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Edwin Diender

As Chief Digital Transformation Officer in the Enterprise Business Group, Edwin helps to advise our customers and partners regarding innovation, business, and growth using Digital Transformation with a focus on Smart City/Safe City economics, eGovernment and Government cloud, and Big Data Analytics and Digital Transformation for Smart Cities.

  • Edwin Diender

    Interview

    AI Lets Cities Learn to be Smart

    Part 1 of our interview with Edwin Diender, Vice President, Government & Public Utility Sector, Huawei Enterprise Business Group. | September 2018

    Edwin Diender

    Transcript
  • CLOSE

    New Horizons: You are listening to New Horizons, the podcast channel for Huawei’s ICT Insights Magazine. Join us as we talk to innovators and thought leaders from around the world.

    Hi everyone. Today, we’re here with Edwin Diender who’s the Vice President of government and public utility sectors the Enterprise Business Group at Huawei. And this is going to a three-part interview, and we’re going to talk about Smart Cities and Artificial Intelligence; Smart Cities and the IoT; and Smart Cities and Big Data. So, first of all, let me introduce Edwin. Edwin thanks for joining us today.


    Edwin Diender: My pleasure to be here, thank you.


    New Horizons: So, Edwin, what can you tell us about Smart Cities and Artificial Intelligence?


    Edwin Diender: Well, what is not to tell about it because there is a lot. Maybe we should start first with where Huawei positions Smart Cities first.


    New Horizons: Fair enough.


    Edwin Diender: And then see if we can link it to Artificial Intelligence if that’s okay with you.


    New Horizons: Sure.


    Edwin Diender: So, for Huawei, Smart City is not something that you can get a purchase order for because it’s not something that sits in a box as such.


    New Horizons: Right.


    Edwin Diender: For Huawei — the idea or the principal — would be more on a conceptual level. We’re looking at it as something like a platform that’s capable of linking different programs and initiatives that would allow and help a city, or a residential area, or what have you, move higher up the value chain.

    And these different programs and initiatives combined eventually would lead to, let’s say, a Smarter City. Artificial Intelligence would be a component where you could think of pieces of technology that do not require any pre-configuration, any pre-staging, and maybe not even configuration, or onsite implementations. What we mean by that is consider Artificial Intelligence almost like a brain of a child, waiting to be opened up to be addressed, and via learning-by-example, and learning-by-doing.

    It builds experience and handles as such. An artificial component in a Smart City as an example could learn from other elements in the city by itself and understand maybe an Artificial Intelligent-enabled camera would perhaps just be put in the network of the city, and it understands automatically that it looks at images of maybe cars that are speeding.

    Without the camera itself needing to be configured to do that because from an artificial intelligent component such a camera would get it, and it would also learn. Perhaps the crossroad that it’s looking at today has a speed limit of 50 miles an hour, and maybe over time, perhaps the city government decide that perhaps the speeding limit should go to 30 miles an hour. Normally speaking, all these speeding cameras need to be configured separately.

    And at one moment, it needs to be pushed into all these cameras, so they get it now. There’s a new rule that applies. That would be one example.


    New Horizons: Okay.


    Edwin Diender: Another example of Artificial Intelligence for cities would mean it understands what it does, and what happens with traffic congestion as an example, or maybe water floods from canals, or levies that are rising, and it understands that it relates perhaps to a weather report that sits in a database that it has pieces of information from it. It can learn from it, and it then understands that there are similarities from back then to today, and it needs to do something with notification, or what have you.


    New Horizons: Well, would another example be let’s say there’s a big football event in a city, and the city may not be really well set up for traffic flow, for a large influx of cars, and trucks, and all the catering that has to happen.

    Where an AI could learn or be told that, you know, on this particular day there’s going to be an event. You may need to monitor or change traffic signaling intervals, how long the lights go… or, to be able to move traffic around. Would that be a good example?


    Edwin Diender: That would be a very fair, and a very perfect example; another example of how and where Artificial Intelligence comes in. Another point that we could perhaps bring to our conversation is the one that when it comes to intelligence, there is not really a clear definition of what intelligence actually is. That makes it very hard to then determine the artificial side of that. And as a result, of that it makes it very difficult to put in place whatever anyone could think about what artificial actually is, or what Artificial Intelligence actually does.

    All the examples that we’ve now discussed could be debated as yeah, you know, those are examples of advanced algorithms, which is fair because they are, but that’s exactly what a child’s brain processes in a very advanced way. It goes from trial and error. It does something and learns from it. It puts a hand on a stove, and it understands that this is too hot to handle are all part of a learning process, and to improve the capacity of a brain of a child to prepare that child for whatever comes next.

    I think when it comes to Artificial Intelligence in city and in city management, as I said before, it’s not something that you can buy out of a box. You cannot buy a Smart City. It is a process, and it moves higher up the value chain, and as such, it learns by trial and error. It learns from mistakes, and it learns from things that go very well. It triggers incentives just like a child’s brain would do it. I think Artificial Intelligence and Smart Cities combined are a learning curve. They’re on a learning track which I think is very, very interesting to be a part of.


    New Horizons: Well, and I agree with you. I think it’s absolutely right. We’re still in the fairly early stages of Artificial Intelligence development. They have a very narrow focus, there’s no general purpose AI, yet. So, what would be another potential example in closing out this first part of the discussion about Artificial Intelligence in Smart Cities?


    Edwin Diender: The component and the element of Artificial Intelligence within Smart Cities is something that sits very much on the side of the equation where you could say items are AI-enabled or AI-prepared.

    It means, in all fairness, that whatever we as Huawei Technologies are able to put in place is that the solution stack that we provide for Smart City deployment are AI-prepared, and AI-enabled for whatever bright application, or for whatever Artificial Intelligence service is coming up in university labs, as an example, to be put in place, and to be tested and to be monitored, and to be controlled.

    That is where Huawei sits right now. We provide a solution stack that is AI-enabled, that has the early features and functionalities of what eventually Artificial Intelligence in the full meaning of the word, encompasses as a potential: from a chip set point of view, from an application-carrying point of view, from a distribution, and a transmission, and a data collection, and analysis, and from a self-learning, and a deep learning point of view.


    New Horizons: Would you say that most major cities have some type of Artificial Intelligence or Smart City long term plans, or should they?


    Edwin Diender: They should. I wouldn’t say that all or the majority of most cities would have this in their, let’s say on paper. What they have is a clear view of the fact that they need to do something, and they need to move higher up the value chain over a certain amount of time. What they struggle with is what to do, and what to do first. And they do think in a digital way. So, digital transformation, digitalization, and digitization — which are two different things — are in their minds. I think what that also means is that within that is a component of Artificial Intelligence already embedded, but it’s not clear because there is no definition yet. The very defined, and very end-to-end, in a very closed definition.


    New Horizons: Well, I don’t think we’re going to ever see things become less complicated. I mean entropy rules. So, this is a very interesting subject that I’d like to touch on again at some point in the future. So, I think this is a good stopping point for the first section talking about AI and Smart Cities, and please stay tuned for part two which we’ll be talking about Smart Cities and IoT.


    Thanks for listening to this episode of New Horizons. If you enjoyed it, please be sure to share it on social media. Once again, thanks for listening.


    Biography

    As Chief Digital Transformation Officer in the Enterprise Business Group, Edwin helps to advise our customers and partners regarding innovation, business, and growth using Digital Transformation with a focus on Smart City/Safe City economics, eGovernment and Government cloud, and Big Data Analytics and Digital Transformation for Smart Cities.

    CLOSE
  • Edwin Diender

    Interview

    The IoT Heralds a Healthy, Holistic Smart City

    Part 2 of our interview with Edwin Diender, Vice President, Government & Public Utility Sector, Huawei Enterprise Business Group. | September 2018

    Edwin Diender

    Transcript
  • CLOSE

    You’re listening to New Horizons, the podcast channel for Huawei’s ICT Insights Magazine. Join us as we talk to innovators and thought leaders from around the world.


    New Horizons: Well, thanks everyone. We’re back for Part Two with Edwin Diender and Smart Cities and we’re going to talk about IoT, which also ties into, of course, Artificial Intelligence that the IoT provides the sensor bases for. So, educate us on IoT in Smart Cities.


    Edwin Diender: Well, the element of IoT, so the Internet of Things, have been available to cities already for a long time. One key example is one that I think originates from the 1970s, where sensor technology is being used as a copper wire ring that sits in the tarmac that you’re standing on with your car when you’re waiting for a red light. All the lanes and all the crossroads at a junction have these links. There is a system behind it.

    You could say maybe that time wasn’t connected to the Internet, but it was some sort of a network of things that understands that in lane one, from north to south, there’s a car waiting at a red light; and the other three lanes, or the other three entrances and exits of the crossroad doesn’t have a car at all; or maybe they’ve got two, and one lane has five. So that’s more cars waiting. So that has some sort of intelligence already behind it and it has some sort of a network of things already attached and combined and working for it. Interconnectivity and network of interconnected things. So we’ve got a World Wide Web, not of computers, but a World Wide Web of sensors and a World Wide Web of things which are connected: sharing information, messaging, sometimes talk to each other, and IoT in a city provides the ability to not have a human eye with a human failure of the eye, looking at things maybe with a certain latency or a certain preoccupancy, but it’s very straightforward. It’s very black and white.

    It could be a sensor that understands humidity, it understands pollution in the air, it understands water pressure, and all these things combined can provide input to what you could say is the ‘brain’ of a Smart City: An Intelligence Operations Center that translates and transforms all these pieces of data into information and that converts this information into insight and that can give maybe notification. A notification that in linkage with perhaps the weather report, water rises at a certain area, or in a certain rural area, or in certain outskirts of a city to a certain level which is similar to three, four years ago when we had a major flood. So we probably need to anticipate.


    New Horizons: Right and there was an interesting partner exhibition at CeBIT 2018, where there was a smart manhole cover, where it was not only able to monitor potential water rising, but monitoring access to the conduits that run there that are you know actually quite valuable in the materials that are used. So in maybe rural areas you want to monitor access to those so people don’t come in and steal copper, or you know, electrocuting themselves.


    Edwin Diender: Correct, I don’t know how many kilovolts of electricity that goes through copper wire infrastructure. Do we close it at the moment the manhole cover goes open: yes or no?


    New Horizons: Excellent point.


    Edwin Diender: I think it’s also fair to say that sometimes ICT, or computing technology, has been put in place to take away the human resources on that, because a computer can do it better and faster than a human. I think that’s not the way we should and that’s not the way we have to look at it. What it should do and what it does in the majority of the cases is, number one, it is adding to the resources. Every investment in computing requires almost four or five people around it to maintain it, to manage it, and to uphold it. Does it take away jobs at some point? Yeah it does, but it creates five other types of jobs back.


    New Horizons: Right.


    Edwin Diender: In return, perhaps it makes the job of the current people more efficient and more productive. So it doesn’t take away the job from them. It makes them more focused on the actual job that they have, or the thing that they need to do in their job, in the right priority, and in the right priority settings.


    New Horizons: Well, maybe reducing a mundane or boring job which they may end up losing focus on over time and relegating that to a particular device to do that, so they can focus on higher level.


    Edwin Diender: Or get rid of paperwork.


    New Horizons: Right.


    Edwin Diender: Or repetitive actions, or repetitive activities which are a waste of time, and there’s a lot of time wasters. Another example of the Internet of Things in Smart Cities is where all things connected create a more holistic view of anything and everything that goes on in a certain area, which is very key for City Managers to understand what goes on in their city and if they need to anticipate on it. The Internet of Things allows us, together with backend infrastructures where big data analytics and Artificial Intelligence component sits, to help us in a decision-making tree and a decision-making process to do things faster, more on point if you like; or because of the time-saving component within it, it gives us more time to rethink, or to think better about the decision that we’re about to make, which lowers the level of mistakes actually.


    New Horizons: Well you know and that ties in to something you were mentioning: water and floods. But also when you talk about utilities you know, water quality, water main breaks, electricity breaks, gas line breaks.


    Edwin Diender: Anything.


    New Horizons: Things like that. It gives you the ability to understand what’s happening in the environment so you can dispatch services to take care of those problems and make sure that people’s services aren’t interrupted.


    Edwin Diender: Very, very true. Just like with any other piece of information or information system that is out there, there’s two ways of looking at it. We look at it from a project-by-project basis, which has a stop and go motion. There is an issue somewhere, we need to solve it. Can we find sensor technology, or is the element of Internet of Things helping us to do so, to create this holistic environment that has a 360-degree view on everything and anything that goes on in the city.

    The point I’m trying to make is the idea and the principle of the Internet of Things from Huawei’s point of view is to provide a platform that understands and that speaks the majority of all these different languages that are already out there, and that creates a horizontal layer of technology that is capable of bridging and overlaying all these information silos without necessarily needing to replace, or needing to upgrade them. The focus that we have at our platform is to integrate and to create an interoperability between all these silos and take it from there as a starting point. The Internet of Things for Huawei is also to look not just at the things, but at anything, at any moment in time.


    New Horizons: And I think that’s a perfect stopping point for our second part in the three-part series. Edwin, thanks for your expertise in IoT and again, I’d like to come back at some point in the future, and explore it a little bit more. It’s a very deep subject.


    Edwin Diender: My pleasure, thank you.


    Thanks for listening to this episode of New Horizons. If you enjoyed it, please be sure to share it on social media. Once again, thanks for listening.


    Biography

    As Chief Digital Transformation Officer in the Enterprise Business Group, Edwin helps to advise our customers and partners regarding innovation, business, and growth using Digital Transformation with a focus on Smart City/Safe City economics, eGovernment and Government cloud, and Big Data Analytics and Digital Transformation for Smart Cities.

    CLOSE
  • Edwin Diender

    Interview

    Big Data Prepares Smart Cities for Every Situation

    Part 3 of our interview with Edwin Diender, Vice President, Government & Public Utility Sector, Huawei Enterprise Business Group. | September 2018

    Edwin Diender

    Transcript
  • CLOSE

    You’re listening to New Horizons, the podcast channel for Huawei’s ICT Insights Magazine. Join us as we talk to innovators and thought leaders from around the world.


    New Horizons: So, we’re back with our final segment of this interview with Edwin Diender, Vice President of Government and Public Utility Sectors Solutions for Huawei’s Enterprise Business Group. On this final segment we’re going to talk about big data and maybe pull the Artificial Intelligence and IoT segments into a nice wrap-up at the end of the interview. So, Edwin, we’ve been talking a lot about IoT and Artificial Intelligence, and that generates a huge amount of data. How is that data processed and used?

    Edwin Diender: If you look at where Huawei comes from and where we sit, is that the systems and services that already are out there are built on different pieces of technology, and it now needs to work together. We need to aggregate all these different information systems, and we need to pull all this information from these information systems into a backend infrastructure; and we need to blend it, and we need to structure all that data from an unstructured point of view. But we also need to do something with the right language that it’s been written in, or the right format that it’s been stored and archived in.

    The first thing that we look at when it comes to big data is to provide a platform that is actually capable of doing that and that speaks the majority of all these languages, of these different information systems and information silos.

    The second thing we do is we try to look into what does that mean when it comes to collection of all that data? And what we do in Switzerland with CERN, where this light particle has been found, the Higgs-Boson, is a key example of what it does with dealing with a vast amount of data in a shortest moment of time. Imagine how much data that actually is.

    Coming back to the platform, if we’ve got a platform that’s capable of doing that — then surely, we’re able to create a similar kind of platform that can deal with data that is less vast, and the majority of big data analytics platforms are able to do that, including Huawei’s.

    The second part, structuring that unstructured data, looking at the things that are similar, we look for the things that are not similar, we look for the anomalies. So, we need to put aside the ones that are different from before; doing that and analyzing that only a few are able to do that.

    But then bringing it out, not as a piece that has been analyzed and to provide you with the information, but that transforms this information into insight, is something that’s actually rather unique, and not many vendors worldwide are able to do this.

    These three elements combined make a Huawei big data analytics platform work.


    New Horizons: What you just said sparks something in my mind. If I’m a City Manager or a Mayor, or some type of government official, to have the ability to collect this data and create a snapshot in time of my city…


    Edwin Diender: Right.


    New Horizons: …and how it’s working under, let’s say, again, we referenced a big event before, or, let’s say — there’s a storm, a tornado, a hurricane, how did the city react during those real-world scenarios…


    Edwin Diender: Yeah.


    New Horizons: …and how can we create better planning and structure for the future because we have this historically accurate data with a very minute amount of detail?


    Edwin Diender: Exactly, the predictive analysis part of it is what we now talk about but also, predictive maintenance, predictive services, predictive support, as one of many elements towards the city management team, which is what the Mayor and his staff currently actually are. They’re almost the CEO of a corporation, if you like…


    New Horizons: Of course.


    Edwin Diender: …of a nonprofit organization. Actually, if you look at the top 10 of what generates the world’s GDP [Gross Domestic Product], they are cities. I think, five or six in the top 10 are cities, and only three or four of them are actually countries. So, the world’s GDP is comprised and combined by the GDP of cities, and we don’t necessarily mean a city-state like Singapore, as an example. Between quotation marks, I say, “real cities,” so, there is a country that has a capital city and a lot of other cities, one of those cities are contributing to the global GDP more and are in the top 10 of the world’s GDP.

    What that tells us is that a Mayor of a city becomes a CEO almost. He needs to be very corporate in his way of thinking. The reason I’m saying it like this, and the point that I’m trying to get across, is a big data analytics platform, just like a business information system for one of the financial institutions of the world, commercial or government bank, hospital institutions, educational boards, and agencies, and what have you, ministries, are all supported with such a platform that can transform information into insight to what goes on; how does that relate to a learning curve from the past? And what is the best advice that the system can give you to do?


    New Horizons: To your point of about insight, to me that was also a critical bit of information. If I am the CEO of a city, how’s my city’s health? How am I growing? Am I contracting? Am I growing in certain areas? Do I need to plan for more infrastructure on the northeast side or the southeast side? And that information, you know, usually is in the minds of, maybe, real estate developers…


    Edwin Diender: Mm-hm.


    New Horizons: …or people that are living there or they want to expand a certain part of the city.


    Edwin Diender: Right.


    New Horizons: But this type of solution would give city planners much more insight into where they need to precisely put their efforts and where the infrastructure really needs to grow for the future.


    Edwin Diender: Totally.


    New Horizons: Because those plans are five, 10, 20, 30 years out.


    Edwin Diender: Totally, it would make their decision-making process more efficient, more productive, and higher up, in terms of your decision would be a better decision. If there’s a historical database that we can look into and that we can extrapolate from — perhaps create 3D models and, say, you know, what would happen if? What if we try an area like that? Big data analytics platforms are also able to provide you with the ideas around certain directions and give you the results of an alternative.

    Your decision becomes a better decision than without this kind of insight. And it is in real-time. So, real-time means whatever goes on in the city now and what you decide now has an impact on maybe your GDP, maybe on the livelihood of people in your city. The point is, in real-time, being able to respond, react, and anticipate on what goes on now, built on real-time information. Because there is a platform that is able to look into this vast amount of data that can collect it, that can transform it, and turn it from information into insight. It is a key component of what a big data analytics platform should be about.


    New Horizons: Well, and I think that’s a perfect wrapping up of all those different pieces that we’ve talked about. Is there anything else that you would like to add to that point?


    Edwin Diender: Well I think we’ve used many words to come to the same center point of attention, so to speak. I hope that the listeners of the podcast have picked up that number one, we’ve got the systems and services in place to support this. We’ve got the platforms in place that can carry this and that can create a foundation for all of this, but the key component I hope that has come across is that all these items that we are talking about eventually become a function, and a feature, and a technicality of the system. It is part of the features spec that — does that make sense if I put it like that?


    New Horizons: I think so. It’s part and parcel of all together.


    Edwin Diender: Right. So, Artificial Intelligence, the element of the Internet of Things, and the big data analytics that goes along with it are core components of the feature stack of such a platform that supports a city and that builds a Safe City foundation.


    New Horizons: Well you’ve done a wonderful job explaining some very complex issues and bringing them down to earth, and giving some real-world examples of these things have been installed, they’re in place, they’re working, and they’re enriching the lives of the people that they touch.


    Edwin Diender: That’s very correct, yeah. Perhaps, if I may make a closing statement in this case? I’m often confronted with someone that says, “Well, you know, it’s very much like back to the future.” I dare to say there’s nothing futuristic about it because what I speak about is an experience that we have built in the past years and, as I’ve said before, it comes from cases that already are up and running, are deployed, are contributing to the benefit, and the value, and the livelihood of people living in cities around the globe.


    New Horizons: And that’s one of the purposes of this podcast, is to bring that information to people that may not be aware that look, this is out there today, this is happening today…


    Edwin Diender: Absolutely.


    New Horizons: …it’s been happening for a while…


    Edwin Diender: Absolutely.


    New Horizons: …and Huawei has been at the center of many of those developments and installations around the world.


    Edwin Diender: Absolutely, there’s nothing futuristic about it. I mean, back to the future, really? The future is now.


    New Horizons: Right, very good. Well, Edwin, thank you very much for joining us, and I’m looking forward to having you on again soon, making this a regular part of our podcast interview. So, thanks again.


    Edwin Diender: Thank you.


    Thanks for listening to this episode of New Horizons. If you enjoyed it, please be sure and share it on social media. Once again, thanks for listening.


    Biography

    As Chief Digital Transformation Officer in the Enterprise Business Group, Edwin helps to advise our customers and partners regarding innovation, business, and growth using Digital Transformation with a focus on Smart City/Safe City economics, eGovernment and Government cloud, and Big Data Analytics and Digital Transformation for Smart Cities.

    CLOSE

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