rugged edge computing, is gonna play a key role. It's gonna play a foundational role, in developing that smart city bedrock of, you know, technologies and strategies. But we wanted to get specific with our discussion today, and really get a pulse check check based on today's, you know, most exciting smart city use cases, and also the ones on the horizon, what role will edge computing play in supporting smart city projects at large? Right? How capable is rugged edge computing in tackling today's and tomorrow's ideal smart city projects? How are IoT solutions providers working to integrate powerful edge computing into their solutions or collaborate with edge computing professionals to execute on some of these use cases? And how prepared are the decision makers behind the scenes of smart cities to make the right decisions around investing in and making best use of edge computing. There's a whole ecosystem to unpack here, some tech focused, some a little more industry collaboration focused, and we're gonna try to touch on all of it here with our panelists. Before we introduce them though, I'd like to give a quick shout to our featured partner for today's episode, which is Premio. If you're ready to take your edge computing to the next level, meet Premio Inc, your premier partner in rugged and industrial computing solutions. From fanless mini computers to high performance servers, Premio equips your business with the most reliable and robust computing technologies. If you wanna experience the power of their edge boost tech in rugged environments, partner up with Premium. They ensure optimal performance and longevity with their modular and scalable solutions engineered for the most demanding applications. It makes them a go to choice for industries like automation, transportation, and health care. So choose Premio for computing technology that's built rugged and ready, and discover more about their cutting edge solutions and how they can drive your success forward by visiting premio inc dot com. Again, premio, I n c dot com. Alright. I think we're ready to go ahead and jump over to introduce our panelists. So thank you again to Premio, and, I'm excited to introduce our four panelists here today for our discussion. Welcome to the four of you. It's a pleasure to have you here, and I'm looking forward to unpacking the diverse perspectives of the panelists that we have on board here for Experts Talk. So welcome to the four of you. We'll go down the line, give everyone their proper intro. First up, we're joined by mister Dave Fick. He's CEO and cofounder of Mythic. Dave, welcome. How are you doing today? Good. Good to be here. Yeah. Welcome to the show. Pleasure having you on. We're also joined today by mister Ira Kerner. He's real estate lead at the Digit Group. Ira, welcome. How are you? I'm well. Good morning, everybody. Glad to be here. Yes. Good morning indeed. Thank you again for joining us. We're also joined by mister Mitch Lewis. He's a research analyst at the Futurum Group. Mitch, welcome to the show. How are you? Thanks. Doing well. Thank you for having me on here. Absolutely. Welcome. And last but not least, we're joined by mister Dustin Situ. He's director of product marketing at Premio. Dustin, welcome. Good to have you on the show. How are you? Doing well. I'm glad to be back. Good to speak with the voice to b two b. Yes, sir. Always a pleasure getting to chat, and I'm looking forward to discussing, Edge Computing here and its foundational role in smart city development with a larger crew. So let's get right into it, folks. I want to start by defining for our audience, where smart cities are at, sort of as a whole in terms of their development and their, utility. Right? And we'll also do the same for edge computing before we start to connect the dots a little bit more. But for context, we got a recent pulse on the top ten smart cities around the globe. This was IMD's smart city index for twenty twenty four. They're sort of one of the premier outlets that's gauging the success, the quality, the technical performance of top urban metros across the world, and where they rank in terms of their smart city development. And they found that several cities in Europe and Asia are dominating the world's smart city field. Zurich, Oslo, Canberra, Geneva, Singapore, Those were in the top five. We also saw cities like London, Abu Dhabi, Dubai, Beijing, Amsterdam round out the larger top twenty. I encourage you all to go check out the whole report yourselves. But for our panelists here, let's start with kind of a pulse check on where smart cities are at today. Right? How far along are some of the most advanced smart cities that you've seen when we look at some of their projects and their priorities? And what sort of specific challenges do smart city, smart cities as a whole and their individual projects face that make edge computing such a a crucial element for their success? Based on what you've seen, what you've worked with, where are smart cities in their developmental journey today? From what I've seen, it it's, all all very early. There you know, at this point, there's a lot of interest in adding technology, and some cities are are able to move more quickly. But, even the the the projects that I've seen most recently are are very early looking at tracking, for instance, you know, the conditions of the roads, conditions of the the trees in the cities, and also trying to track, just general, like, pollution in the area. And I think there's this grand vision of being able you know, as a city manager, being able to see a dashboard of the health of all the different systems and all of the different environmental conditions in the area and use that data to make, data driven decisions around where to prioritize resources. If you think about, like, how complex cities are, all of the, innumerable number of systems of of people and infrastructure and and environment, being able to track all that and make decisions is very difficult. And so I've seen some very exciting projects get started, but I haven't I don't think that we're anywhere near where, where we can get to. And a lot of that has comes down to what computing is available and and, and, you know, a lot of technologies are limited by the availability of high performance computing in these environments. And so, I think as we see the computing technology develop and the software technology develop, this will get more and more exciting. But I think this is a space that won't be stable for decades. Yeah. I kinda have a somewhat thought. Seems pretty early on. I think, you know, the foundation of of building these smart cities comes from a lot of different, piece parts in terms of technology, that are all kind of starting to come together. So, you know, you have different types of iot sensors, things like five gs. Now ai is really picking up steam, to kind of help all those things go together. And of course, as we'll get into, the capability of the servers to be, you know, having more powerful servers out of the edge to kind of put all these things together. So I think it's still pretty early on. And a little interesting too. As you walk through the list, you know, not a big American presence on there. So from a from an American standpoint, definitely seems pretty definitely pretty early. Yeah. I would I would chime in as well. I would think we are definitely pretty early, but I do believe we're on an inflection point. Inflection point being, we're at a perfect time where technology is starting to drive the needs for a smart city. The both the ultimate goal, right, for a smart city, I think, is to automate a controlled loop of autonomy. But how you do that controlled loop of autonomy and the projects that are coming forth require so many different transformative technologies. Right? Everything from the IoT sensor that's funneling the data to create the situational awareness. Right? The OT technology that's driving back to the IT technology, and then you're creating kind of a mesh network for machine to machine communication through infrastructures that's built through edge computing. And if you even dive into edge computing alone, edge computing, the complexity of the ecosystem, it's connecting all the dots from sensor to compute architecture to data telemetry to even the AI, modeling side of that with the deep learning models that are moving out to the edge. It is early, but I think, a good point that Ira mentioned was specifically, right, if United States is so is so behind, there needs to be some type of government regulation or subsidy that's really driving forth. Right? One major comparison, I think, is is China. China, in terms of the government, is fully aware of all the different things that are going on, I would say, in their country based on their their governmental regulation. So a lot of their smart city projects tied into security and surveillance are heavily way ahead of, United States in in some of the cities. So but I believe the technology is is at the inflection point, and and we're starting to kick that off. And then, Ira, I'm curious to get your thoughts on this one too coming from a, real estate background and having worked on, you know, whether at a small or large scale, the deployment of, smart city style projects and use cases, where are you seeing the development of smart cities today? Well, I think that, as far as on a real estate basis, you know, I'm looking at it from another, perspective, another point of view that, beyond the technology, let's get into the logistics and the infrastructure. You know? What's the most effective way to house, you know, these, these facilities, that will maintain the the servers and everything that's involved. So I'm I'm really approaching this from more of a physical point of view rather than the technology point of view. My my belief is we can actually create a lot of value in real estate, by rehabbing bad real estate and maximizing the use, to accommodate the smart city development. K. Well, I think that in you know, you've all raised interesting points here that basically go to show there's a lot of different motivating factors that are guiding the development of smart cities today. It could be everything from literally where do we house some of these edge computers. Right? And, retrofit our city aesthetically or functionally to support smart cities. It could be, you know, at a technological level, how advanced adopting and making best use of AI technologies, of the balance between, you know, cloud networks and environments and, you know, really small scale but powerful edge computing nodes, right, across a spread of of IoT use cases. So there's a lot of motivating factors here and a lot of different battlefields, really, where smart cities are having to, prove themselves and having to bring different people to the table to, develop and to actually see some successes in the grand vision of a connected, smart, you know, citizen focused, service focused, city infrastructure, and, you know, feel and environment. Right? And so I wanna hone in on number one on that list that I broke down. Again, the, IMD's smart city index for twenty twenty four. Zurich was the number one smart city in terms of its projects, its solutions, its technologies, its infrastructure. And respondents from the survey who were citizens in Zurich, they weighed in on the technology that's performing best for them. Sort of in what use cases do they feel like they have some kind of smart ecosystem that is supporting their day to day. And I wanted to just list these off real quick because I found them interesting. Online purchasing of tickets for events and outings was, like, number one. Great. You know? Very well integrated smart city ecosystem for their museum, and exhibit outings. Basic reliable Internet speed, online access to job listings and transportation scheduling, traffic congestion data and information in real time, processing of ID documents. These were some of the ones that just won out. Right? Very sort of quality of life, day to day style, you know, smart city use cases, you could say. Where they were performing worst or where they felt like there was room to improve included things like air pollution monitoring, parking visibility, CCTV camera, sort of proliferation, as well as an open forum for proposing new ideas for city life in a more, I guess, connected, and tech forward, fashion, right, or environment. So, again, these are a lot of public facing services that are very tangible. They're very quality of life focused. They're not necessarily, you know, emergency service focused per se. And I wouldn't also say that they sort of scratch the itch of, the most sort of cutting edge or advanced version of smart city infrastructure and use cases that we might imagine in our heads. But I'm curious though, with some of the, you know, use cases that I listed out, what do you think this says about the way smart cities are developing their technology solutions? And what role do you see edge computing playing in supporting maybe some of these entry level smart city projects. Right? And why is it important to start to invest properly in the right edge computing solution for these projects that maybe aren't the most data intensive, but will we'll lay that proper foundation that will prepare the city for future projects that maybe are a little more data heavy. Give us your thoughts here on the connection again between edge computing and this current crop of IoT and, smart city use cases. I can go. I I think it kind of, you know, backs up what a lot of us were saying that this is pretty early. And that's not to be disparaging about anything they're doing, but, you know, when I think about smart cities, it's really the idea is really more on that cutting edge, things that they say they're not doing well, maybe like the air pollution or some of the emergency services, things things like that. Whereas, you know, online ticketing, that's great, but it definitely seems like a starting point. Right? So I think maybe that's the approach is, pick the things that are easy, or very straightforward, focus on quality of life. And then you can kinda build from there, and tackle things that are more cutting edge, maybe, more smart city like, you know, emergency services, You know monitoring traffic integrating things into hospitals all those cool sorts of things, but you have to you have to start somewhere. And I think, starting with simpler, quality of life things that integrate, you know, computing and data into people's, day to day life is is a good place to start. Yeah. I I agree with Mitch in that. I think we are, at the you know, we've all said we're at the very beginning of it, but at the end of the day, we're almost all in a kind of a a beta test mode for the technology and how it translates to the cities. And the end goal, the result is we we want interconnectivity with everything, which is what's gonna happen, but it's gonna require a lot of evolution. And and as I alluded to earlier, a lot of physical, you know, consideration of where where we're gonna house all the, you know, the machines, you know, the machines that help us enable the technology. You know, I think So I think oh, go ahead. I I was I was gonna say, you know, I think one of the things that was brought up here is that, you know, when we talk about smart cities, there's lots of different types of technologies. And, so this wouldn't really consider it, like, one monolithic system. It's it's more of a, like, a category of systems to make, life easier in the city for for people and and for the government. And so I think there, you know, there's lots of different ideas on how to make this easier. I'd love to be able to you know, when we when I when I drive into Austin, which is where I I live, being able to get directed to parking and not have to hunt around would be, excellent. And and having you know, we already have real time traffic conditions, which helps with navigation, and I I appreciate that. I'm excited to see what happens in the future with, more real time monitoring of, I saw this interesting project about, potholes, which seems really, dumb. But, you know, around here, there's frequently issues on the road where some something's dropped under the road. Maybe it's a piece of material that fell off of a pickup truck or, you know, there's a stalled car or there's, like I said, a pothole or a damaged guardrail. And just being able to notify, the the local government that, hey. This issue exists, but have that done automatically so that it can be handled immediately. There's a huge progression going from there all the way to, you know, the ultimate of having a a dashboard where you can see absolutely everything about the city and manage it from a almost like a big control room. And, you know, I think as these systems come online, the founders and, entrepreneurs that are trying to, develop these systems will need to make sure that they're solving the the most salient problems for cities today. And and, and and so I I see this being a big collection of of different groups, we're, you know, trying to solve individual problem problems. Yeah. So to add to that, a lot of what you mentioned, Daniel, like, each of those type of, I guess, smart city projects or things that are going on in that city really heavily tie into data. You know, I think data is extremely important. I think in the past decade, that data has been driving what we've defined as the cloud. But, I mean, if you really focus in a lot of those key projects, you know, a lot of that won't be successful without a strong backbone of what edge computing is. And I think edge computing is so broad as a whole, but I think if you define it simply, it's really just moving a lot of this compute power traditionally that was in the cloud closer to where IoT sensors are generated. Right? Once you're able to do that, you're able to actually drive key benefits for whatever type of application because you have ultra low latency, you have better security, right, privacy risks, and then more reliability. So once you have all those things come together, I think you'll have cities start to regulate, but also, streamline a lot of, benefits for the the people in the city in their smart city projects. I think there's some flexibility too. Like, if you have the compute directly on the devices that are, you know, the sensors that are monitoring the city and you don't need to have a bunch of other infrastructure supporting it, it becomes easier to say, like, okay. Let's, you know, deploy these sensors throughout the city. Now they plug into, you know, existing infrastructure or they don't need, like, a a a bunch of new server space that can make it that can reduce the barriers to bring new computing online. But now the challenge there is that that computing needs to be inexpensive. It needs to be, low power and rugged, so you can't have, like, a a huge box at every sensor. If it can be miniaturized, fanless, environmentally enclosed, that makes a big difference. And so from what we've seen, a lot of the challenges with these new technologies coming online is just that it becomes too expensive. You know, you're creating some value, like like we were talking about. You know? If you're even for the parking situation, you wanna identify where is parking available and direct people to that. Well, if it costs enormous amount of money to deploy that capability, then you're not going to do it. But if it can be really inexpensive, then that becomes a no brainer for cities all around the the country. And so I think, you know, one of the things that we really need to make happen on the computing side is can we bring down that cost, which is a combination of, not only the the cost of the silicon, but also the the complexity of the enclosure, which comes from the power consumption and and, just really trying to make the thing miniature miniaturized. I mean, yeah. That's that's exactly what Premio deals with on a day to day basis or for the last thirty five plus years is taking the silicon and finding a way to ruggedize the product and push it to extremes. Lots of those extremes and lots of the projects are going into a lot of wide operating temperature, shock and vibration, wow wide power input. And I would say our goal or, you know, in terms you mentioned cost. Right? Our goal is to provide a wide portfolio that's, cost sensitive in the sense, but actually uses all the latest and greatest, semiconductor technologies. That's a commercial off the shelf product. So, you know, it's it's it's an ecosystem of different partners. Right? So only from my kinda staying within my lane and and and within my scope. Right? We are providing a wide portfolio of computers, that are plug and play, that are off the shelf, that could be used in an array of sensor gateway that's kind of managing the data telemetry. And, you know, y'all mentioned, that in a lot of ways, smart cities are still kinda beta testing. Like, even the most advanced Zurich level smart cities are still just kinda dipping their toes in the water in terms of tangible day to day services that, citizens can feel and interact with and actually even report on. Right? And even, like, give feedback on, yeah, I could feel this aspect of my day to day is enhanced by smart city technology. But I'm curious if y'all are seeing that in that beta testing mode, as cities and their decision makers are trialing these, you know, smart city projects, are they also getting beta test mode e with edge computing as well. Right? Is edge computing a key part of where they're experimenting to make sure that they're investing in the right foundations? Or are you seeing more of a let's adopt IoT sensors, let's adopt smart city technologies, and take advantage of maybe existing cloud that we already have, and edge computing is more of an afterthought. Kinda what what do we see in that dynamic? Right? As smart cities develop, is edge computing treated as a forefront of that development or more of an afterthought? Or what are we seeing? I I think they're these products are usually put together as a service. And so, like, this I don't think the city goes and directly purchases the the edge computing. They evaluate different services. You know, it'll be a company that says, hey. We can monitor your parking situation, and they'll have some API or and and website that's based on that that provides that. And so there will be a a part of their their sales pitch is going to be what is the computing infrastructure that's required. So is it, you know, there's computing at every camera or there's a big server or there is a a combination. They might offer different options, And so that becomes a, part of their their sales pitch on, like, what that service looks like. And then, of course, you know, the service can be a platform and integrate into other types of, systems. So I don't think the city itself directly invests in, the the sensor or, like, the computing for those sensors. They purchase the services. But if they have a server farm that's kind of backing all that, so where does that data go? Does it go to the cloud or does it go to, like, a centralized set of servers at the city? That's where they end up investing money, for their own infrastructure. And and and that's the point that I was making earlier that if if there's a physical location to store, those units, it it can be very costly. But we have opportunities throughout the country to utilize, underserved, under underused retail, you know, kind of, failing shopping centers. You don't need to be, you know, in the main part of town. You don't need to be on Main and Main to, you know, to have this you can be in the worst part of town. You can be in a shopping center that's ninety percent vacant. And when you're able to find that, when you're able to find an underperforming shopping center with a lot of vacancy, well, then you have a lot of leverage to negotiate very, very reasonable, you know, economics to the extent of, you know, the, the physical, you know, placement of these of these stacks, these units. And and by doing that, by the way, on the real estate end, you're also creating a lot of value. Yeah. I mean, I think building out smart city applications and and building out, you know, what is the right type of edge computing kinda go, hand in hand, and it it, there's a lot of factors. You know, the the key one really with edge being how critical is the performance or how latency sensitive is it? You know, as I think Dave was saying, just earlier, like, how much of this can we do directly on a device? And, cities need to kind of figure out when is that the right approach versus maybe you it's not as mission mission critical or as latency sensitive. Can we take something in, send it back to the cloud to do some processing, whatever, and then and then bring it back. Or, you know, in what cases do we need to be keeping whatever data archiving it back to the cloud, things like that. So, I think it's very use case specific. And as these cities kind of go beyond, their their beta phase where they are now, into building out more use cases. That's something they're gonna have to kinda figure out. Yeah. I don't I don't think the city. I agree. The cities are not the ones who are the technology experts. The technology experts are the solution integrators who are able to stitch the ecosystem together and map it all together. So, you know, when I say that, it's really just combining the hardware, the software, the services, and pushing that, into a smart city project. That will determine what's best, whether it be in the cloud or the edge. I think as we continue forward, it's not gonna be either or, you know, the edge and the cloud definitely work in tandem. I think if we look at the example of AI, you know, with without situational awareness, situational awareness, before even moving it out to the edge in order to do the inference detection specifically. You need to have both those working in tandem with the, the the wireless connectivity. Yeah. I think that's a that's a huge point because I think to me, AI is going to be very, integral to building out smart cities, right? If you have all these different sensors, to gather data, they're kind of your eyes and your ears and whatever all your senses and now we have more of a of a brain right with the new ai models, kind of driving all this, but no one wants to be training, doing model training really at the edge, at least not for most use cases. But you do probably a lot of inferencing is going to be at the edge because you wanna take that data in and quickly make a decision. So, like you just said, it's that balance of cloud or some other data center and then bringing it to edge and, you know, using AI to drive whatever, edge application, smart city application that you have. But isn't the edge and AI, aren't they they complement each other rather than they compete with each other? Yeah. Absolutely. With with the thing with the edge, we're talking about two different things. Right? We're collecting data on one hand. And the use of smart city technology is to, it is to, as I said earlier, is to provide interconnectivity, and and services for the people within a municipality. How does AI factor into that? I I think Oh, that's You know, it's it's the inferencing part. So if you deploy your model, you know, at the edge and then as you're bringing data in, you can use whatever AI model you've deployed at the edge to quickly be making decisions or you know driving these things you know, figuring out traffic patterns, you know, examining the the trees to see if they look healthier or whatever it is, you know, looking for for potholes, and that AI mind can kind of, kind of do that right at the edge. I I think it really comes down to the the latency. We should really define latency and where AI is able to help with that is if you had to send data back to the cloud to actually identify an object that's been trained, for example, say, in security and surveillance, you're doing gun detection. Right? You need to have that ultra low latency very quickly detect detect, an object. If you had to send that to the cloud specifically, the latency would be too long. It'd be too costly. But once you are able to train that model in the cloud, which has all the resources, the AI, horsepower, you can move a smaller version of that model into a smaller version of a computer that has the horsepower to do the detection in real time where the security camera is sitting. And when you're able to do that, then you're able to do the AI. And, ultimately, what all the leading technologies are talking about is the generative AI. Right? Eventually, maybe this gun the AI model is able to actually train itself to learn something else eventually in the future. I think AI is a pretty broad term too. So there's been a lot of focus recently on chat GPT and, you know, chat bots. Those are gonna eventually turn into agent models that can take actions on your behalf. But I think when we're thinking about AI and smart cities today, I think we're typically thinking about, you know, you have the sensor that's that's collecting a stream of data, whether it's video or it's a vibration sensor or, you know, a variety of other ones and taking that and just identifying features in it. So is there a person in that video? Is there a is there a weapon? Is there, you know, is the tree healthy or not healthy? And so, you know, some of the, you know, the tree is know, is the tree healthy or not healthy? And so, you know, some of these things are important to do locally, not just because of latency, but because of bandwidth. If you have, you know, thousands and thousands of cameras all over your city, imagine the infrastructure you need to bring all that data to a centralized server location. If you can reduce that traffic to just, high level information, then that will reduce the cost of the infrastructure and make it more reliable. Because if the higher your requirements are for bandwidth, the more, the more difficult it is to keep that amount of bandwidth available to all the sensors throughout the city. And so I think what one of the things that we need to think about when we're building these systems is not just the, like the cost of the the compute units, but also the cost of how do you route all that data and where does it end up and try you know, part of edge computing is aiming to reduce that as much as possible. Yeah. And, you know, something else to keep in mind, like, for example, I did some reporting not too long ago on the, IDC Smart City Awards, and a lot of the awards that are capturing the attention of sort of the the more insular smart city community, right, are more of the cutting edge ones. The ones that are leveraging the best in class of AI, best in class of edge computing, and are solving, tougher challenges for cities, leveraging, again, IoT sensors and this ecosystem of smart tech to, really elevate that responsiveness or that service to the role or to the the, you know, status of really being a smart city initiative. And a lot of the ones that captured my attention I'm curious y'all's thoughts on this is really just one of my thoughts as sort of a a I'm curious y'all's thoughts on this is really just one of my thoughts as sort of a a pulse checker on a lot of these topics. But it seems as though the beta phase of smart cities is gonna be able to rely on, you know, some existing cloud infrastructure, some existing data center infrastructure. But as smart cities take on more of these initiatives that are emergency service oriented, where latency is critical, and where the, you know, the node itself that's capturing data is further, further, further out and deeper integrated into the infrastructure of the city, there's going to be more and more of a reliance on edge computing, rugged edge computing, and, you know, obviously, edge computing that can evolve to the conditions and the, continuous sort of, increase in data intake. I'm curious if you all agree with that assessment, if you see any other motivators that are going to push smart cities to more quickly or holistically embrace the kind of ruggedized edge computing that we've been talking about here today. That's, you know, doing more and more of the processing literally at the edge. Yeah. I think when when the city is looking at purchasing one of these systems, one of the questions that they're going to have is the total cost of ownership. And as you can push this computing to the edge, the the total cost of ownership should be less because you don't have to worry as much about, a whole bunch of supporting infrastructure that needs to scale up with it. And you kind of future proof yourself too where if you decide that, you know, you really want you know, you added some system to one portion of the city, now you're adding it to another portion of the city. You can start adding more devices locally at the edge, and you don't need to worry as much about all of the other infrastructure that needs to support it. You know, I think I think it's maybe understated just how challenging it is to have systems deployed all over, you know, miles and miles of space and and and routing traffic from it. I mean, just trying to, you know, route Internet from one room to the other in our house seems like a challenge. I can't imagine doing it across the city. And so if you have to do that with really, you know, super high bandwidth fiber optic cables and, and you have to have excellent coverage over every street and and every building top and whatnot that that just adds to the cost. And so I think from, like, a a vendor standpoint, if you're the integrator putting this technology together and you're trying to get that sale, it is going to make it easier for you if you don't need a bunch of supporting infrastructure. And so I think that's going to push, the the vendors themselves to try to avoid requiring a bunch of, you know, additional infrastructure beyond just the the devices themselves. Yeah. I mean, I think, Daniel, to your point about ruggedizing servers, I I agree. I mean, I think latency is right. The the driver here, specifically for and when you need the low latency is going to be those, you know, emergency services, you know, anything that you need really that immediate kind of response. So because of that, you you bring things to the edge, because then you're not doing your computing in a nice, safe data center. You want your server to be able to hold up and, you know, be resistant to, dust or vibration or You know heat, cold, whatever it is. So, yeah, I mean, I think that's kind of at the core of it. But then it becomes which use cases, do you really need, some to bring down that lead and see which things can you can you send out to the cloud maybe? And then in the meantime, right, as, you know, cities take on their first or second smart city initiative, likely they're going to be looking at, you know, maybe some of the investments they've made in the past, that they're a little more familiar with, the technology partners they know a little better, they might lean towards taking advantage of data center infrastructure, towards investments in infrastructure that supports cloud services rather than, you know, suite of ruggedized edge computing nodes. So, Ira, I'm curious on your end, you know, any advice or perspective you might offer to cities as they look to, especially American cities that need to get up on that top twenty, for the smart city index. Are there areas where they can start to take advantage of existing infrastructure or invest in infrastructure they're more familiar with to support Smart City projects, you know, users or or rather municipalities and cities, they can use the less expensive real estate, the underused real estate to to accommodate this. It's frankly, I think it's it's it's a perfect combination. You don't need a two hundred thousand square foot data center to accommodate this. I think that if you can have sort of many data centers throughout a town of of of bad retail, quite frankly, ten thousand square feet here, fifteen thousand square feet, and you do it in multiple locations. As I said earlier, you're creating a lot of value for that real estate, but you're also I think, you're making just logistically, you're making things a lot easier. Do you see challenges with securing those? You know, you mentioned they're less desirable in maybe, like, an abandoned shopping mall. Like, if the equipment's expensive and valuable, do do you have you seen how have you seen cities take on the security challenge with that, making sure that the you know, all of the data that's there is protected and, you know, you don't wanna have a a data leak on on one of these servers. Yeah. Of course. And and that's that's always a consideration, and that that is something I look. I think that's the big question. I think that is, you know, the big caveat with what I'm proposing of how do you make sure that these locations are secure. Now I'm not saying do this in a blighted area where there are security threats, you know, around every corner. But I do think every town has, you know, your good retail and your bad retail. And in the good retail, you you can you know, the rents can be depending on where you are in the country. And here in the northeast, it's thirty five square foot. But those those markets also have retail areas that were once at some point decent but are now no longer in favor. And you can negotiate rents that could be single digits, You know, to talk about how can we, keep those secure, you know, as I said, that's, I think, that is the real talking point here, but it it can be done. I mean, that's what you you put different measures in place to ensure that, you know, there's protection. Alright, team. Last question I've got for the squad here. I feel like we've done a good job here of of communicating and establishing why edge computing is going to be such a critical foundation for smart cities. Whether we're talking about some of the entry level, you know, types of investments in edge computing that may even include, you know, more localized data center investments, All the way to the more advanced ruggedized, edge computing modules that are going to support at the edge computing and higher risk, low latency, smart city initiatives. Right? And I'm I'm curious though where y'all are seeing some barriers and adoption of edge computing to support smart cities down to the actual sort of, municipality level, the city level. You know, y'all mentioned the cities aren't the tech experts. Right? Well, sure. But at the same time, they're still the ones making the, decisions. Right? They're still the ones investing in these projects and trusting their solutions providers who maybe are gonna present a black box solution that's both the sensor, the software, the data capture, and the edge computing. And so I'm curious where y'all feel the market still needs needs to improve some of its education. Right? Where can the larger edge computing ecosystem step forward to bring municipalities more to the table, get them more educated on the need for edge computing in the smart city ecosystem? And what do you think that looks like in practice, actually improving that educational ecosystem to support smart cities and their edge computing foundation? You know, you can make a case for, the fact that municipalities can save a significant amount of money with the use of and the implementation of smart cities. I read somewhere that, there are some proposals of, through the use of smart city technology, adjusting street lights in on highways and in in different, you know, municipal settings where the the the less traffic exists. They would lower the the the, you know, the power of the street lights. And, there was a study that this can save municipalities millions of dollars over over, you know, course of of time. So, you know, there's a lot of incentive for municipalities to step up and make these, these, you know, these these and and and implement these these technologies. So, it's just a matter of beta testing, I think, at this point. I I agree with that, Aaron. But I think the the flip side of that too is that, you know, while these initiatives can cost can save money, you know, they they cost money, for the for the cities to deploy as well. So, I think there's kind of a mix of, you know, being expensive and maybe not having a full grasp on, you know, if the city is not the the technical expert not having a full grasp on the possibilities or the requirements, or some of the technologies that are maybe going to drive some of these things like AI are still, considered kind of new. You know, it's not necessarily new, but, a lot of the, the developments, you know, innovation in it is, and not super proven out. So maybe there's still some some hesitancy there to actually, deploy something like that. Yeah. I don't think the the cities themselves aren't creating the technology. And so if I put myself in their position, they'll have a vendor come to them and say, you know, in this example of the streetlight scenario, you know, the vendor will say, like, hey. We can save you millions of dollars a year on on, on your lighting infrastructure and, you know, there's other benefits as well. Maybe we can identify where there's lights that are out or, you know, where you don't have enough lighting. And, you know, here are all these great benefits. As the city, the the question is, well, how do you evaluate that? Like, do you just take them at their word and and purchase the system? Do they have case studies at other cities that that have deployed this? And can they figure out if that is gonna work as well in their environment as it did in in that city? And so, you know, I I think a lot of times, this isn't really about, you know, can the city deploy new technology. It's about more of how can the city get confidence in the claims made about different technologies, not just in terms of whether the technology works at all, but does it work in their environment versus the the one that it was tested in previously? Is is that all part of a very large picture that we're trying to accomplish of total interconnectivity? You know, you you want the, DPW to know when the when the local garbage cans are filled. You know, you want residents to know if there, are available parking spaces on the street. You know, if possibly, you wanna lower the energy needed to, to light up, you know, an empty highway. That's all part of connectivity and and keeping people more involved and better informed. You're not only receiving data, but you're collecting the data to distribute. I think it's it's a lot, easier said than actually done. I I mean, I by no means am a expert in terms of municipality and kind of the rules and regulation, but I would defer back kind of to government intervention. I think when you do have a push from government intervention, things move pretty quickly. A good example would be, semiconductors, right, in the in the chips act. Right? I think before congress pushed the need to bring onshore manufacturing semiconductor, a lot of people in this country didn't even know what a semiconductor was. But with all the the government subsidies back into it, right, multiple investments into these major tier one semiconductor companies from Intel, TSMC, Samsung, GlobalFoundries, Micron. Right? They're all bringing this this technology back onshore. And my point I'm trying to make is that, if you have this this this government push or government incentive to really drive forward some type of new technology, that's gonna drive the tier one technologists or tech companies to really educate the market down, right, from a top down and really facilitate a need through their use case, their technology. And from there, that kinda trickles down into real case real case use case studies, and from there, commercialization within the municipality. So that's that's kind of my my standpoint. I agree with that. Yeah. And then, Dustin, I just wanna throw you one more question here. You know, being that, you're sort of the the edge computing industry voice here on the roundtable. What do you see other players, yourselves included, in the edge computing industry doing to advocate for yourselves as, you know, key part of smart city investments? I know that, you know, premium does a lot of partnerships with, other solutions providers that leverage, Premio products for their smart city solution. And so, you know, how are you seeing the larger edge computing industry plant its flag and say, we are an essential part of, you know, the, strategy here for investing in and supporting smart city projects. Consider us. Make sure that you're thinking about, you know, investments in edge computing as a part of that long and short game. What's y'all strategy there and what are you seeing? Yeah. So I would say there there's so many layers to how you run business and how you actually facilitate real business. Right? So from an edge compute standpoint, if you kind of look of all the different silicon, the silicon itself relies on system builders to take that technology and incorporate it into a system level. Without that, you wouldn't even have a system to deploy. So, I mean, it takes system level. Without that, you wouldn't even have a system to deploy. So, I mean, it takes each tier to successfully push forward whatever their tech technology is, combine that into a solution, and pass it on to the the next type of solution integrator. So my point is, within the ecosystem, you need to make sure we're all working together in tandem. And the scope of the project is very important because without defining the scope within that project, it's not you're not gonna be able to successfully kind of choose the technology or, the things that you need to successfully extremely complicated. So I agree with everyone on the panel that we're still early on in a lot of our our smart city projects. But I think it's an inflection point because we do have the technology in place. It's just now government intervention pushing forward with the the goals of what they're looking for. And then from there, I think we can get to, one step closer to a smart city. And I love that takeaway to close things out. Right? In a lot of ways, it seems like we've actually conquered a lot of the technology challenges of supporting ruggedized edge computing, you know, necessary smart city initiatives. Right? We have the computers. We have the the vendors that are integrating edge computing into their products. We have the ecosystems that the necessities of cloud, of data centers, of ruggedized edge computing, all supporting, a network of IoT nodes for smart city initiatives. But really now it's about execution, it's about market education, it's about municipality education, and about aligning on priorities for these projects, the tech stack needed to support them, and how these, projects can start to domino. Right? Where you invest in sort of the beta phase, but how those investments actually lay a key foundation to support the more intensive, the more data heavy, the more, you know, cutting edge smart city style projects and use cases. So with that, I think we've got our work cut out for us as an industry, but we'll go ahead and wrap things up for this panel and this discussion. I'm very grateful to have the four of y'all here for this analysis. Thank you for your perspectives and your your varied takes, and lenses here to give us a pulse check on edge computing's critical foundational role to support our smart city today and our smart city tomorrows. So thank you again to Dave Fick, CEO and cofounder of Mythic, Ira Kerner, real estate lead at the Digit Group, Mitch Lewis, research analyst at the Futurum Group. And Dustin C2, director of product marketing at Premio. Dave, Ira, Mitch, and Dustin, thanks to the four of you. We'll definitely have you all back on soon for further discussions as we see smart cities continue to progress across the world. Thanks again to the four of you. Thank you. Great. Thank you very much. Good to be here. And thank you everyone for tuning in to today's episode of Experts Talk. If you like what you heard and saw and you want previous episodes, head to market scale dot com where you can find our full catalog of episodes and discussions with top voices in your industry. You can also head to market scale dot com for a catalog of our future and upcoming episodes, including some of the ones we've got coming up tomorrow and Thursday, as well as for the rest of May. And if you yourself wanna be a panelist here on Experts Talk, guess what? My DMs are open. You can ping me on LinkedIn, shoot me a message, email me, daniel dot litwin at market scale dot com. Give yourself a, you know, a small elevator pitch of your background and expertise, and who knows, you may just find yourself in the hot seat here of Experts Talk. Alright, folks. Signing off for this Tuesday morning episode. I'm your host, Daniel Litwin, the voice of b two b, and we'll catch you on the next episode of Experts Talk.