According to the source of "wisdom", smart cities can be divided into two categories.
First, large-scale installation of digital equipment in cities.
Including monitoring equipment, digital traffic facilities and signs, real-time communication equipment, etc. Through the collection, integration and analysis of these data streams, the city operation can be monitored and managed in real time, and these analysis information can also be sent to the mobile devices of urban residents (such as computers, mobile phones, GPS devices, etc.). ) real-time, providing more convenient information for the daily activities of urban residents. Through storage and further analysis, these real-time data can be used to describe, simulate and predict the urban operation characteristics and future development, thus providing reference for the further development of smart cities. In addition, the large-scale application and development of digital technology can also stimulate the development of local related industries, especially the development of regional service industry and knowledge-based economy.
The second is to develop knowledge economy in a certain region.
From this perspective, a smart city is an economy led by smart people and driven by reform, innovation and enterprises. In this system, information and communication technology (information and communication)
Technology (ICT) is the driving force to realize innovative concepts and designs on this regional development platform. However, as far as information and communication technology is concerned, simply nesting in the urban system cannot transform the city into a smart city. It is necessary to combine human and social resources with a more relaxed and open economy to promote the intelligent development of cities. The concept of smart city was originally located in the perspective of technology and technology management. However, with the continuous improvement of the concept of smart city, social capital, education, economy and other aspects are getting closer and closer to the perfection of the concept of comprehensive smart city.
At present, the development of network infrastructure provides a foundation for urban scientific and technological innovation, and also promotes the economic, cultural and environmental development of regional cities.
Smart City Development under the Guidance of Big Data
Big data should play a role in four aspects in smart cities: scientific planning, the application of big data in data support, public participation, social supervision and objective evaluation, so that all aspects of urban planning have a more reasonable basis; Real-time monitoring, digital, networked and intelligent development can ensure that any degree of operation of this city is in the hands of radio stations; Accurate governance, including accurate information, intelligent solutions, rapid impact and performance evaluation; Efficient service, providing convenient, accurate and fast service for the public.
Characteristics of Big Data in Smart Cities
(1) data volume
The amount of data in the concept of big data refers to a large number of arbitrary types of data generated from various data sources. Under the framework of smart cities, multimedia/social media and other types of networks show geometric growth in data generation.
Even modern industrial products, such as cars, trains, power stations and so on. With the improvement of intelligence, more and more sensors are equipped, and these sensors continue to collect more and more data. The increasing amount of data brings new challenges to data collection and data analysis.
(2) Data speed
Speed in the concept of big data refers to the speed of data generation and transmission. Under the framework of smart cities, the content of data is constantly changing due to the increasing amount of data and data sources and the constant change of data types. For a certain data storage, the speed of data generation and transmission determines the speed of data content change. Data users often have faster data generation and transmission speed, so that they can know the real-time information they care about. Therefore, the speed characteristics of big data put forward higher requirements for data processing methods and algorithms.
(3) data diversity
Data diversity in the concept of big data refers to the diversity of data types, such as video data, audio data, image data, text data, data logs and so on. The diversity of data types is closely related to the diversity of data sources, such as mobile phones, video recorders, sensors and social platforms. Compared with traditional structured data (such as financial data, futures trading records, personnel information, etc.), under the framework of smart cities, the data in the concept of big data includes a large number of complex unstructured data, and there is no fixed data format. Similar to data speed, the diversity of big data also promotes the further development and optimization of data processing methods and algorithms.
(4) Data value
The data value in the concept of big data means that big data contains valuable information, which can provide useful reference for corresponding decision-making. The realization of data value requires big data analysis, which is the process of extracting valuable data information from big data. Under the framework of smart cities, data value assessment is the most important feature of all applications based on big data, precisely because data value assessment can generate the information needed by data users.
(5) data accuracy
Data accuracy in the concept of big data refers to the integrity and accuracy of information contained in big data. Data accuracy is a description of the quality and credibility of big data. The core content of any information management practice is data quality, data control, metadata management and the requirements for data confidentiality and legality. Accurate raw data is helpful to analyze and mine accurate data information, thus providing more accurate reference for corresponding decision-making.
Under the framework of big data, due to the diversity of data types, only collected and stored data cannot be used for efficient and accurate data analysis. Moreover, large-scale data analysis depends on the high-speed automatic operation of computer algorithms. Therefore, data integration has become a necessary step in big data analysis. Data integration means integrating it into an integrated database according to the research needs and the differences of different types of data. The integrated database should have the following characteristics: the differences in data structure and expression form in the original data should be kept in the integrated database, and these differences can be used for high-speed analysis of computer algorithm reading and big data analysis, thus ensuring the algorithmic solvability of the integrated data.
In addition, under the concept of big data, even the analysis of single data, reasonable data integration and database design are very necessary. The specific details of database design are determined by the particularity of research content and research methods. For a specific research content or method, a certain data integration method is often more advantageous than other methods. Therefore, it is necessary to consider the modifiability of the database when designing it, so that it can be modified when using it in other research, thus enhancing its practicability.
Practical experience of smart cities and big data
From the perspective of national policies, the overall technical framework of the planning smart city project in China and the first phase of the planning smart city project supported by the Ministry of Science and Technology put forward a six-horizontal and two-vertical smart city technical framework. The bottom layer of the six horizontal layers is the city perception layer, then the transport layer, the top layer is the processing layer, the support service layer and the application service layer, and the top layer is the smart application layer. Safety system and standards and evaluation run through the whole situation. To truly realize a smart city, big data technology must be introduced, mainly including the following three types.
1, big data fusion technology
One of the major challenges faced by China's smart city construction is that the urban system cannot be effectively integrated to form an information island. Therefore, in the field of big data integration, on the one hand, we should strengthen the research and development of key technologies such as modeling and integration of massive heterogeneous data, storage and indexing of massive heterogeneous data columns, and provide standards and technical support for information integration of underlying data.
2. Big data processing technology
In the process of smart city system, considering the transmission efficiency, data quality and security, it is necessary to preprocess large-scale data. Big data processing technology often needs to be combined with parallel distributed technology based on cloud computing, which is also a widely used technical solution in the international industry.
3. Big data analysis and mining technology
Compared with big data fusion processing technology, big data analysis and mining technology is more complex, which is a very challenging technical problem faced by international academic and industrial circles.
Typical cases of smart cities at home and abroad
United States: Dubuque has beautiful scenery, and the Mississippi River runs through the city. It is one of the most livable cities in America. With the goal of building a smart city, Dubuc plans to use the Internet of Things technology to digitize and connect all resources of the city (including water, electricity, oil, gas, transportation, public services, etc.). ), monitor, analyze and integrate all kinds of data, so as to respond to the needs of citizens intelligently, reduce urban energy consumption and cost, and make Dubuc more suitable for residential and commercial development.
Spain: The sensor project makes the construction of smart cities completely based on practice. According to Mariano Lamarca, head of sensor project of Barcelona Communication Institute, smart city is one of the most important projects in Barcelona at present, and Barcelona's former textile industry zone is now the most important testing ground for this project.
EU: Propose and start to implement a series of smart city construction goals. The EU's evaluation criteria for smart cities include smart economy, smart environment, smart governance, smart mobility, smart residence and smart people.
South Korea: To promote the intelligentization of government administrative services, South Korea is building a green, digital and seamlessly connected eco-smart city based on the network.
Beijing, China: Beijing's smart city construction is guided by the strategy of "People's Beijing, Science and Technology Beijing, Green Beijing" and combined with the city positioning of "National Capital, International City, Cultural City and Livable City". In the construction of smart cities, give full play to the advantages of modern science and technology and establish a people-oriented management concept. The construction of smart cities in Beijing is comprehensive and systematic.
Smart city is the next stage of urbanization, the new height of urban informatization and the prospect of modern city development. Wireless city, digital city, safe city and perceived city are necessary conditions for smart city. Honest city, green city, healthy city and humanistic city are the proper meanings of smart city; Smart cities generate big data, which in turn supports smart cities. The combination of smart city and big data will surely have a bright future.