IoT for Smart Cities - Parking, Infrastructure, and More (Cloud Next '18)
Welcome. Thanks. Everyone for coming this afternoon my name's Fraser McDonald I am a product guy on an IOT cloud at Google and I'm, John hood I'm CTO at smart parking a company that's using IOT core. So. Thank you all for joining us we, want to ask you a question just to get things rolling here just to get a bit of a sense of who's, joining us this afternoon for the next 45 50 minutes so just by some hands how, many in the crowd today are working directly for a municipality. Okay. So, we got some hands from people that are working with cities themselves how about people that are working for vendors. That serve municipalities. Okay. So, a good number there as well. How. About people who have lived in a city Oh. What. Do you know all right so we've got some subject matter experts, here that's great and I. Say that kind of a half kiddingly, but, one of the one, of the points that John and I want to talk about today is a bit of an idea of who. Are we building these smart cities for what. Is the the reason for making him not just how you make him so, I think everyone in the audience has got a bit of a voice in that so. Thanks for joining us. So. Let's warm up with a. Bit, of a teaser. Take. A look at this kind of echocardiogram. Looking thing off to the side here and, see. If you might recognize, some patterns, in it does anyone have any ideas of what we might be looking at. Yeah. You, have some urban areas some parking they're, definitely urban areas you're right in fact if we show the names here we're, looking at some familiar areas you got the bay area off to the side New York London, Tokyo San, Francisco, so. What we're looking at here is movements. Of people on their mobile devices every. One of these dots is somebody. That has opted. In in Google, Maps on their phone for location. Tracking so you've taken that data anonymized. It collected. It and you're, looking at the living breathing city here this is a 24 hour cycle of where people are going what they're up to and this. Is enormous, ly valuable, data it gives us a bit of a sense of context, for what we're talking about today that there's an incredible, amount of information it's available to us if we can make use of it so this, is for people's. Personal uses on their phones and maps and seeing where they been but, imagine, how useful data like this could be to people who are planning traffic, patterns people who are trying to plan pickup, routes for waste management somebody. Who's trying to get a new freeway going somebody who's trying to choose where, the next neighbourhood the businesses, should grow in we're. Seeing a growth in mobile devices we're, seeing a growth in IOT devices and, we're seeing a simultaneous, growth in the ability to process this data on a massive scale so. This is just the beginning of smart cities we're getting into a really exciting age for it. So. Question. You. Might have expected coming to a tech conference coming to a Google conference that we're gonna talk purely about technology, and is, this. What, smart cities mean the technologies, so. Yes. And oh yes, in that these are definitely ingredients, of a smart city I mean having access to Wi-Fi is what gives us the ability to collect data having. RFID transit passes are fantastic, resources for municipal, planners to know when, and where are people going so we can make smarter routes having. Self-driving, cars are gonna be an enormous, overhaul. Of what it means to live and be transported, inside of our cities but, these are ingredients I mean in the same way that any ingredients. Alone don't make a cake this isn't, the smart city itself what, John and I want to talk about today is a, bit, of a shift and we're, wondering if you join us in this shift from thinking about a couple of the nouns a couple of technologies, of smart cities to, a few adjectives, that might describe them so. Over, the next little. Bit we're gonna do a few things one. Is I'm, gonna share a few stories of what we've learned at Google from some projects, that we've been involved in that overlap, with the smart city space so, a bit of stories. That we've had some learning from and a bit of what. Ifs and then. We're gonna hear from John and John's gonna tell us well if that's the what if this, is what it actually looks like John, and his company are building, the kind of infrastructures, for cities around the world right, now that, let them make good use of their data and we're.
Gonna Wrap up with a Q&A so, before we dive into some of these stories that we've learned from I. Should. Call out that this session is one in which we have Dory so you might have been in a session this morning that has Dory as well it's, a Q&A tool that we've got at Google. And we're rolling it out and trying it at this conference so if you go into the mobile app that you have for this conference and you go to our session you, might notice that there's a QA portion, in it where, throughout the car. To see, something that looks interesting or a question crosses your mind in the moment you can write a Q&A question, and the. Rest of your fellow audience members can then vote it up and at. The end of the session we'll mix a bit of microphone, questions, and Dory, questions, from our moderator who will read that I would so, if a question crosses your mind feel free to hop onto your app and ask it as we go, okay. So let's take a look at some stories of what we've learned at Google from some smart, city adjacent, and overlapping, projects. What's. The first adjective that comes to mind the, first adjective, of smart cities that at least John and I when we were sat down and to sitting, down a chat about this thought I was efficient and, I think there's a reason for that is because it comes up the most regularly, for smart cities take, a look at this this is the list of the, most common. Smart. City projects that are underway right now in the world and, if, you're taking a look at it you'll probably notice a bit of a pattern to it as well you've got parking street, lighting wasting, energy management and then a whole bunch of transportation. Logistics and, optimization. These, are efficiency, problems, and one. Part of it might be yeah these are the low-hanging fruit these, are areas where an, IOT, sensor or actuator can really help and not be too complex, of a rollout but. Another big reason for this is these are areas of high ROI each. One of these is making the city better able. To spend its money or better, able to allocate its resources and, a. Really, important adjective of a smart city is one that is not wasteful. With its resources, so. What does an efficient smart city look like in the project that we've worked, on some. Of you might remember this demo from, next 2017, this is a bit of a what-if this is something that we showed which is taxi cabs driving around a city so we've got some simulated fleets of taxis across New York and these, taxis are kitted out with something that's a little different and instead, of having just a display ad in the back that's showing you a clip, or an, ad for something they're, also location, aware they know where, they're picking up where they're headed what time of day it is and with just a little bit of that information we.
Were Able to personalize, the ads to, whoever might be riding in the car with an incredible amount of accuracy it's. A tiny bit of additional data but, it produces a huge oak, so. This is an example for ads but, imagine, this, kind of intelligence, if it were applied to real-time. Traffic. Control, if your city or your building, a tool Forest City was, able to equip, the city's traffic control measures to. Respond to floats, and parades to respond, to an event that spontaneously, happens, to respond to live traffic conditions, or, imagine if this kind of real-time data and a little bit of location, in time awareness, was able to affect. Waste. Collection, so. That's exactly this next example this is a company called an AVO and their Google customer, and, they're building something pretty cool which is a waste management solution. And instead. Of being the traditional take on waste management which, is usually sort of schedule oriented, and you know you know, your time when you're gonna get a pickup the truck comes by they, pick up your bin whether it's full or not and they, drive off I never, decided that they were going to add some sensors, in a bit of an intelligence, to the process so they're, parking, or rather they're a waste, management solution, is aware of how. Much trash is in the bin they, sell this to companies, that need a more efficient pickup schedule and all, they did was put a couple sensors in to know when. Trash is getting full and slapped a GPS on their trucks and out. Of a small change like that their customers, got better service, because they had reliable pickup, and didn't have to think about scheduling. So much is starting to think about waste management as, a service, and they. Themselves got better optimization out of the route because they could tell the drivers exactly where to go and where they were needed. So. What's another adjective that might give us a bit of a. Place, to start for smart cities. Participatory. So. What would that mean there. Are a couple of perspectives you could take on this and one of them is, participation. Of the people that live in the cities themselves so. Here's another project that we had some overlap with at Google. Some. Of you in the audience might recognize where in the world we are flying, over right now this is Japan and specifically. This is an image that was captured back in 2011 when. In, the Fukushima area of Japan there were three nuclear, reactors, that melted down and it, was a major public. Safety concern and there. Was a pretty incredible response. In 2011, what we're looking at here is a couple people in Japan that were citizens put, together Geiger, counter kits they, were, makers, and tinkerers and shipped, them out to people other citizens, around the country who, got. Him built him connected, him up to the web on a platform, called patch Bay at the time and overlaid. It on top of Google's maps and. What you're seeing here is people, getting involved in producing, and, engaging with the data of their own cities to make them smarter, this was real-time. Intelligence. On, should. I be in my area am i safe now. This is an interesting impersonal, one for me because this platform patch Bay went on to become the SciVal, a IOT enterprise, platform that Google just bought earlier this year and is, getting rolled in as part of the, IOT core cloud offering.
The. Next one here is sidewalk labs you might have heard of this one as a sister, company of Google underneath alphabet, and sidewalk. Has a mandate, to not. Think about the city of next year or three years from now they're thinking about this what might cities look like 20 or 40 years from now so, this is another project we're involved with it gives a bit of an idea of where why might, we be headed and sidewalks. Taken on a really ambitious project, it's, another one that's a little bit personal to me as as a Toronto, by myself, growing, up not too, far from that watercolor, toothpick. On the left there, this. Is a, micro. City that sidewalks, taking on in Toronto they're gonna wire up absolutely everything from, the municipal infrastructure to. The transportation. To, waste management, to lighting, and they're. Gonna try to figure out what. Can we do with the data so this story is just beginning the, sidewalk story is just starting but, what would it look like if we wanted to try to affect some of these changes and play with some of these ideas right. Now we've, done some of these projects, as Google what are some of the tools as GCP, that. We're rolling out so that we can help companies. And municipalities, try, some of these ideas themselves so. How might I tackle, efficiency in participatory. City let's, take a look at Google Cloud IOT, for a minute. So. Like much of GCP we're, building on the exact same tools and stack that we build on for our own products when you're looking, at the. Google Maps infrastructure, you're. Looking at the same company that's producing GCP, tools for your company to use and we took the same approach with IOT, this. Is an example of what an, infrastructure. Might look like for powering a smart city project, using, a couple of GCP building blocks so, when I left we've got our devices whatever they might be whether. Those are occupancy. Sensors, they're smart energy meters they, are watching. Out for traffic patterns, these. Are the devices on the left that have something to say or that, might be controlled, like a stoplight and the. Tool, that we put together in the middle here is cloud, IOT, core so. This is a recent product we've started rolling out specifically, for this use case there are a lot of GCP ingestion, tools, for huge amounts of data like, pub/sub, but. The unique thing about cloud, IOT core is that it's also meant for talking back and it specifically meant for devices, so, this is something that can run with any hardware, that your city is bringing along any sensor or actuator over. A number of different protocols, mqtt, is a lightweight protocol. For devices that are a bit more resource constrained, HTTP. For something that has a bit more compute, power and overhead and doesn't, need quite that but, this is a way for you to give your devices a unique identity, and be. Able to talk back and forth with them and tie. Them in to the rest of the GCP ecosystem, so you can start making use of their data and we're gonna talk a bit more about the, rest of this picture of what is making use of their data look like just. In a minute. What. We're looking at here is a bit of add, these blocks together and we can start playing with the ideas that we were looking at in a couple slides earlier all. Right let's take a look at a couple more adjectives, responsive, so. Responsive. Seems self-evident. You would want a smart city to be one that can correct, if something's going wrong is something that's aware of what's happening in its, own grounds, and something. That feels, like it's, not. Just all operating on autopilot. What's. An example of something. Responsive. Well. Here's an example of something that we've learned a bit from at Google and this is a parking feature that we've rolled out which. Is based entirely on machine, learning this isn't the same level of granularity as. What John's about to talk to us about in a minute this is just high-level, this is just a bit of information on where people are sometimes and. Tried to make some estimations, on traffic patterns and parking, patterns based on that so if I'm planning a trip to the mall or I'm going to a city I've never been to I can, get a bit of an idea of it looks like I should go at 10 a.m., instead of 4:00 p.m. and, this. Is an example of something that doesn't just show you where the parking lots are it's, responsive, to when, you might want to be there.
What's. Another adjective self-aware. So. This is one that, I find, really, interesting and, really important, in the smart city space and. It's. Quarter, rolling out any new programs as a municipality, or its core to being a vendor to the cities because you can't make good decisions, unless you know what's going on in your own grounds. What. A self-aware, look like for a city well, a lot of you I bet have used Street, View before I was just doing a trip last weekend and had, never been south on Highway one before and was using Street View to check out a couple of towns and where's a nice spot for a hotel so. That's. An example of how I can get a bit of an awareness as a consumer. But one, thing that we learned at Google from Street View was the incredible, richness of image, data and. This. Picture that we're looking at was useful to me is somebody taking a ride but how could it be useful to a city. You. Might also be familiar with google lens as a consumer, something else that makes a bit of intelligence from images this, is an example of I take a picture of a flower or I can have that flower identified, for me it was something that rolled out at a recent IO and is, chasing that exact same problem, of well. We've got a lot of image data in cities these days is there anything we can do with that so, this is a consumer, example, what might that look like in a smart city context, how. Can I take these adjectives, responsive, and self-aware and look, at some Google tools that would let me chase that that would let me learn from that so. I'm pretty excited to be able to chat about this one today as it's a relatively, new idea that some of our teams have been playing around with and it's, a combination between some, of our learnings from Street View and our. Machine learning and image processing tools and, the. GCP. Tools that are offered publicly, so none of this is you, have to ask for special permission this is all GCP tool capabilities. But. It's an idea that we are looking actively. For early partners on so if it looks like something that's interesting to you reach. Out to me after the talk. Geno, lens is the consumer product it, will take, an image and tell you a rough idea of what's in the image what you might also know is that inside GCP, there, are a couple image processing tools that go deeper than that the. Vision API is effectively. That for, your apps if you're building something that, has a photo capability, you. Can send the image to the cloud vision API and, it will return with, a level of confidence what, it thinks is in that image and, that's great for a lot of you use cases if you want to be able to tell yeah, this is a car or this is a park or this is a tree it's. An incredibly powerful thing to build in with absolute. Simplicity to an app but. What if I wanted to go one level deeper what if a city really wanted, to get to know what's, going on on its grounds without, having to kit out an enormous sensor network let's. Go one level deeper to the next product called Auto ml, and this, is where you can start training your own image, recognition models, so. This starts to get really, powerful as cities, start, wanting to ask questions, about what's going on on our grounds now. Our own Street View imagery isn't, publicly available and isn't available to process for a number, of privacy reasons but, images, that a city is taking itself are well. Within their right to process. So, what. Might it look like to take a look for are, there trees close to powerlines that might be a risk right now are, there potholes, in the road that we might need, to be keeping track of these. Two products are built for exactly that cloud, vision API gives, you a good idea of what's, in a picture and is dead simple they integrate to your applications, you, pass it an image it passes back what it thinks is in that image if, you want to go one level deeper and you're, working on an application for a city that says we'd. Love to help you answer a very specific problem, then. Cloud auto ml will, let you very. Simply, with and without. A data scientist on your team create. New models that will allow you to identify what you're looking for so, imagine what this could do for cities if you. Could get. A better idea of real estate value out of images if you, could take a look at where, are we at risk for, a tree falling on a line where. Are we looking promising, for new areas of growth based on businesses. And buildings that are booming in that area, an. Idea, of could, we look for indicators of energy. Surge of production, could, we look for measures. Quantitatively. Of development, of poverty of living conditions in our cities these. Are tools that are on GCP today. So. We've, talked to Cup a bit about a couple of the projects that were working on at Google and, we've talked a bit about what we learned from them and what are some of the GCP tools that might help you ask those same questions in your cities let's.
Go One level deeper, imagine. If you were never stuck looking for parking and to answer that question please. Join me in welcoming Upjohn. Thanks. Fraser, yeah. We're living. In a changing, world aren't, we and, parking. Is one of the things that we live with which really sucks and so. I, just. Want to tell you a little bit about who. We are and what we've been doing for now. 15. Years, we've, had to build a lot of Technology ourselves because there are no standards, but, we're doing it in the real world every, day today, so. We're. Based out, of several. Locations, around the world Australia New Zealand and the, UK, we. Actually dog food our own technology in the UK and we run the hundreds, and hundreds of car parks. Across. The UK with our own technology but, in New Zealand in Australia, and other, parts of the world we have a number of very. Significant. Smart. Parking systems, in place. Tens. Of thousands, of sensors we build sensors, that go, in the ground just. Like that yes, just, want an example of one it's. Not much bigger than a, D size battery, and it, has to last for up to 10 years in, the ground. So. That's sort of things that we do so we've had to do Hardware we've had to do software we have to do networking, etc. And it's all powered today. On Google, cloud platform. So. This is just a quick, list of some of the cities that today, are, using, the smart parking solution. And, we're. Starting this is a still journey in in progress, you know a lot of the things that we're doing are still just the very basics, of just, show me where a car park is you know tell. The city or, the business, how. The parking. Is used you know it being. Used. Efficiently, and effectively and, continuously. Or is it underused, or is it overused, is the, pricing, right. Are. The types of rules, such, as how much time you're, allowed to park in a certain parking, spot actually, appropriate, etc, so, these. Are just some of the cities that we're running today, and. The. Big question where. We're starting to pose is. What. About your city, so. Today. We. Already you know as you can appreciate we've, had to build a comprehensive, range of solutions and this diagram just illustrates. Some of the types of functionality. Targets. Or audiences. That. This, technology. Delivers. To first, of all the person in. The car driving we, deliver. A broad, range of applications which, give guidance, and, information about, parking, spaces as using Google Maps using, Street View is, all that sort of interactivity. That convenience. That connection, with you and so, that you understand, what's actually happening, and where you're going and then and then finally be able to actually pay. For that parking, session, whether it be a pay for what you use so, you know a timer, starts to just tick. Away the time and when you've finished your, car parking session and you drive away it closes, that session and, we do that today or you, know it can be, fixed. You know prepaid you know you pay for 20 minutes or pay for 30 minutes or whatever so. That's one class, of application, that, we are delivering and, just. Last week we delivered two new application. Two new versions of that application to customers. In other cities. The. Enforcement. Officer you know I know you, know this is probably the least desirable. Aspect. Of parking, but there are people that need to actually go along the streets and and, effectively, and efficiently manage. Where. The cars that. Are just, not playing by the rules right and and, and do the necessary thing of putting a ticket on your window now, what, we give is live real-time, information to, those officers, on the street telling, them exactly where the car is, exactly how much they paid when did it expire, etc.
Etc Etc so and this is real-time, information, a. Lot, of what. Fraser, was just talking about it's about being alive the city is alive and, and these sort of things need to be constantly. Moving. Talking. About IOT. One, of the things that we have. Found, well is, a necessity, of parking, is that. This. Is actually legally, enforceable, IOT. As you. Well. Know as, being drivers, and and you know you've ridden the cars and parked on cars we all have right a, car can actually leave a parking, space and another one pull in right away right, and we're talking about wouldn't, a second. Assuming. You're not speeding too fast. But. It happens, really really fast and if, we didn't detect when, that new car comes in we could give a parking ticket to, that second. Arrival we. Can't allow that and this is actually the rigor and the. Significance. Of the class of IOT that, parking, is now, also as I commented before this is a battery operated thing and it has to last for years but. Meanwhile we're doing this real-time communications. We, buried in the ground and it's usually in concrete. Or timac. Cement, and so on it's, very very nasty for radio communications, we've had to develop that type of radio communications, and finally, we put big metal things overtop of it right which also gets in the way of doing. Reliable. Secure. Robust. Radio, communications. So these are the sort of this is the class the edge of IOT, that, parking. Is all about in smart parking has solved, and I, can, tell you you know we've got a lot of wounds, on our backs a lot of a lot of scars from, learning, this technology, and in, fact as I commented, you know dogfooding, our own technology. Has been a really really good, way to make sure that we do the. Right thing. What. Has, actually started, to come back to us from our customers, you know from those cities from those. Customers. Who are utilizing our smart parking platform, is once they put those gateways those communication, Gateway's onto their lampposts right and getting power and and, network connectivity to them either through 3G, 4G or or, some sort of other, communications. Mechanisms, that. Gateway becomes, a very strategic element. For building, out more. Sensing. And more capability. Into, the smart city infrastructure, and and the solutions, that a, city, wants, to actually deliver and so what, we've we've, been actually, being told by our customers, and we're responding, to, is building. An open platform and open framework, which. Enables, smart, cities, and so it's not just about parking. It's actually about modern. Life in, cities pretty. Much as. Fraser. And, I am talking, about now. And. Where this is taking us is actually in to building, a broad, range of.
Solutions. That sit on top of the smart cloud, platform. Which is completely, GCP, it's actually. 100%. Pure service. As, well, there is no Linux, operating system, in it there is no Windows, operating system, in it it, is completely, built utilizing. GCP. Serverless. Computing. Components, and this is really exciting because I believe this is actually the future, for how we, build large-scale. Internet. Scale global. Scale live. Network. Computing, systems. Which. Is essentially, what, I'm going to talk about here now the first building, block that we utilized, was, the, cloud. Core. IOT. Functionality. That Google. Provided. And we did this we, started using it around about two years ago, prior. To that we'd actually been building our own our own IOT. Framework, for managing our devices but, as we were listening to our customers, and seeing the need for right before smart. Cities we needed an open, IOT, framework. And it. Just did not make sense to reinvent, that wheel especially. When you had solid. Serverless, technology. That was also going to be driven by the market that, was going to be open and flexible that. We didn't I just our, team didn't need to rebuild we didn't even need to support it you know we don't need to now maintain, that technology. And we can trust that GCP, and Google are going, to drive that more and more into. The the, functionality, requirements, of the market and we just are able to, benefit. From it and as. I commented before this is actually giving us, city. Scale live. Responsiveness. We. Are doing today. With, those cities that I listed before in. The order of about a million and a half to two million, event. Sensor. Event transactions. Per day. What. You might not have noticed also on that slide that previous one that diagram was we also do cameras, you know there's especially, in in, the, UK we do a lot of number plate recognition, and. We're doing about a million, images, per week and, and, so that's the class of computing, the class of the capacity. Of data that we're processing through this platform called, smart cloud. The. Following three things that I talk about here is one of the one, of the objectives. Of our smart cloud platform, was to actually eliminate, the, need to have software. Developers, involved, in everything that a customer, wants we. Wanted to enable. The customer, to build their own dashboards. Their live dashboards. To display, them anywhere, that they needed to without.
Requiring Us to go and hack. Some code the. Same is true for data, analytics, and data processing and what, we have, actually done is we've used bigquery. And data. Studio, which is a fantastic tool you, know isn't it, my. Analogy is you, know Gmail to, email is data, studio to, Big Data it's, actually that is free, like, Gmail, is is it's, an amazing tool and I'll show you in a moment just, from some displays, of those, sort of reports that we're generating, directly. From smart cloud which is using, bigquery underneath, it the. Same is true for business rules for. Parking, there are very complex. Processes. For managing business. Rules in a time of day when. Parking, can occur, for, certain types of, uses. Of that parking, when. Is enforcement. Being enabled, and when is it not certain. Car parking spaces may become non. Car parking spaces that set for 30 to allow traffic. Flow all those rules, including. Also other things such as has, a payment arrived, have they overstayed, their welcome and, that parking space because they've gone beyond. The maximum period you're allowed to park so all those business rules which historically. We, wrote custom, code into the system and you know had some sort of a UI that you type in some data you, know typically. Into a database now. What we have is an if this thin there that rules. Engine which processes, us continuously. And. I mentioned. Our mobile, apps for guidance, and payments and other things in, fact the, app area. Is just so significant, and you know we're all users, of apps what. We also realized was, you, just don't want to have yet another app you, know and it is you. Know there, are a number of surveys, that have already shown, that you know after 90 days or so of getting a smartphone you don't typically, don't load on the rap you, know getting that footprint onto your phone is really really hard and so, what we've built is an app framework. Obviously. We have. You. Know full. Functional. Apps and a smart parking app on the App Store's today is our app, and. And a variety of cities, a number of the cities that I listed there have taken that out app and, we've. We've actually branded. It and facilitated. And with functions that this is appropriate for them but, more interestingly is taking those components. Such, as the guidance component, or the payment component, and embedding. It in your own app and so, that's the framework for, mobile apps that we've also developed and. Finally. Managed, API API, is actually, how you integrates. How you enable, innovation with. Ourselves. Internally. How. You work. With partners, and and, software, vendors as well, as integration, with city systems, and so, a full. Suite of of managed, api's which are and that, is using the apogee technology, from Google cloud you, know guess, what. So. Just. Want to quickly now show you if. We can switch to the. Demo. Yay. I must, admit we had a little bit of a network. Issue, as. I sort of walked up but here here's a live. Picture of, one. Of the cities it's, actually Wellington City the. Capital of New Zealand, so. One, end of the world and. And what. We've got here is I. Can. Unzoom Ian into, the city, these. Are the parking bays that I around. The city of Wellington, and. I can see that that's been vacant, for 38 minutes, this. Is live live. Data right. From. The. City, right. And. This is just one, aspect, of. Visualization, and. Because. It's built into dashboards I can do such things that I push.
It Into full-screen. Mode and, display you know you can put it onto big screens elsewhere. Every. Every, one of these dashboards is just a URL and. One. Of the, powerful. Things is I can create my own dashboards. And there, are some default ones there's the data smart. Zone is what we call our infrastructure, area where we can monitor and see see, the infrastructure, and, and. What you saw earlier on and phrases, slide is that that, sort, of map. Of the, city's. Activities. Going on well, here where we've got on, one of the other what we call tiles, is actually. The 24-hour. Cycle of the, heat map of the parking, utilisation on the city and this is just another bit of insight that, we're providing cities, if. You, notice just. Just, some of the things prove this is real-time you, can see the the numbers changing. There those are parking events that are happening on the other side of the world right now. Here's, another city this is Hamilton City in New Zealand as well. And. I think I've lost, the other ones I was. Going to also show a. Couple, of cities like Cardiff and so on so can we go back to. Our slides. So. Just. Going, back to those. Sort of smart. City requirements. One of the things that we, in. Smart, parking and in the smartpak a solution, I have to respond to and pretty much what Fraser was talking about is just live, streaming, this constant. This, instantaneous. World, that we live in and this, is a change. For how computing, needs, to be done it's no longer store. Something to do a database then, retrieve, it do some sort of processing, on it produce, a report and. Then store it back into a database etc things, have to be instantaneous, and responsive, you, know for example if you were driving, down. The street and you're using Google Maps and it took twenty seconds to sort of give you the next turn you'll, probably be on, the wrong Street up a tree or something like that. So. This, is the new, norm. Is live, streaming the efficiency, and convenience and, I've been talking just, indicated, the things like apps that we're delivering the, dashboards. Providing, those dashboards to any display, whether it be a display, on on a street, because, it's a URL anywhere, there's a browser that can be displayed and one one of the the experiments. That we were actually working through is just using Android, Android things to, display, that in remote places on, to other displays, and, this. Is really, great for providing. That convenience, of information. Where. It's pertinent and a dashboard can be just for example, how, many bays are in this area, of a street or in this honest, floor of a parking building and, so this is all about connecting, insights, to you and the. UI mean here is there are many different, audiences you know it can be you the the, user of parking, but, it may also be the city. Strategist, who wants to have understanding. Of the of what's. Actually really going on either the. Uses. And mechanisms, that are being operated. For, the parking is it optimal, for the city you, know as we all know it becomes very very, inconvenient. And, and, challenging. When you're circling, round, and round blocks, just trying to find that Park, now. Using this real-time data accurate. Data we, can take you right to that Park and when it changes we net we're letting you know as well. What. We're doing is we're starting to create the, ability to enable, new outcomes, and. We've done that both on the technology, so, rather than using classical. Computing and I actually class. Using. Standard, traditional servers, and server. Os's as being classical. We've, gone completely. Service. Completely. What I call cloud native for. This platform it's. Essentially, the same way that Gmail works, the same way that Google search works is how we've built, smart, smart, cloud our platform, and it's. Enabling. Ourselves. And also, our customers. To, actually achieve, new outcomes, and this is driving, us, to, become more responsive. With our roadmap you know a road map is no longer a 12-month. Road map it's actually dynamic and, changing because the way we're implementing, the functionality, and the way we're enabling our customers to also have their roadmaps, of functionality, is, is in a much more agile in a much more modular, and freed. Democratized. Manner democratizing. Over word used word I think in this conference. So. Here's just a quick. View. Of the, architecture, of smart cloud and as you can see it's heavily, GCP. And as, I, mentioned totally. Service. So. I see core is where we ingest. And we send, out messages from, and we also manage, these tens, and tens of thousands, of devices. Both. The gateways, and the, sensors, that are actually in the streets or in the parking buildings I don't, know if you've been to parking buildings where you see the, red green lights. Over. Parking bays it's quite common in some some parts the world certainly it's, very popular on, in.
Australasia. And. And. It changes, your whole, dynamic. You drive into your parking building and you literally will just glance out of the periphery of your vision too seed a parking, spot yet and yeah, and. Then we put signs, throughout. Just saying okay, there are five up on level four and there, are twelve up on level five and so, on and and also just be able to glance at other site so this sort of information is all being managed by IIT, core both the the. Measurement. And also, the control of those, indicators, for example. We're. Also managing. The data in a very dynamic ways I talked about using, bigquery, as. The fundamental, core for, big data but, simultaneously we're, using BigTable. Which. Is essentially, the engine, underneath Google search to, also manage this parking events in real time and then. The API is I commented about four, dashboards, for payments, and and actually any application. So. Over. To you now hopefully, that's given you a taste of what we do the, point is that what, we're doing is real-world IOT. That is trying, to and is actually reinventing, the experience, for, cities already.