How will edge technologies and AI shape the future of our cities? In this episode, Bill sits down with John Lockhart, Lead Sustainability Technologist, Global Digital Cities at Dell, to discuss all things digital cities. They dive into how city leaders can approach digital transformation and tackle the problems in their cities, and discuss digital twins and the impact of AI.
How will edge technologies and AI shape the future of our cities? In this episode, Bill sits down with John Lockhart, Lead Sustainability Technologist, Global Digital Cities at Dell, to discuss all things digital cities. They dive into how city leaders can approach digital transformation and tackle the problems in their cities, and discuss digital twins and the impact of AI.
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“What's happening at the edge from an IOT perspective, as well as what's happening in the data center, they're able to really drive insights from the value they're gaining at the edge. And then that in turn delivers on the outcomes that leaders are providing their, whether it's constituents from a city perspective or whether it's shareholders from an enterprise perspective."
“Cities have really been dealing with a lot of different technology challenges as they come across a problem over the past 30, 40 years, they'll apply a solution that solves a particular problem. But that's really like putting a band-aid, rather than trying to find the root cause and see how they can drive different results.”
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(01:05) How John got started in tech
(03:26) Applied IOT in digital cities
(05:46) What makes a smart city smart?
(08:56) Where can city leaders begin?
(10:23) What obstacles do city leaders face?
(13:53) John’s work at the live lab incubator
(16:48) How do cities decide what problems to tackle?
(20:45) Greenfield versus brownfield
(26:31) Digital twins in cities
(29:57) Understanding ROI in digital cities
(38:42) How will AI change our cities?
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Over the Edge is brought to you by Dell Technologies to unlock the potential of your infrastructure with edge solutions. From hardware and software to data and operations, across your entire multi-cloud environment, we’re here to help you simplify your edge so you can generate more value. Learn more by visiting dell.com/edge for more information or click on the link in the show notes.
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Over the Edge is hosted by Bill Pfeifer, and was created by Matt Trifiro and Ian Faison. Executive producers are Matt Trifiro, Ian Faison, Jon Libbey and Kyle Rusca. The show producer is Erin Stenhouse. The audio engineer is Brian Thomas. Additional production support from Elisabeth Plutko and Eric Platenyk.
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Follow Bill on LinkedIn
Connect with John Lockhart on LinkedIn
Artificial Intelligence and Gen AI in Smart Cities, white paper by John Lockhart
Narrator: [00:00:00] Hello and welcome to Over the Edge. This episode features an interview between Bill Pfeiffer and John Lockhart, the lead sustainability technologist of global digital cities at Dell Technologies. In this conversation, Bill and John discuss all things digital cities, diving into how city leaders can approach digital transformation and how edge technologies and AI will impact the future of cities across the globe.
But before we get into it, here's a brief word from our sponsors.
Narrator 2: Over the Edge is brought to you by Dell Technologies to unlock the potential of your infrastructure with Edge solutions. From hardware and software to data and operations, across your entire multi cloud environment, we're here to help you simplify your Edge so that you can generate more value.
Learn more by visiting dell. com slash edge for more information or click on the link in the show notes.
Narrator 1: And now, please enjoy this interview between Bill Pfeiffer and John Lockhart, Lead [00:01:00] Sustainability Technologist of Global Digital Cities at Dell Technologies.
Bill: So John, you work in Dell's Digital Cities business unit, and the things that are happening in digital cities are just mind blowing these days.
So I've been excited to have this conversation and I'm glad we can finally make it happen. By way of background, how did you get started in technology?
John: Yeah, well, Bill, great. Thanks for having me on this show. I really appreciate the opportunity here. And obviously, um, a lot of us have interesting backgrounds.
I started initially in tech, basically after graduation at university. I had been engaged to my wife. And we decided to move. She was from Thailand and we moved to Thailand and I ended up opening a computer store and really built machines back in the early nineties. And from that, as their economy kind of soured towards 1997, I ended up moving back into Seattle where my son was born and started working for [00:02:00] Microsoft.
And that was probably the first exciting job that I had. A few years later, decided to kind of jump off of a cliff and join a startup in Silicon Valley. And, you know, little beknownst to me at the time, you're young and you feel like you can take the world on. I thought that this would be a great opportunity.
A lot of different things happening. And I ended up in the midst of the dot com bust. As many people did. Yeah. What was great about that is a lot of the companies that we worked for, we built some of the key technologies that really launched as, you know, part of these startups, but inevitably a lot of them and their CEOs.
Potentially made some not so great investments resulting in that collapsing and I ended up leaving Silicon Valley and found a job at Citrix where I started in virtualization, both on the website, the app side, really in the early parts of 2003, 2004 timeframe. And that, you know, obviously it was a start over from a career perspective, but it gave me a breadth of knowledge that really was [00:03:00] around solutioning.
And about eight years later, I came across to Dell as part of our. Desktop Virtualization Solution Team. And then from there, it just, one thing led to another, and I ended up leading a group in Singapore that turned into our IoT business, that again, later after that, turned into the digital cities back in the end of 2017.
Since then, I haven't looked back. So I
Bill: like that. You went into IoT. You said that kind of became the digital cities. business, which is interesting because that's like applied IOT. This podcast is about edge computing and digital cities use, I think really about every piece of edge computing that there is just kind of all pulled together into a single operational sort of microcosm, which is
John: fascinating.
Absolutely. And what I can say about that is IOT really had the right principle, but what it didn't take into account was really how it could stitch together with the backend systems that are really running inside of the HQ or inside of the [00:04:00] data center, whether it be part of a government or part of a university or part of a specific enterprise from an industrial park or manufacturing or even large scale enterprises.
And when we couple together what's happening at the edge from an IOT perspective, as well as what's happening in the data center. They're able to really drive insights from the value they're gaining at the edge, and then that in turn delivers on the outcomes that leaders are providing there, whether it's constituents from a city perspective or whether it's shareholders from an enterprise perspective.
That's kind of a
Bill: cool sort of positioning of the hierarchy, right? IOT is really basically the end point, and that's not solving a customer problem in and of itself. It's just. The next data collection that gets closer to them and then edge computing is using that stuff to do something, but smart cities pulls all of those things together into, like I said, kind of that ecosystem of solutions, whether that's helping with trash pickup or just, you know, e government [00:05:00] or whatever interesting city scale solutions.
So. Going into the smart cities conversation, what makes a smart city a smart
John: city? That's a great question and it's one that we're asked to answer time and time again as we speak to mayors or ministers or actual CTOs of cities. And the interesting part about that is cities have really been dealing with a lot of different technology challenges.
As they come across a problem over the past 30, 40 years, they'll apply a solution that solves a particular problem. But that's really like putting a bandaid rather than trying to find the root cause and see how they can drive different results. And what we've got is this like about 30 years worth of technologies that have come together and maybe made.
Individual departments, let's say of a city, work better as what they're doing, but in the development, in the evolution of that, what they've got is IT departments per their own, you know, little [00:06:00] area, and they're driving outcomes of their leaders, but they're not really giving the aspects that bring that together as an application.
And what I mean by that is that from a city perspective, we need to really pull together different Things that are happening in some cases, for example, like weather conditions play a role on how wastewater treatment happens. If we understand when there's going to be a hurricane or a flood that would do that.
So when we look at what makes a smart city smart, there is technology out there. It's been out there for 20, 30 years building on itself. But at what point do we look and hit reset and start over to say, Hey, let's turn this from a smart city into digital transformation that allows the city to be agnostic and nimble enough to really start to make changes to individual vertical siloed pieces.
That in the end will come together to drive these outcomes. And that really happens from an individual site or plant level, all the way up to the department. And then from those departments, how those [00:07:00] departments interface with each other to drive city level or mayoral type of outcomes that again, in turn, lead to what these leaders that are elected are really trying to drive home.
Some of the promises that they make. It's always interesting
Bill: when you dig deeper into a problem, the connections that you don't necessarily think about before you're really talking about the problem. It's the most fun part of this podcast, right? So you were talking about being aware of the weather, because that can change it.
Your wastewater handling, your storm sewer capacity, things like that. And I was thinking that makes sense because, for instance, if there's a major event downtown, then you need to plan your trash pickup to be a little more aggressive in the public spaces, which means you're emptying the trash more, which means you have trash trucks on the street, which changes your traffic flow.
And so you have to time all of that stuff for if everyone's leaving at the same time and the trash trucks are leaving at the The time and they're moving slowly and they're periodically stopping. Everyone's going to go crazy. And [00:08:00] so, you know, planning your digital city so that all of these systems come together.
And when the event is done, everything's clear. So the people can leave quickly and peacefully and get home and not be frustrated by the experience. That's just such a nuanced approach. Little things that people wouldn't think of as connected, but they make the difference in was my experience great or was it okay?
John: Absolutely. You gave a lot of great examples of, again, how these systems play together, but the key in that is really ensuring that the data you need from, let's say, weather systems and transportation systems, as well as wastewater and or the solid waste collection and processing of that, how they come together so that that Timing of the different elements can ensure that the actual residents and constituents of a city can benefit and are not hampered by those.
It really takes a lot to get these cities going and what some of the challenges that we see the leaders that are facing and and [00:09:00] or obstacles is really where do I begin. A lot of CTOs and a lot of departmental leads that are running their IT departments get pitched to day by day. different solutions that meet a very specific problem that they're solving, but if they're not considering how they bring it together and where they're going, they end up solving a problem today that was a result from yesterday, but they're not getting to where they need to be to drive the future.
There is a path and part of that path really is understanding what these leaders have promised their constituency, what they've outlined in the strategic vision or plan. And then from that plan, how they go about executing that in a way that doesn't disrupt current and existing systems that we call, you know, per se brownfield with the intention to really drive some of the greenfield change, but demonstrate the success as we progressively move through this digital transformation of it could be as individual department or how those departments kind of interface and work together [00:10:00] collectively to start driving those higher level outcomes.
And I would imagine
Bill: that the problems that cities face and the challenges that they're trying to solve for are still pretty similar to what small, medium, large enterprises are trying to solve for, how they're trying to apply edge technology. So with that, what sorts of challenges, obstacles do you see that city leaders face when trying to become a digital city, when trying to digitize all their operations like that?
John: I'll speak a little bit in depth on kind of wastewater treatment, right. These are existing OT systems and the staff of the folks that are there are pretty, they've been doing the job for 20, 30 years. They've got equipment that's been replaced bit by bit over time, but they haven't modernized on a certain level, nor have they made comparative or co relative analytics between.
Performance at a plant level, right? So what's important first is to understand that that's a deficiency, but not try to [00:11:00] wrap their head around the entire restructuring or entire digital transformation. But maybe look at two plants as a starting point, modernize the gear so that they're not dealing with different types of equipment and different types of, you know, technology that doesn't necessarily.
Talk together and making sure that they kind of standardize, modernize, and then normalize how that data is collected so that they can do those co relative analytics to see where best practices are happening within each one of them and then apply that across to both of them. When that is demonstrated that it works, you can take and scale that.
Right. And that's a mechanism by which we can look at current challenges without retrofitting the entire system all at once, but demonstrate what they're going to gain out of transforming part of it. And then the funding and the investment that comes along to help continue that. We'll again, just propagate by demonstrated results.
And those results again, turn into efficiencies that are [00:12:00] given back to the constituency, cleaner water, more water that's available. And then when incidents happen, such as let's say, it could be a major storm and a lot of new water coming into the mix. How do they really handle that and mitigate that they're able to do this because they're able to manage efficiently their current processes and then offset those.
And so bit by bit. And stage by stage, it's important to really understand the end goal and really start building out what that looks like in a phased approach. Nothing happens all at once, but also they need to be able to jump into and start at a point with demonstrated results and make changes. If it doesn't work the first time through, they can make some minor adjustments because the right initiative was placed or positioned in the first place.
And then again, that leads into those results. So starting
Bill: small. In production, testing things and iterating, learning when you have that [00:13:00] down, then starting to, starting to deploy it out at scale while still learning and iterating. That's, I mean, working with systems like that, where you've got people that have been doing, you know, they have their equipment, they have their tools, they have their job, they've been doing it for so long.
And then all of a sudden, Oh, Hey, we're going to digitize everything. That's a big adjustment. As part of that. Kind of exploration and starting small. I know you've done some work with a live lab incubator. Can you talk a little bit about what that is and
John: what's being done there? Yeah, no, absolutely. This is a great question and it really was a great initiative.
So one of the projects I worked was really where we've got a county that operates with a number of municipalities within the county, but each different department and each different segment, whether it be Department of Environmental Protection, Department of Transportation, Public safety side of it, as well as some of the non emergency citizen services, they all have different goals and initiatives and different things they're trying to really prove [00:14:00] out.
And what we find time and time again is if you get into each of these individual departments, they're running POC after POC. Trying to put a bandaid on a solution that if they take a step back, there's a different path. And so what we've done is got in concert with the university, always bringing in academia as a, you know, a starting point or a basis for building what we call like a smart city AI living lab.
And that gives a lot of benefit to an environment that allows a horizontal platform to come in and look at point solutions as they would interoperate together, we open that up to faculties for whether it be a grant based, or it's just something that a university professor is assigned to class, hey, go figure out how to make pedestrians more safe.
We know we've got video analytics, but does that work by itself? Or should we put lighting involved and then add further information where that would. So having a living lab is really a live environment [00:15:00] to not just proof of concept something, but actually pilot something that if it works out correct and it drives the results that are expected by the city, they don't have to worry about standing up a small environment, testing a few things, and if it doesn't work, they got to start over.
They have a lab that can actually facilitate those types of functionality, and in some cases it could be air quality indexing as it relates to traffic congestion and traffic flow. In other cases, it could be flood management. So, like I said, it really depends on what cities are trying to do, but having That relationship with a university and also open up to some of the startups where entrepreneurs have a space where they can come in and test an individual siloed solution, but then demonstrate how that interoperates and works at that higher level platform.
So a city knows what it can expect. It really brings about those results and does it in a way that we're standing up virtual environments rather than. Coming in and dropping [00:16:00] in a few servers and setting up a few cameras and a few air quality sensors to drive this, all the infrastructure is already in place, then they can just look at those edge pieces that they're dropping in, and how those edge pieces will in turn start to pull in the results.
If they don't like what they see, they can make adjustments without really Tearing down that infrastructure, starting over or bringing in a new partner. And that's really what's made the Living Lab successful from the perspective of how it works. Now we've done this in, in one particular area and as word of mouth spreads on what's happened, we're getting a lot of.
I want to say questions, a lot of inquiries from other cities that are saying, hey, how can we repeat what you've done? Because we want to take advantage of this. I don't want my DEP running out and running pilots on their own. I want them to start testing in an environment that allows that to interoperate and drive city level results.
Bill: So, toward the start of that, I got an interesting, like, [00:17:00] push and pull of, of competing priorities. On the one hand, start small and prove it out in production. On the other hand, you were saying you don't want to solve just a point problem that's too narrow. You want to have something that's going to solve I guess really the root cause or multiple problems if you can.
So how do you decide, how does a city decide, how do, how do you help them decide what the actual problem that they should solve is?
John: Yeah. Yeah. No, it's a great question. Where I'll begin with here is like I said, so, so let's look at, let's say traffic flow and traffic congestion. Now the solution there would be delivered to whether it's a department of transportation or some other groups that are offering, operating within a municipality.
What's What's important there is that they'll have video analytics, they set cameras up and they're really observing the flow patterns, type of vehicles that are on the road, number of vehicles that are on the road at certain hours, and what makes best sense. What they are not doing is those systems seemed, [00:18:00] in a lot of cases, they may be proprietary or closed off.
We ensure that the folks that we partner with actually have solutions that are open. to open their APIs up so that they can transfer the data that they're collecting into a integrated operations platform. And this is that horizontal piece that I mentioned, where we can plug in open and public systems like national weather data to those same systems.
And the fact that we've got metrics that are on the traffic flow and type, now within this integrated operations platform, we can take and say, Hey, these, this number of vehicle in regular sunny conditions with nothing. Nefarious about the weather side of it equals that we're going to have smooth traffic, even though sometimes it may be congested.
But however, if I layer into that what's happening on the weather side, and I know that it's coming, I can now determine that there may be some adjustments to be made by correlating those systems. So the key there is to know that not individual siloed platform can solve all the [00:19:00] problems, but they may be the best at what they do from a video analytics perspective.
They're not. going to be able to solve all the problems. And a lot of companies, a lot of partners that we work with really are great at certain technologies, and they become even more powerful if they kind of open up and don't lock their system into a specific platform. Whether that be only one cloud, you know, we want to work with multi cloud.
Some sensors may operate on cloud provider A and others may operate on cloud provider B. We still want to be able to take the metadata that comes in, run correlative analytics and not Bind a city, and the same goes for enterprises. Not bind them to one particular platform over another. This keeps the city in a capacity to be nimble and also make choices as new technologies evolve and develop where they're open and they're not really locked in.
And so having that available to cities allows them to continue. To really provide the best services they can to their constituency, while [00:20:00] also normalizing data that, you know, for all intents and purposes in the siloed piece, maybe, you know, a setup to really operate by itself. Now those independent solutions, it's essential that they do operate by themselves, but it's also essential that they play nice in the sandbox with everybody else.
And as a result, as you're managing these types of bigger environments, you're able to make sure that the data that's needed to drive the results that lead to. better livability, improved citizen services, and really driving results that a lot of our leaders promise as part of their platforms are able to be realized and achieved.
So
Bill: going back a little bit, you had mentioned brownfield situations, Greenfield versus brownfield. So for any who's not familiar with a greenfield being a clean build, right? A new city that hasn't been there, or a neighborhood that they're building from scratch as a kind of a mini smart city as a proof of concept or something like that.
And a brownfield being [00:21:00] existing systems, existing processes in place, trying to add to modernize, retrofit, whatever. There are at least a few greenfield smart cities. In planning, underway, in some form of development where different groups are building a smart city from scratch, which is pretty amazing.
That's a huge task. And then most of the opportunities, of course, are brownfield, right? New York City wants to have better trash collection, or a better sewage system, or something like that. Solving a problem, starting to modernize piece by piece. Kind of a personal question. Do you prefer working on Greenfield versus Brownfield?
Which one's more fun and interesting, right? Is it like the potential of Greenfield is so amazing or the challenges and intricacies of Brownfield are so amazing? Or am I just asking you which one of your kids you like best
John: and you can't answer that? No, no, it's a, it's actually a great question, but it's an interesting question.
The good news is, is that property development [00:22:00] occurs. Across the matrix. It doesn't matter whether it's a brand new city built in the middle of the desert, or it's something where there's an area that has really been run down in a city and city master planners have decided to really make a change and really go in and you know, whether it's demolish or rebuild certain areas from where their existing crumbling infrastructure is into something that would be more modern and more suitable for what the society expects, obviously with the property development phase.
So in a lot of ways, every city, even if 90 percent of it's brownfield, there'll still be that 5 10 percent that has that greenfield opportunity. If we're trying to, you know, talk about a city from scratch, it's a huge investment. And those are very rare and really require a national level of type of investment to make that happen.
So we don't run across those too often, but they're fun to work with. Now, the challenge is, is that everybody That you can consider that's out there on the [00:23:00] hardware side, as well as on the software and solutioning side really jumps in and tries to say, we can do all these things for you, or it's something brand new from scratch.
It's important to talk about it from a physical and civil engineering perspective. Initially, and so we understand the groundworks of what's being laid. And then from there, really, how do they build that up to drive the results they expect? So I would say they're both fun. I would say that the task with a brownfield that's a little bit more challenging is you've got a lot of existing.
Workers and workforce and that workforce sometimes is set in their ways and it's important to show that some of these changes will actually allow them to do their jobs easier and make it more efficient and they can drive more of the services that those particular departments, whether it be solid waste management, whether it be wastewater treatment, whether it be again community services and how let's say homeless shelters are run and different services that are provided to those within a city.
It really has to address all of that. All of the [00:24:00] needs of what the city is and really tie that back into what a city leader's strategic plan is or strategic vision. They all have them, but how do we help deliver that on them? And again, when we get into planning for this, when it's brand new, it's pretty easy.
We can come out with the latest and greatest technologies, but it's important to look at those systems and ensure that there's no lock in, that they're really driven towards the best of breed and technology, and that those are open and able to work. With as they change to maybe switching from technology, you know, vendor A to technology vendor AA, because something new has advanced like generative AI, or how is AI happening at the edge?
So I find both of them fun and I love both of my children. If that's a, an easy way to answer that equally. Yep.
Bill: And in there, you were talking about civil engineering, which probably that, that makes me realize this is probably why I'm so drawn to digital cities. My first degree was civil engineering, so I would have been part of the Brownfield [00:25:00] development of this whole conversation.
Which is sort of
John: funny. I can add one more point to that. And the key is, is we bring in this integrated operations platform or unified operations. What we're doing is tying siloed systems together. If we derive enough data from that over a certain period of time, at least a year. So we've got seasonal changes.
Work weeks planned and weekends and then other events like in Singapore here, we've got the F1 that comes every September. So we know that's going to be an international event and it's going to really affect how the city operates. So understanding that 12 month cycle at a minimum within the city. And having that data that's rolling forward allows them to create a data, I call it data oasis because it's a compilation of a lot of data lakes coming together that will in turn drive a digital twin that allows the civil engineers to actually engage in master planning of the city and they can look at current statistics [00:26:00] like what happens if population increases or decreases and then if so I'm planning this development and I need to lay ground on that.
Groundwork by, you know, trenching fiber or laying additional sewage lines and additional roads. Sizes may be large enough or not large enough. Are there enough medical facilities and schools in the area and housing, things like that, things that really are imperative to properly. Plan for a city and where it grows and how it adapts and evolves over time, having that unified system that provides that repository or data oasis, then in turn drives a digital twin where the mayor can show what's happening today in real time.
And data scientists can run on a parallel instance of that and start to play with it. What happens if the sea level increases, right? And starts flooding areas that we didn't anticipate because of global warming or some other potential. Having that twin and having that basis of data that comes together really leads into the next phase of how the cities plan and the future of how [00:27:00] they're embracing artificial intelligence to help them drive those results and really see.
What changes could be or what happens if they make investments in certain areas? It kind of brings
Bill: up one of those, I guess, kind of downstream goals, larger goals that you would want to get to with digital cities, which is to build that digital twin. If you can have a full, you know, if you have enough of your city instrumented and you know what's there and what the capacities are and such, you can build.
a virtual simulated version to start to run what if scenarios. And you know, like what if we decided to host the Olympics or the Super Bowl in the Americas, or if F1 came and it was bigger and the city of Barcelona hosts Mobile World Congress, which is like 40, 000 people that come in for a week
John: and
Bill: then leave.
You know, it changes everything about how the city How do you plan for one burst that is so big? [00:28:00] Digital city would really help with that as opposed to just a paper and pen sort of exercise.
John: You're spot on. I mean, this is exactly the challenges that cities are facing. And one of the other key elements or critical elements there is really.
They don't know where to start a lot of times and really what's key is getting that alignment to what a city leader is kind of trying to accomplish. And that usually falls down to like, whether it be the office of technology and innovation from their CTO leads that to actually how individual departments are running, but if you're aligned to their strategic vision and you can demonstrate results, the funding for that scaling piece becomes.
a lot easier because you've demonstrated what those results are. And in some cases, ROI is one of the things mentioned. When we look at a return on investment, when cities make these kind of goals out there, it's not always monetary. Sometimes it's in citizen livability or improvement quality of life, improvement of medical [00:29:00] services or services that are meant to go out.
To really solve other problems that are happening, reducing crime, improving safety in areas or improving traffic parking conditions so that more people can get in and out of the city more conveniently and be able to do some of the things that foster revenue that comes into the city, right? If the.
Popular restaurant you want to go to has no place to park around it. It becomes a bit of a challenge if you're trying to drive and stimulate these kinds of things. So really the success factors that we look at change, but if you have that alignment with the city leaders and what their strategic vision is, I think that I find success in that, and then that success bleeds into further projects, further investment, because leaders are really accomplishing some of the things they promised their constituents.
Bill: And so that takes us into kind of a different piece of a different, interesting conversation. ROI, if you don't invest very much, Then your return on that [00:30:00] investment is fantastic as long as you have basic successes, right? If you invest a whole lot, then you have to have some massive runaway success to show a good ROI, like a high ROI.
So, The reality is somewhere else in there, you invest and you show success based on some sort of metrics. How does that work for smart city initiatives? Where does the funding come from? Who pays for these
John: things? I mean Yeah, a lot of times it's government funding, and you'll find that, interestingly enough, like in the U.
S., you've got the IIJA funding, right? It's infrastructure related. They're really Invested a lot of money so cities can modernize. What the key to success, especially when ROI is being looked at, is really there is a dollar value investment, but there shouldn't be an immediate expectation of a return, they really need to look at a three to five year model.
When they look at the 12 month model, I made an investment, I've delivered, but I don't see what I'm expecting, is when they really run into trouble. And I think [00:31:00] the key there is to look at what they're expecting to arrive at as a result and by when. And again, it's not always monetary, but it's important to do that.
So I'll give you, I'll go back to the example. If I'm modernizing a wastewater treatment facility, The importance there is that there's going to be a big expense up front, but if that reduces the maintenance costs over that 3 5 year period, that I would expect that there's X number of dollars year 2, year 3, year 4, but now have been reduced by 40%, then I can see there's an actual Resolution, there's an actual return on that investment that really justifies what the project is.
Now further, we can take advantage if those systems are built in a way that is, as I mentioned, opened and kind of bringing together systems that didn't interoperate together. We can take advantage of other things that weren't looked at before. And this gets into a little bit on sustainability. So, and, and again, this is related to wastewater treatment.
Sludge is generated. Sludge can be offset. Contained and that'll generate [00:32:00] methane gas. Methane gas in turn can power a generator on site and that generator then will reduce the demand of the wastewater treatment from the grid. So they're becoming more sustainable, more carbon friendly and reducing the demand.
on other additional city resources that we know increase year over year. More devices come out. People are operating multiple computers at home, TVs, tablets, phones, all these things are happening inside of a home. And if I can take government services and say, Hey, I've reduced 20 percent of my demand on the grid so I can continue to operate, deliver the water cleanly, but at the same time, take advantage of some of the things I'm generating, I can turn that into usable.
Insights. And again, methane gas powers the generator. There's also a result of, you know, materials that are biodegradable that can then turn into fertilizer, right? Obviously, there's more processes here, and I don't want to dive into all the intricacies of how that occurs, [00:33:00] but you can take advantage of all the waste generated and convert that into some energy and convert that into other usable materials.
And again, By doing these things, we start to enable and embrace this kind of a feeling of what circular economy would look like if it was done on a large scale. But again, cities, in order to make those investments, need to be able to realize that on a small scale before they're willing to fund and start to grow.
And that's the, I would just say, that's one of the most exciting things about the role I'm in and really designing and working with cities on delivering these types of initiatives. There's just so
Bill: much to think about and talk about with smart cities, because. It's, it's that whole ecosystem of life, which is fascinating.
So going back to something I was touching on the edges of before, smart cities is a huge swath of use cases, right? Computer vision for safety and security, but we can also use it in manufacturing for defect detection, footfall analysis to [00:34:00] watch traffic flow and see how long it takes people to get from place to place and how safe they are and estimate populations and things like that.
can be used in retail to estimate how to lay out your store more efficiently, things like that. So we've got all of these things that are useful in private industry that we're putting into public spaces or useful in public spaces that we're also putting in private spaces. How often do you see public private partnerships where businesses gain benefits from being in a more intelligent space and having access to larger data sets and such?
Is that? A consideration in smart cities or is it really public funding, government driven?
John: Well, if we talk about department by department, right, those are typically going to be isolated to government funding. When we get into things like the smart city AI living lab, that's exactly what comes together is a public private Partnership, so that these [00:35:00] solutions can be tested, can be seen that they interoperate together.
And then even the small startup that's developing some new great technology that can be applied, let's say to shopping malls, right? They're able to test and leverage that and then see how does, you know, I'm tracking footfall and I'm tracking wait time and duration time within the stores from a retail perspective, but what does that mean to the shopping mall?
Right. And in turn, if I look at the shopping mall, then we're talking about larger entities that own a lot of shopping malls or own other types of buildings and development, whether they be apartment complexes or the university complexes. So the PPP is an essential role and has different areas where it can really be applied to drive the value that you're speaking of.
It doesn't fit every government initiative or every government department. But in cases where both the city side and the private sector come together, we're finding a lot of value in driving what does that mean? How can they come together? [00:36:00] Because these integrated operation platform, if I looked at it from a building perspective in Singapore here, we've got.
A lot of buildings that have a shopping mall, but there's a connected parking structure. And then above that's going to be commercial space. And then potentially above that, maybe a hotel or residential apartments, right? So they've got a lot of different users and different businesses that are set up within a single building.
And then those developers operate like 50 of these buildings throughout the city. So really bringing that together, they can take advantage of things that drive. in the public interest, but at the same time also have that private interaction. And so we do find areas where a PPP or a public private partnership comes together so that we can drive better results, whether it be kind of like the example I mentioned, or whether it be on the AI Living Lab.
Where they can come and bring about those together scenarios. We could find that there's different [00:37:00] technologies. Now we talk about computer vision and computer vision is great. So when we look at that, but they typically are isolated to very specific things that they're doing. And where we gain better value out of that is again, what happens if I'm looking at foot traffic and I'm also looking at lost theft.
Right? I need to tie into other systems to bring about those results, right? If I'm looking at vehicle counting and traffic congestions for like urban mobility, right? And then I want to tie in weather systems. This is where computer vision is great at what they do, and they are the experts. There's a huge number of partners out there globally that really drive the successes there, but It's how do they play in the sandbox with all the other players that are out there that will drive an improvement and further evolution of where technology is driving towards, as well as how artificial intelligence is used to really take data sets from both sides and run different [00:38:00] types of analytics to deliver results.
And, you know, I keep mentioning the outcomes are key. If you can't deliver an outcome that really drives the value of what's been promised or expected by the consumer. So, for example, the Department of Transportation would be the consumer of computer vision. Well, they want to drive improved traffic flow, but they may also be looking at, the mayor may come back and say, well, I'm glad you're improving traffic flow, but what have you done for greenhouse gas emissions?
How have you improved emergency response times? And it's like, hey, we can put air quality weather stations. add locations, capture data in both sets, and then show you that we're having these results that improve livability, improve the way that we operate our traffic signaling, and as well as making people happy by spending, you know, 8 percent less time on the road going from work to home or the other errands that they run on the way.
Bill: So, you said AI in there, I gotta go there. As we're looking forward, how is [00:39:00] AI going to impact our cities in the future and does generative AI have a place in there? Is that going to change how our cities operate?
John: Yeah, I believe it will improve how cities operate because how many of us have called the non emergency call line and says, Hey, you're been placed on hold because our volumes are too high, right?
We see chatbots from time to time jumping in. They're trying to solve problems, but they don't know exactly how to do that. This is where generative AI has a real value, but it goes beyond a non emergency call line. If you can imagine. Like going into municipal centers, right? It could be areas where there's a basketball or there's national parks and people congregate together, having informative maps of the city and different things to do and having generative AI respond to those will mean that the citizens or the communities get results, get information more readily available that's based on actual data that's being generated.
And so what we'll see is [00:40:00] with the current levels of manpower, we don't need to Continuously expand those just because the demand expands. But generative AI and AI as a larger set will help to drive improvements in efficiencies that again, if you give it back to the cities, you're able to really improve the feeling of what they're getting.
If they know the government's investing a bunch of money or a lot of funding in certain areas, if they can see the results, mayors are happy. The constituents are happy with who their leaders are, and again, that gets into re election cycles and delivering on promises that again, in turn, funds further expansion of these areas.
A lot of people, when they talk about AI, they say, oh, we're losing our jobs, or we're going to, you know, we're not going to have the ability to do that.
Bill: Yeah, that kind of happens with every technology update.
John: Yeah, what we're seeing with artificial intelligence and generative AI with that in mind is that we're able to allow the same level of workers to [00:41:00] perform at a greater capacity, delivering more in content, delivering more in the way that cities respond to the needs.
And that really covers departments, whether it be emergency response, fire, police. Community services, it could be maintenance on potholes in the road or where there's extra rubbish or garbage on the roadside that people need to collect. Somebody taking a picture of that and uploading it to a city application, that in turn, AI can look at that and say, ah, here's the geo positioning of it.
And I can automatically generate a service desk request that sends a truck out to go pick up the rubbish or sends a maintenance crew out to fix a hole in the road, rather than we're not getting rid of a job, but we're providing an efficient. It doesn't require somebody to send an email or to log a ticket when we can automate those facilities.
Bill: So again, looking forward, what city is top of mind for you that's doing this right, that's [00:42:00] on the right
John: path? That's a great question. And the good news is, is that there's cities all over the world that are really competing for that top spot. Who's the smartest city in the world, right? And we see a lot coming out of Dubai.
We see things in Singapore. We see things in Barcelona. And we've got, obviously on the U. S. side, New York wants to be there. They want to be one of the best and smartest cities in the world, obviously Washington, D. C., and a few other large cities. The good news is, is that competition Really evolves technologies to really deliver these systems.
Now I'll speak to in particular, something I really like about the way Singapore does it. They've got an application that we call Sync Pass. And that application allows me to access through authentication and dual factor authentication. Once I'm in, I can see all of the information on my retirement fund, all the information on the tax that I'm doing, all of my health related data that the city collects, and further other services that they provide.
Now it's through a single portal. And obviously [00:43:00] security is imperative here, but the fact that they were able to deliver this level of government type of services and expectations through a single unified application drives home the ability for citizens to really Understand what the government is doing with their tax dollars.
Understand things that are private and know that things that are public in there, and not to mention some of the other portals that really say, Hey, if you've got a community concern, tap on this particular app. So it doesn't mean that we've integrated everything into a single app. It means a single app was used.
To securely connect to all the other government systems. And again, as that evolves over time, we will start to see monolithic applications that are web-based, turn into microservices architected, which means that the city or those particular departments can start to enable that modern functionality by going to these like microservice architecture, so they can add features and functionality, fix bugs [00:44:00] easier within their individual apps.
But at the same time, they're not compromising any of the citizen security. It's an evolution. Now we're at a great point, but then how do we get further ahead and how do we continue to evolve? Dubai has got a lot of great things happening there as well. From the UAE side of it, they're looking at systems that monitor the way that oil is offset from all of the restaurants, right?
What do we do with the cooking oil? If the cooking oil overflows, it goes into the sewage, which means that there's a greater burden. on wastewater treatment. If they're monitoring it, they can actually pick it up and reuse it or recycle it in a way that's more meaningful and always avoid the situation where an overflow results in catastrophe.
We'll continue to see this monitor and change in different sections of a city. And the great thing about smart cities. It's too big for anybody to go in, any one nation or any one city to really go in and have the greatest city that only evolves. [00:45:00] There's a lot of different levers and a lot of different departments, and each one will be advancing in one area.
And then over the next years, the other cities want to learn. Singapore sends its folks over to Dubai. What are you doing here? Dubai sends its folks over here. What are you guys doing there? And you start to see that competitive nature of, you know, I don't know if it's capitalism or what the right word for it is, but as this competition.
You see nations and or cities strive to really improve the livability and lives of their communities. Competitive but
Bill: collaborative and making everything better at the same time. That's very cool. So, John, probably time for us to wrap this up. Otherwise, we're going to be here all day and having lots of fun and learning lots of things.
But how can people find you online and learn more about your work and keep in touch with you moving forward?
John: Absolutely. So obviously you can find us on Dell Technologies under Digital Cities and under the Edge Business Unit. And you can also find me on LinkedIn, John [00:46:00] Lockhart. What I can say is that there's a white paper that's being AI And generative AI, as it's going to be used in some of the areas that can be looked at as we approach cities and them taking on this technology, it again will never be just a swap and replacement of people and their jobs, but it's going to be something that enhances the way that cities.
go about delivering services to their communities. And Bill, I wanted to thank you for the time and opportunity to really communicate some of the great things that Dell is doing to really bring about these changes in this digital transformations as cities approach the midstream of the 21st century moving on into the 22nd century.
I can't
Bill: wait to see what comes next. And thanks so much for the perspective and for answering all the wacky questions.
John: Absolutely. My pleasure. That does it for this episode of Over the Edge. If you're enjoying the show, please leave a rating and a review and tell a friend. Over the Edge is made possible through the generous sponsorship of our [00:47:00] partners at Dell Technologies.
Simplify your edge so you can generate more value. Learn more by visiting dell. com slash edge.