Categorizing Smart cities and Big data foci of Japan

Transcription

1 WECC2015 Track 1: Resilient Infrastructure for Society 1-4 Strengthening national interests and creating new industries using big data Categorizing Smart cities and Big data foci of Japan Professor, Urban Innovation, Asia University Hisakazu Okamura First of all, please allow me to introduce myself. I was born in 1955 in Tokyo Japan. After my graduation from Commercial science division of Waseda University, I joined IBM Japan in 1982 as an apprentice system engineer and a sales taking care of electronics component manufacturing customers. In 2003, I voluntarily established a new business project of environmental related solution based green business. I think it was too new area for all the IBMs over the world at the time. In 2008 IBM Japan officially decided to fund a green business division as the first project prior to all IBMs in the world. I was appointed to the General Manager of the division then. 6 months later, IBM United States announced Smarter Planet collaborating with Obama s Green New Deal. This was exactly the timing when green business met the city. This environmental related business has kept on changing its shape from carbon dioxide problem chemical contamination to the smarter city on the smarter planet which meant how the people could live better supported by IT technology. Ministry of Economy, trading and Industry Japan established 2050 workshop with us for smarter cities in Japan in This is the first official smart city project that Japanese Government did. Smart Community, the project has become famous as 4 region test project for energy in Yokohama, Kitakyushu, Toyoda, and Keihanna later on. I am still working for several Governmental organizations with similar roles around smart city after my book Smart City was published. I am now working hard on a very new division of Smart city in Asia University. The first Smart city division of 1 University will start its operation in April From this year 2015, I am also working as a member of egovernment promotions of Government. Well this is a chart which is used by IBM or many companies to describe the areas of Smart cities. Sometimes smart city is considered as a name of city real estate project or some construction projects but the fact is slightly different from them. Basically the word Smart City is describing business focus. These are categories where the business exist. The time when the computer industry has begun, computer or some data processing business were only between companies. For instance, IBM was selling a system to a customer for making the customer s business process smoother or better. This is called B2B business. Now in 2015, most of the major companies already have computer systems and ERPs (Huge system software covering from accounting to Manufacturing, SAP is a famous product) with them. Simultaneously the carbon dioxide related subject, global warming, and emerging countries city development are getting

2 very active subjects to discuss in also the business world. Computer industries and also the practical global level issue are getting closer and sometimes merged They steered to another direction. The idea was to provide IT solutions not to a company for its own benefit but a city which many industries and issues are gathered for solving common problems. City projects are parts of Business Categories of Smart city. From the issue holders view, they have infrastructure, city management and citizen related problems. It means these areas are the places to be invested, places to get smarter with IT solutions. When you look at this chart and see which area Japan is focusing on. After 311, all the 54 nuclear power plants have shut down. Due to the nuclear plants frozen, many fossil fuel based power plants have restarted or built again. Simultaneously Government has accelerated the renewable energy projects represented by Feed In tariff by METI. It is said that Japan as a country is focusing the energy area in smart city. Matter of fact, besides many energy projects in Japan, European countries were announcing many city projects of health care, public safety and Government operation including big sized and tiny village projects all over the world. Please take a glance at the word Olympic on the far up right and the one on the left corner. From the view point of Olympic coming to Tokyo in 2020, Urban design or development should be the focus of its smart city considerations but if you change the angle, public safety is going to be so important subject to discuss. It means, the investment not only on the urban development but also public safety, of course more, are targeted as business focus. There is an important word Aging. 20% of the population in Japan is over 65 years old now. Within those elderly people, the employment rate including those people is increasing. Of course the issue of wellness and medical is getting more serious than ever but they say Japan is running faster than the others as a leader. What does it mean the leader? Japan is the first country which is facing to this aging problem in the world and this country is taking many actions toward earlier than other countries. I could say new trials of Japan Smart cities are urban development toward the Olympic game Public safety and the actions for the aging society. Focus of the smart city in Japan has been changing into new areas now. Prime Minister Abe leads the project titled Local community vitalization. As it shows, this is the area of smart city with Local government redesign on the top. This is a chart describing the cycle of the disaster This circle is showing the time going. In the area down left, this is the timing called Recovery. In the beginning of this timing, people need food and then water. Houses and roads are getting needed later on. Sewages and Industries may be needed to walk forward and start working. Entering the era called Reconstruction after that the damages of the disaster have been cured more. People start to reestablish the new city to live there again. Education, job creation and other creative requirements are coming up so quickly. The period called Before is just after the reconstruction and just before the next disaster comes. In this period people are acting completely different from the era before or after. Every single activity creates data. Just after an earthquake If a person tweets that he wants have water this might be a data of the emerging demand. After three months went if the same person tweets the same water demand that will have another type of demand. The point is that DATA HAS BEEN CHANGED. Even if the same person or same facility input the data twice other factors can make those duplicated data different. Obviously the data that people need food, and the data that people need the road are completely different. How many people want rice 2

3 and Which road is safe for bus instead of damaged train?, these different data keep on changing independently by influencing each other. As you can guess, those data describing the smart city categorization and this changing data like the disaster recovery demands are both sorts of BIG DATA.BIG DATA. Why are they called as BIG DATA? Why aren t they called as LARGE DATA.? There are several misunderstandings in this discussion. Please look at the next chart. There is a phrase called 4Vs of BIG DATA. If the data volume is only the discussion, the solution must be so simple. How to store the large data and how fast we can handle those will be the main issues. These issues are depending on the resources of computer hardware and communication systems. If it is correct, computer hardware and some communication recourses are sufficient, we can simplify the city problems and disaster recovery status aggregation. On the other hand some people areas especially in Japan have confusion in using the word Big data and analysis. Recently I see many people are explaining about analysis as big data. We have the transaction data of the sales orders as big data so this is the monthly summery of the orders by product. as you know well this is just a summarized data analysis. The problem of the BIGDATA is that it is BIG. Big is different from Large. The word Big contains some meanings of uncontrollable or unknown. When you see a big person not a tall person nor large person sometimes we call a great entrepreneur a big man even if he is not tall. BIGDATA 4V shows that difference clearly. The volume of the data is a clear characteristic of BIGDATA as everyone can imagine. Before the IOT, most of the data were coming through controlled resources like corporate computer systems or some limited machines which were totally recognized. After IOT on the internet that are widely used, uncountable number of machines are connected to the internet and keep on putting data in. The machines started to send and receive data automatically. Now they make their own decision and forward data by themselves. When some bank transaction happens to you like a person sent a lot of money to you the bank automatically sends the information to you on line. It is sometimes misunderstood that this is IOT process. The real IOT is this. The huge amount of the physical transaction data from the ATM machine will be aggregated by the central computer on secured leased lines. Simultaneously data from security cameras and the doors which are not the direct bank transaction related information will be sent forwarded stored and circulated on the secured leased lines on internet like VPN under some conditions that were originally set by human beings but judged on each transaction by systems automatically. So the volume of the data has kept increasing much more than sky rocking In long time history of computer systems, most of data used to be text. Very little handwritten or image data existed for long time only to store for referring purpose mainly not to analyze as data in the green screen times.. Now those IOTs, machines like video cameras send and receive images and movies but very few human beings keep on checking them. Variety of data has become the important element of the BIGDATA. Images, handwritten, texts, many languages, sound designs, charts and so many data are running around the world now. Now do you know that most of the stocks are dealt by computer programs. They, computer programs are using and analyzing vast number of data to refer. They keep watching the movement of currency market, weather report and some agriculture markets to decide the actions toward the deal. It is really impossible even for them to store all of those data to analyze. The way they do is the streaming 3

4 computing. Streaming computing is a name of the technique to abandon useless data in speed. They need to put the priority on each data and store them or throw most of them away. This is the BIGDATA velocity. That is why technology for clarifying or prioritizing data is the important element of BIG DATA. Data that can be used by human beings must be small. If someone gives me a book with thousands of page written in 100 languages by chapter if someone asked me to summarize it in one minute it is impossible to do. So I will be ask him to focus on a subject in the book and to narrow the areas or languages that are more useful. It is the same for computers. Only the difference is their units. Thousands of book page of the book may be trillion of pages for the computers. So prioritize and sense the velocity are the key factor if this. Big data is data that requires this activity so seriously. The last V is Veracity. Before, the data typed into system used to be controlled by human beings. They were already checked and secured at the time. Now any data can be jumped in. Any data jumped in could be used as a data freely now. There are so many wrong, half processed, malicious data with trustable data combined. The element of BIGDATA so called the Veracity did not exist before. Smart city projects use data for people. If the data was wrong, the project and the activities will be dangerous to citizens. The technique to clarify data precisely and correctly must be needed in BIGDATA handling. This is obviously different from just a large data and a analysis.. and quickly the information is handled. On the right hand side there is a word ANALYSIS. Analyzing the data is the very important tool for the business executing group. For them data is not what they finally need to keep. In order to execute or do something they need to analyze data. Beside data they have practical things to do. This is one of a chart that was proposed to the city Government of New Orleans. Considering the right hand side group is the group that is always facing to issues of citizens like police registration fire department and city hall. Data analyzed by them is not only just digital signals but important information. For a Government like this New Orleans after the severe disaster Katrina many urgent voices that are coming through the right hand side groups were urgent problems to solve. The left hand side group should gather data from many different external sources including broken injured people or damaged roads through IT systems. If that data passed to the middle for integration the right side hand group can exchange them from data to I formation to help people. When these two types of information are combined and integrated the Government can start its data oriented operation in another word city operation based on BIG DATA. This is the information supply chain. Please look at the left part on chart. Data should be managed. When the role of the information system division is to manage the data which is gathered from IT systems their mission is how securely correctly It was September years after Hurricane Katrina hit the town. 6 members were assigned to help the Mayor of New Orleans.Due to 3 meter deep water that was lasting and pressing on the ground for 9 months there still were thousands of potholes on the road and many damaged under ground pipes of water and gas. 4

5 We thought we would be able to help from some IT solutions to get the city operation smoother. From some operational function viewpoints we thought we would propose some super software to this city because it had been already 6 years. But the fact was so different. Over employees of the New Orleans city hall went away from the city after the disaster but people have come back. The point is that most of the gone employees never came back but many new employees from all over the states came back without any experiences of internal communication and collaboration as one organization. As a result the communication between divisions didn t work well. Over 180 small IT servers are operated by each division. Paper printed excel data were oftenly passed to the next division and typed all again into the system which is owned by next division. It was taking 18 MONTHS to complete the annual report every year Of course the integrated data didn t exist so it was impossible for the city hall to show any effective data to citizens This cartoon is inserted into our proposal report and claimed to the Mayor after our analysis. It says that the data integration is the most important thing to go on the city operations. We said that they need to talk before that. This chart looks adorable and colorful but contains very severe messages. For instance during our making process there was such a debate. You cannot see any crisscross on the church. There were many different religions in Christianity there. So one group complained me to take it off. They said that not all the churches have it. We knew that each individual religional church kept a community and made citizens have kept up I erased that immediately. As many African Americans were kidnapped from many countries in Africa 200 years ago. There were many different races in African American then and now there still be the same in this town. Not only the race discrimination but the variety of races with religions makes things difficult. I hope that integrated big data contribute integrated human relationships by effective management and analysis even if the problem is complicated. I was also helping many cities of Tohoku in Japan after the Great earth quake in This is very touchy subject but I really saw how those difficulties have grown as same as New Orleans after the disaster in this country. After one side of a certain town was chiefly washed away by tsunami people would try living on the other higher side. The prices of the higher land and the real estate got higher. People lived in the damaged side were forced to live in the temporary houses. People lived on the higher hill started to sell the expanded property with higher prices than before. Under this circumstances of difference people started to clarify people by their original town names. This types of difficulty cannot be taken away. BIGDATA cannot do anything for that but the city hall must have been able to do something earlier before this happens. In the beginning of this report I showed the foci and the categorization of smart city. As I mentioned smart city doesn t only mean the city with skyscrapers like Singapore or Shanghai. Smart points out how people can live smarter than before. Whichever the data or big data comes up to discussion any data of smart city should be used to make people smarter. I have been working on the smart city projects with IT systems. I am always thinking of the balanced collaboration between data and human management. This balanced operation is truly the core of smart city. In many hundred years ago even without any computer system there surely was data among people. One big difference between now and then is its characteristics with 4Vs. From positive way 5

6 of thinking 4Vs says large fast correct variety data can be reached the right places. You all can use and utilize that huge information for better life. The possibility of its misunderstandings among human beings causing difficulties and disasters may be lowered by BIGDATA. Hisakazu Okamura Professor from 2016 Council member of faculty of Urban innovation Asia university establishment. Vice president of Dengen Solution Co. ltd.. 6