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  • Huawei

    Big Data Prepares Smart Cities for Every Situation

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.

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