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China big data expert committee consultant, Chinese Academy of Sciences Academician Li Wei: big data city intelligent transformation

Published in14:51 2015-06-03| Time reading| sourceCSDN| ZeroArticle comments| authorWei Wei

Abstract:In China Cloud Computing Conference keynote session, China big data expert advisory committee, Chinese Academy of Sciences Academician Li published "city big data intelligent transformation" theme of the speech, he said difference between smart city icity and digital city dCity mark icity is a complex ecological system.

[CSDN] 3-5, June 2015, as the most influential event in the field of cloud computing:The seventh China Cloud Computing ConferenceGrand opening at the National Convention center. Conference to promote the cloud computing innovation and development, cultivate the new format in the information industry "as the theme, inherited the former sixth successful experience, more than 100 domestic and foreign cloud computing core and experts in the field of wonderful speech, focusing on ecological system present situation and the trend of development, exchange of experience, further pushing technology innovation and application.

In China Cloud Computing of the afternoon session keynote session, China big data expert advisory committee, Chinese Academy of Sciences Academician Li published the data the city's intelligent transformation of the keynote speech, he said is icity is a complex ecological system. It provides the following three iconic service, query depth, law discovery and decision making smart City icity and digital city dCity mark difference between. Then he explained the three signs. In addition, he believes that to complete the city's intelligent transformation, the need for hardware and software aspects of support, including the original data of the unified unstructured data model, and finally he also introduced a group of software engineering.

China big data expert committee, Chinese Academy of Sciences Academician Li Wei

The following is the speech record:

Distinguished experts, ladies and gentlemen, good afternoon, I report this afternoon, the topic is "the city of big data intelligent transformation". To enter the ten second years in twenty-first Century, to achieve industrial information, agricultural modernization and urbanization has become a new development of the socialist construction of China's strategic needs and the current urgent task. So the three aspects of the intersection and integration and development so we must to information as a guide, to build a new town as the starting point to the successful completion of the. In the past ten years, the city of information technology city wisdom city and so on these have become a topic of academic circles and the media hot topic. In fact, any industry or a region of the information process, can be divided into two stages. The first stage is the digital stage, which includes the information of the sensor, storage, calculation, transmission and control of the network and digital. The second stage is intelligent, that is, it is a higher stage of digitization. So this digital city I think now we have a more unified opinion, what is the digital city? Is if the city to maximize the use of digital and sensing technology, network technology and computing technology of information infrastructure and in the cloud computing software environment and on the data of urban population, resource, environment, economy and society to be computing and processing, to reflect the urban society a variety of large data effectively integrate for planning, forecasting, operations and the monitoring and management of city, to improve the management of government departments and decision-making ability, improve the quality of life of urban residents, this is if you do this. That is to achieve a digital city. For example, some of the major regions of developed countries in Europe and the United States, as well as new countries, including China's developed regions and cities should be said to have basically achieved the goal of digital.

From the digital to the urbanization of this intelligent transformation, which tasks should be included? I think it's smart city,The distinction between the city's intelligence and digital signature is three:The first is that the smart city is a complex information ecosystem, it should provide three kinds of subordinate subordinate service,Depth inquiry, law discovery, decision making, which is equivalent to the intelligent discovery of knowledge, the use of knowledge, and then the transformation of society which are included in the law of intelligent query discovery and decision making inside.

Now I want one of them to talk about what they should be.

Then from the big data processing point of view, the difference between smart city and digital city, I think that the smart city to establish a unified model for unstructured data. This moment, I want to talk about this issue, third from the perspective of software development, is the smart city to use the software group software development methods.

First, what is called the depth of inquiry?For example, now let us to or Google, baidu or, enter a message: "I often have a headache nausea, sometimes vomiting, can't see things clearly, occasionally appear tinnitus, I should how to do, I want to solve these problems in my current. I this is the Google answer, I used 0.54 seconds to find out the 42900 with you this number of pages please look at one by one, the first three are my here three. This is the data query, data query and our intelligent query where it is different? Data query you are from the 42900 pages of these things to find.

So-called intelligent depth query, like people, we went to the hospital and see a doctor. He was one of the first to guide medical service, with you first check your judgement is what disease, machine if the intelligence should be how? The first step of the machine answer according to input your things, you may have under the four possible, first called cervical spondylosis, I this morning did not attend the meeting is to see cervical spondylosis may also brain tumor, may also be Meniere's syndrome, may also be a cold. Doctor is a picture to give something to a preliminary diagnosis, next computer, assuming I choose a brain tumor. Then the computer should give you the depth of a query the so-called knowledge exchange should give you an answer with three kinds of treatment programs. Three sets of programs, the first set of the program is available to you for the establishment of tumor hospital, the second is related to tumor doctor according to now according to ranking the list to you you can easily pick, or according to the symptoms you now you can take what kind of medicine, give you, for the user to choose. If I choose to be in a hospital, and I chose the brain tumor hospital; Chinese Academy of medical science, it will answer brain tumor hospital, Chinese Academy of Sciences, it can answer you all the necessary knowledge, for example, registration, online registration should I pay attention to what matters how registration. The second kind of medicine fee you can also refer to the tumor need how many money, if the field how to facilitate inquiries. Such a query is the depth of the query, with the previous query is no different, it is not the exchange of information, but the knowledge exchange, you find the knowledge. To achieve such a depth of query, in fact, use first said we input the nausea and headaches, which is called using the method is inductive guess, inductive reasoning, we from a symptom defined you a property is a brain tumor or Meniere's disease.

Then you choose a brain tumor, your choice is in fact related discussion. Originally, we choose tumor hospital and drug are different individuals, storage in different places, because they have common symptoms have in common, so the computer to they are singled out to supply you choose, but once the brain tumor, Sun Yat sen University or tumor hospital, I to you, it is logical reasoning.

The other is the Chinese Medical Hospital tumor hospital registration procedures, the road map, medical expenses, these raw data is equal to the link between each individual and the entity and the original data, the connection.

Depth inquiry is a kind of knowledge exchange which provides knowledge and not a web page.This system from the description of the phenomenon of the accident or initial symptoms, by way of human-computer interaction, the system provides with the phenomenon or symptoms related to all can for the selection of concepts and entities in the user to make a selection system to find associated with ontology and associated knowledge map, and depth of user knowledge interaction, logic and reasoning, induction, to change the status quo of key calculus all probably online and related solutions and knowledge. This is the knowledge level communication. This is intelligence, this is a kind of intelligence, is our knowledge of the exchange. For example, we recently discussed the test Turing, is a kind of special depth of inquiry, this is the first kind should have the depth of the query function, this is the first point I said.

To build such a depth of inquiry, what do we need to do? We need to be the best in terms of the original data is a unified tetrahedral, there is a unified data model, this time I have to say. In addition to the computer there should be a lot of ontology, entities, knowledge map, ontology, ontology knowledge map similar entities of the original data connection, including reasoning mechanisms should be provided in the software. This is what I said the first intelligent applications, intelligent transformation of the first application.

The second is calledLaw discovery.You may previously learned logic or scientific interest found the feeling, as we all know, whether classical logical data or Karl Popper's scientific discovery logic atomic statements are indivisible objects in these languages. Scientific knowledge is a formal language called first-order language, first-order language consists of atomic sentences and compound statements, compound statement is the logical structure of the language and an atomic statement is the starting point, including the relationship between concept and quantity, this is the equation. In fact the concept and the equation between them, these things are the core of every scientific theory, and the rest of the logic can be calculated through the. Atomic statement this stuff inside the logic is not study, the past is by scientists through the eyes, ears, nose, tongue and throat decided, now is through large data, high data how the data how concept extraction, how to extract the equation between concepts, which became the all modern search, a lot of research in this area. Any such features from the sensor directly to the data and then produce a relationship between the things we call the law found that if there is a aspect of this is intelligent applications. For example, for example, in fact, we see all the history from Aristotle to until now scientists, such as Newton, Newton's most important contribution is the mechanical, mechanics in the core of what is it? Newton found these, the first basic concept, force, mass and acceleration, in particular, the force and quality of ancient Greece, the acceleration is the real Newton found. This is to propose a concept, the concept of the relationship between the number of what is it? Is f force equals mass multiplied by acceleration, these things are called atomic statement again from the point of view of logic, on an atomic statement found experts in the past from the eyes, ears, nose, tongue and body feeling, now is the people through the analysis to find these concepts, at the same time, to find the quantitative relationship between these concepts, all of the following things are the five aspects can be solved.

So,Law found the precise relationship between is system through the description of things related to the data statistical analysis and calculation, the essence of atomic concepts are extracted by means of man-machine interactive mode, and is given in the form of a mathematical equation with the things related concepts.This part is the discovery of knowledge.

What is decision making?Here I cite an example, for example Beijing Tiantongyuan area 8 square kilometers are now a total of 91.5 million people, the main city road has two, a is inspected to G6 and bypass to Beijing, the second route is from Li Tang Road to Anritsu road into the city, now is the early peak traffic number 14 million people, so every day overload safety comfort is poor, traffic congestion on the road for a long time, the root of the problem where is it? Assuming that if each car by 70 people, the average of 9 in the morning to send 10 buses per minute, then, to 2000 times the car, this car 40 kilometers in order to transport people out, so this is a problem every day. Now if we want to give Baidu input this information, enable traffic jam I to seek solutions, then it is also within a few seconds replied me here a total of 124 page for your reference, specific to say I live today added today I wish 7 points to work 8 to class uplink no, the traffic situation how, can't give you the answer, the intelligent will become what?

I say first big data, now we in Beijing, this also is a digital city, after data analysis found that residents of the card this 14 million people are some, residents can get around the main roads from the city has 38 regions now have points out who in what place, but in fact only nine area is their main purpose is to focus on the 83% of the population, this is now the big data calculation.

We hope that the smart and transition to what the situation? That is the way it should be, it should be is man-machine interactive, for example I input is added to the solution to traffic jams, the first computer to answer you operate from a strategically advantageous position, you are looking for solutions for today or long-term solution? Of course I choose today's program, how do I do today. The computer should then told me that you choose there are several ways to solve, you want to optimize bus scheduling or hot regional direct way or optimization routine arrangement and the bypass road arrangement way. For example, I choose not only to the public transport scheduling and short-term program, when I am right? According to the computer the wishes of the individual I today the best travel time and working hours, to promote the personal, you put your suggestion is sent to me and at the same time at the same time and was sent to my boss, told my leadership today I work an hour late, knock off an hour late, which can not buckle commuter. This is the solution of artificial intelligence. Intelligent solutions include actually through man-machine interaction, keep the whole problem to clarify what kind of question is, for example, for a very simple example, suppose a bus load is P order, departure city is Y order, then P multiplied by Y order, more than X, and so on into the conditions of digital description this condition, we finally find the total transportation amount, the maximal value of Y order P factorial, this is the whole optimization problem, the other becomes the boundary conditions and mission conditions, these are the input of human-computer interaction into account, and then continue to ask you to solve what method, dynamic or static all kinds of algorithms, there is a complete algorithm for all selected database on the Internet, but also experts selected.

So in general,Decision making is for the user's request, by way of human-computer interaction of ontology, the concept of entity attribute multi-level inductive guess, logic key operation, provide and the types of decisions, you are seeking the maximal value and minimal value.The results after according to the mathematical model of the problem and according to the man-machine interaction to initial conditions is given, finally according to equation according to the user to provide group statistical rules and population dynamics of the evolution process and according to the population of each individual are required for individual solutions. Not only is we find a statistical rules would be finished, the ultimate goal is to each person of every individual solutions, achieve group optimization, which is not only just discovered knowledge, use knowledge and to solve the problem of high intelligence. So I think this is a smart transition if you can have these three functions, the depth of the query, the rules of discovery and decision making, then we can say that we have completed the digital city of intelligent transformation.

What needs to be done in terms of hardware and software? The first is a very important issue is the need of the original data semantics of non structured data model.Is the city of big data is carrying knowledge and information entities, through a variety of digital and sensor from every corner of the city and people from different areas of knowledge, they can be structured data, past the original data, can also be non structured data, such as voice, image, video and so on, from to do not have a unified format, and even the same time version is not uniform, greatly increased the difficulty of data processing efficiency, so the need for a unified model, I think this is very important. I don't talk about it in detail, this model should have a unified and related scalability.

In addition, I would like to give you guys talk about a group of software, is a software engineering approach is not the same as the traditional. The city is a complex social ecological system, the basic characteristics of the composition and evolution is the macro is institution of municipal management of urban macro planning and on the allocation of urban resources compares regulation, micro is competition and market mechanism for allocation of resources city and urban development decisive role. This is our city is like this. Groups of software engineering and intelligent city is a complex information ecosystem, it has in its every time the data are under social ecological system of digital mapping, is a municipal institution of urban macro regulation and market mechanism of city resources allocation and the development of decision a qualitative description.

This kind of thing how to develop? Can you please Microsoft to develop a smart Beijing OK? Now a little bit of a problem. Why? I explained to you, the traditional software is the definition of the method of elite, Google or Microsoft, are famous brand university outstanding students, professional backbone. Second is the plan, the entire development process is closed, to ensure the development of security. This advantage is the high quality of the program, the history has proved that as long as there is no malicious attacks, like Microsoft, we all day angels, very good use of a software system.

Why does it not work? What are the disadvantages of it? Is that we look at the development of Microsoft's workload, I cite the Vista Windows. Now smart cities, Beijing intelligent, according to the classification of national economic industries standard a total of 20 categories, 20 categories of our country have 100 a large class of 400 comprehensive class a thousand small class, we usually say a industry probably equivalent to a comprehensive class, then our country now is not the 360 lines, but 400 industries. If we have chosen a 10 million urban population, such as Hangzhou, Suzhou like this in large cities, assuming that his number is 320 industry, each industry is a thousand different services, a variety of services, each industry eyebrow a pick service code hypothesis is 8000 lines of code of the total is? Is the line. Just say that Microsoft is that how many lines? Microsoft is 6000 million lines, so the 2.56 billion, to use a Microsoft to stem requires 213 years, 20 Microsoft to do also need 10 years time obviously, it is impossible to have, now, a total of only a few companies such as Microsoft, so this is the realization of intelligent city research and common system of fundamental difference here. Is there any way? Is also a way of. This approach is the emergence of Appstore in 2008 we have learned, in addition to the Google Andrews Market, such as Appstore from 2008 to 2013 5 years 1 million 300 thousand people completed 2 billion 600 million lines, 5 years to complete. So to combine these two methods, combined, so we put forward the idea of a group of software engineering, this is what? Is the ladder structure is a new structure. This structure is hierarchical and modular architecture, longitudinally divided into layers, horizontal is composed of several modules. Relations between the each layer decision under the function of a module and the layer of each block module and the lower interface, each layer of the software to achieve, including design documentation, development module code, test program is through the market, like the Appstore, through market competition, won the bid to realize. Approach to building is each layer is he under a layer of market competition for the development and successful organizers, competitive rut formulation and market supervisor, then the entire in order to ensure the security of software, if a user is to take part in this layer in the layer, he knew this thing is in trouble, so to ensure the security software to implement temporary partition layers, vertical planning software, transverse crowdsourcing complete implementation, complete the software code and test development, which is we called a smart cities group software development method. Only with this approach to mobilize 700 thousand users, we can put the 400 industry's ten million cities in the smart city built in 5 years, I said here today, thank you.

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