In the era of big data and artificial intelligence, cities are gradually having a "unified logic". How will the industrial ecology be transformed into intelligence, how will urban business scenarios and services be upgraded, and what impact will it have on the government governance model? With the technical construction period of batch after batch of smart city PPP projects, it has entered the operation period. It is foreseeable that in the coming 2020, more smart city construction and operations will begin to publish transcripts, centering on the legal system, data production and transactions, data off-warehouse (central warehouse) on-chain (blockchain), three-dimensional real-scene city update of the CIM base of the urban information model, and around the integrated development of BIM building information model, 5G, Internet of Things IoT, spatial computing and analysis GSD, augmented reality AR, location intelligence LI, and artificial intelligence AI. Smart city construction will usher in a new era of smart cities. If we say that the era of Smart City 1.0 is defined as China’s first proposal to build a smart city to the country’s promulgation of new smart city construction evaluation standards, the construction model of this era generally adopts the construction of cement + mouse information infrastructure as the main form. The establishment of new smart city construction standards and related norms in the country belongs to the era of smart city 2.0. And the next smart city 3.0 era is bound to have completed the growth stage of information construction, stepping into the development of smart city operation projects everywhere, ushering in substantive government operations, forming urban elements that are known, visualized, measurable, and controllable. A new world where everything works.
Cities have always been the embodiment of the highest achievement of human civilization. But the city has always been just a container for various technologies and products. The city itself was too complex to ever become a product. Now that we have the Internet, the Internet of Things, and artificial intelligence, everything in the city gradually has a unified logic, and it even becomes possible to work together. This logic is called "data". After all, the essence of the world is not matter, but data. Even the inheritance of human beings is essentially the encoding of data. The city evolves under the logic of data, and will eventually become a product that can be manufactured and operated by an enterprise. Such an enterprise will also have astonishing energy and vitality, beyond all our imaginations. But this product is not a cookie-cutter assembly line, let alone a predictable planned economy, but a highly free and changeable life form. The real creators and masters of the city must be the citizens. The result of technology being omnipotent is that it is ubiquitous, but it is colorless and formless. This future is already happening, "Google has its spirit, Ali has its meaning, China Fortune Land Development has its shape, Tencent has its blood, Vanke has its bones, Huawei has its tendons...". Google's smart city vision is through Sidewalk Implemented by Labs. In the waterfront area of Toronto, it only announced a planning design and built an exhibition hall. It has become a new leader in the construction of smart cities in the world, and major cities in North America have initiated project invitations to it. But behind this, on the one hand, is its huge investment layout in the field of smart city industry. Relying on a story and a demonstration, it has driven the huge global orders of its investment companies; on the other hand, the Toronto waterfront plan has indeed demonstrated its perfect understanding of the urban system and the entire process of planning, construction, operation and management. From the planned spatial structure, to the construction system, to the operable infrastructure system, to the data-driven refined management methods, it can truly achieve continuous benefits relying on data operations. Simultaneous development of industrial investment and urban operation, including the consideration of citizen participation, ecology, and fairness, can be called a classic. It has all the spiritual connotations of smart cities, so it has its "god". Ali, from selling "goods" to selling "cloud", although AWS set an example first, it is still a very powerful operation. Online, especially e-commerce traffic will inevitably dry up, and competition for offline entrances is almost the entire future of the Internet. Alibaba Cloud has joined forces with first-line security manufacturer Uniview Technology and first-line transportation manufacturer Qianfang Technology to form a capital consortium. Relying on the story of a signal light timing in the city brain, it has conquered cities and land all the way. Not to mention, it has become a national strategy. It can be purchased from a single source without bidding in intelligent transportation projects in provincial capital cities, catching traditional information integrators by surprise. In recent months, new positioning keywords such as new infrastructure and IoT platform have also seen its calmness and restraint. I believe that by telling the top-level story well, and then focusing on the middle and lower-level business, it will have a good business performance on both the G-side and the B-side. However, Ali still has the fatal flaws of traditional informatization integrators, that is, the ability to solve urban problems is insufficient, and the scenes that can tell stories are too poor, so it is easy to immerse in the comfort zone of traditional government informatization. The strategic cooperation with China Fortune Land Development just now is an excellent move. It may obtain multiple urban scenes that can be practiced and realize the joint development of "Ali Department". Tencent, as one of the two major Internet giants in China, cannot fail to pay attention to this huge market, but it has not found an entry point to intervene in a high-profile manner. In fact, in the core technical fields of smart cities such as the Internet of Things, smart home, driverless driving, shared travel, maps, and artificial intelligence, Tencent's defensive layout is already a big game of chess. Relying on the WeChat portal, Tencent has obvious advantages in urban services, and it is also penetrating the community market; through the construction of its own Binhai Science and Technology Building smart building platform, it also has With the "Weilling" intelligent building platform, it already has the prototype capability of the future smart city operating system. But the most important point is its ability to connect with "people". From people to people, to people to things, to things to things, and finally connect everything. Citizens and their needs are the core of a smart city, and the entrance closest to "people" is of infinite value. Of course, as more and more urban scenes and offline entrances are opened one after another, whether the advantages of the social side can continue is not a small challenge. For Tencent, it is possible for Tencent to continue to become Ali's number one rival by taking Weiling's productization as a breakthrough and comprehensively deploying an urban IoT platform. The value of the word "connection" is no less than the "blood" of a person. China Fortune Land Development, known as the operator of a new industrial city, has two core skills, building industries and building cities. It is difficult to find a second company in the world that can understand these two things at the same time, and can independently complete the planning, construction, operation and management of the city. In this regard, it is almost the only irreplaceable among the above-mentioned companies, and it controls almost all urban scenarios including residential and commercial, covering infrastructure and public services. In terms of industry, it is very good at attracting investment for the government, and it also works as an incubator to invest in the early stage. More importantly, like Google, the boss has also invested in many smart city-related industries, such as driverless driving, shared travel, new energy vehicles, infrastructure, ecological restoration... It is only one step away from a perfect smart city operator. In fact, the only thing missing may be the Sidewalk A story like that in Toronto. Vanke, as the No. 1 real estate developer in the universe in various senses, is also leading the trend of renaming and changing industries in the real estate industry on the cusp of deleveraging. Shenzhen Vanke Real Estate Co., Ltd. has just changed its name to Shenzhen Vanke Development Co., Ltd., and has further iteratively upgraded its positioning to an "urban and rural construction and life service provider". On the basis of consolidating the inherent advantages of residential development and property services, its business has extended to commercial development and operation, logistics and warehousing services, rental housing, industrial towns, ice and snow vacations, elderly care, education and other fields. These asset-heavy operations are tiring and slow to make money. Therefore, it should be its real intention to transform into a more high-end technology enterprise image and develop towards the advanced stage of urban operation, that is, data operation. Although it is not easy to evaluate how Vanke is doing in terms of operations, but in terms of construction, Vanke's technical reserves should be the undisputed leader in the industry. Over the past many years, Vanke has been walking alone, leading the way of housing industrialization with prefabricated housing as the core. In the future city, the flexible space system supported by the elastic construction system is the premise to realize the characteristics of space sharing, functional mixing, and light structure. Only in this way can the data-driven construction process be realized and the space can be operated. Sidewalk is because Google invested in the modular construction company Factory OS has the confidence to enter the construction industry, similar to Katerra, which has received a huge investment from Softbank. Therefore, Vanke has the opportunity to build technology in the future, which is the physical and spatial skeleton of the city, so it is called its "bone". The overall insensitivity to information technology is the flaw in the transformation of Vanke and all real estate companies. In the cooperation with IT companies, the inability to communicate in the discourse system may be the biggest obstacle. Huawei, as a traditional telecom equipment manufacturer and system integrator known for its technical strength, has always been a low-key but non-negligible force in the smart city market. From the cloud to the end, every link of the entire IoT data link is inseparable from Huawei's equipment and products. Terminals, chips, 5G, LoRa, NB-IoT... all have the ability to determine the direction of market technology. Its 2012 laboratory focuses on disruptive black technology, and it has been deeply involved in basic research earlier than Alibaba Dharma Academy. Its goal is to "build a smart world with everything connected." Whether Huawei can achieve it is hard to say, but without Huawei, it seems that no one can do it. In the Internet era, Huawei relies entirely on its technical strength to maintain its presence, but the lack of Internet and operational genes has seriously affected its future market position. Huawei should have seen this problem, so it set up a scenario laboratory to deepen the needs of real-world scenarios. In the construction of smart cities, data links are the basis of digital twins. If the real building structure is the "bones", then the virtual network architecture is the "ribs". If Huawei can cooperate with suitable online and offline partners to "integrate the bones and muscles" and focus more on the application technology innovation required for urban operations, it can also use smart cities to complete the transition of enterprise form. At the 2019 Shenzhen Security Expo, you can see that Huawei is flying high in the Sino-US trade war, with "Kunpeng" and "Shengteng" as its two wings, and more than 40 leading ISVs in the country have launched various smart city scene solutions. Among them, the city information model CIM real-scene fusion technology platform jointly released with Jiadu Technology is eye-catching. It can be called the highlight of the 2019 Shenzhen Security Expo. In addition to the above, a new giant has recently entered the field of smart cities with a high profile. Ping An, as a company whose main business is finance and insurance, has 22,000 engineers and R&D personnel, far exceeding most technology giants; it has established a global leading edge in the fields of intelligent cognition, artificial intelligence, blockchain and cloud technology. Ping An of China is the second largest shareholder of real estate companies such as China Fortune Land Development, CIFI Real Estate, and Country Garden. It has also established equity cooperation with almost all first-tier developers, thus mastering a wealth of urban scenes. Funds, technology, and scenarios are all available, and it can be said that they are born invincible. If there is a company that will dominate this field in the future, it must have at least two of the genes mentioned above at the same time, and the city operation gene may be more difficult to obtain than the IT technology gene. Hard training of internal skills can certainly improve and achieve a certain degree of transformation, but genetic changes can easily hurt muscles and bones. Therefore, in the next stage, the level of vertical and horizontal integration basically determines the height that these enterprises can reach. Although almost two of these enterprises (domestic) have strategic cooperation agreements except for some direct competitors, in-depth cooperation that can really take advantage of each other has not yet emerged. The most basic model in the future is the combination of "technology + scene", so we have seen a lot of "Internet + real estate" strategic cooperation. However, because the field of vision of real estate companies is mostly limited to residences and communities, and they lack imagination for IT technology, there are no interesting innovative practices yet.
The overall digital transformation of cities, and even data-driven operations, as the general direction of smart cities, I believe there has been a consensus. But at present, we are still in the early stage of digital cities as a whole. The planning, construction, operation, and management of cities have not yet truly realized digitalization, let alone intelligentization. The thinking of IT companies relies on black technology research and development, faster speed, and more accurate algorithms to improve products, but in fact, the real intergenerational improvement depends on the change of thinking mode. It's as if we found that the soul of Apple's mobile phone may not be the touch screen and processor, but the interaction habits and the application store outside the mobile phone. For smart cities, this app store may be the mechanism for data operations, including the decision support platform and data laboratory we have been working on, which is the real focus of this story. Taking data as clues, we see that the planning, construction, operation, and management of cities are reorganized into a new gameplay. Driven by technologies such as the Internet, the Internet of Things, and artificial intelligence, various traditional industries and urban management have been endowed with new logic. Regardless of business operations or government management, digital transformation is not simply converting the original process to online, but redefining it with more interactive, shared, flexible, and refined models. In this process, each link will generate a large amount of data, which, like energy in traditional industries, will become a new driving force for industrial development, and will be connected with upstream and downstream industries through data. One of the most common industrial upgrading paradigms is to transform traditional urban public goods through technologies such as the Internet of Things and sensors, so that they have shared low-cost operation capabilities and can obtain continuous benefits in the operation process, such as shared bicycles. This operation-driven logic requires enterprises to have both product and operation capabilities, and to be able to implant operable technical elements in the product design stage. In the operation process, a large amount of data flow will be generated throughout the product life cycle, and the human-driven management method becomes data-driven. On the one hand, it can optimize product operation itself, reduce operating labor costs and overall costs, and use artificial intelligence to continuously improve product operation and maintenance efficiency and improve user experience; on the other hand, the data of various products and system operation and maintenance in the city are aggregated into the city data platform, intersecting and combining with each other, and can help optimize other systems; and the data of all systems comprehensively describe the operation of the city itself, and realize scientific planning and refined management of the city through the city-level decision support system. In general, from the traditional one-time sale or rental profit model, it will be transformed into two profit stages, one is product operation income, and the other is data operation income. The latter will become bigger and bigger and eventually surpass the former. Bike sharing is a very typical Type-specific products: Compared with traditional government public bicycles, the Internet of Things enables a single vehicle to be online in real time, accurately positioned, and controlled; users do not need to own the vehicle, they can obtain the right to use it at any time, and can find the vehicle through location services. After the trash can is completely full, request a maintenance operation through the IoT notification platform. From three inspections per day to on-demand cleaning for about ten days, the demand for cleaning personnel has been greatly reduced and labor costs have been saved. More importantly, garbage cleaning has become a data-driven process. If you are designing a set of automatic garbage collection vehicles based on unmanned driving, you can automatically collect garbage every night according to the route planning of the full bucket signal, making the entire garbage collection a complete data-driven closed loop. For the traditional Internet industry, the logic of the C-side and B-side is often relatively simple. For cities, however, multiple subjects are complex and values are fragmented. For the government and city operators, the costly hardware and software input should eventually lead to more efficient and low-cost governance, as well as more commercial value in the operation stage, but this is not something that software and hardware can directly achieve. To make the government managers who pay the bill experience the value of data, not just the sensory stimulation of the gorgeous big screen, this is not the height that can be achieved by pure software and hardware product development. To sum up, how to establish an industrial ecology with data as the main line, running through the whole process of planning, construction, operation, and management, and possessing comprehensive capabilities including top-level design, hardware, software, and data operations, is a question that every enterprise interested in smart city operations must think about. Technically, the integration of the data industry ecology may have the following key points: 1. Standard system. Even if it is a small field and product, its data will also involve subsequent docking and integration with other city data. In the top-level design and product design of smart cities, standards such as protocols, networking, data models, and security in different fields should be fully considered, and the data architecture should be fully flexible and variable. 2. Data-based industrial ecological connection. At present, there are many various application products and solutions on the market, but few of them can truly achieve a consistent data ecology, especially the value of data collected by the system, which is often ignored and abandoned. The government or large enterprises should take the lead in establishing data laboratories or similar data integration and application platforms, combined with government open data, revitalize the value of urban data, effectively connect the supply and demand sides of data, and develop more advanced solutions in the fields of business and government governance. Multiple applications. Third, the business model. At present, most of the existing smart city profit models are driven by government investment, focusing on the division of labor and cost bearing models in investment and operation, and lack of real business forms that benefit all parties. But in fact, in the whole process of various industries, there are potential operating and profit spaces. This requires each enterprise to attach great importance to the operation link in the process of digital transformation, abandon the traditional logic of selling or leasing, and pay special attention to the data in the operation link. On the one hand, it helps optimize the product itself, and on the other hand, it pays attention to tapping wider commercial value to extend the industrial chain.
Since 2019, life in all walks of life has not been easy. Facing the depletion of online traffic on the Internet, they began to think about downgrading consumption. Developers "couldn't raise money" while building houses and were "stuck" by policies and couldn't sell them. This is the case for the three formerly prosperous industries. On the surface, they encountered a group of "black swans" due to bad luck. In fact, it is also caused by the economic cycle. "Grey rhinos" will always come when they should come. On a deeper level, with the development of urbanization and industrialization in China today, all habitual growth methods are close to the limit. Without deep adjustments, it is not so easy to jump over the middle-income trap. The focus of development in big cities has shifted from incremental to stock, housing demand has slowed down, and developers are increasingly disliked by the government and banks. The real estate industry with Chinese characteristics has always been a very special role. Although products and property services are core competitiveness, making money basically depends on capital and leverage. Developers who can't get financing, in the end, only have product capabilities, and become builders, and the financial capital behind them takes the bulk. As a result, developers have transformed one after another, and most of them announced various cuts from the real estate business, changing their names to various operators and service providers. To put it simply, houses that cannot be sold are held for a long time to collect rent. Whether it is a long-term rental apartment, health care or shared office, this logic is the same. Even if the income level reaches ABS and REITs, it will not be able to achieve a high turnover; more advanced city operators, from investment promotion to infrastructure and public services, solve everything for the government. However, it is obvious that short-term profits will be greatly reduced when the former changes from selling to renting. Selling cabbage with negligible financing costs and labor costs when selling white powder in the past can be imagined. As for urban operators, it is easy to lose sight of the boundaries between enterprises and the government, and it is not so easy to take money that does not belong to them. In fact, city operation and management can indeed be a big business. Under the traditional model, the operation and management of cities are mostly public goods that require a lot of human and financial resources, so almost all the things are done by the government. After the popularization of PPP, city governments began to outsource more and more tasks to enterprises. However, there has been no clear boundary on how to divide the work between the government and enterprises. Operation is to plan, organize, implement and control the whole process of product production and service creation. It is originally a kind of business operation behavior. The work of property leasing and management is originally a mature market-oriented field, which is not the focus of our discussion. Many jobs in the urban public domain also tend to be undertaken by corporate entities, especially those parts that can truly realize market-oriented operations and make profits, or at least be able to maintain self-sufficiency. governmental The role will gradually turn to a purely "management" role in the true sense, mainly to complete rule-making, bottom-line review, standard inspection and other work. Traditional urban operations, in order to maintain the efficient operation of infrastructure and public services, mainly rely on manpower input, which is costly and inefficient, such as city appearance, sanitation, public transportation and other fields; the same is true for urban management. Even the so-called digital urban management or grid management that is popular now seems to be an information-based shell, but in essence it is the improvement of management granularity achieved by intensive manpower input. The two things of operation and management can be truly distinguished and realized. An important prerequisite is data. With the development of ICT technology, especially the Internet of Things, the urban infrastructure system has gradually completed the digital transformation, realizing the interconnection of all things, real-time online, sensory and controllable, and many of them have the ability to operate unattended and autonomously. For example, dockless shared bicycles replace piled bicycles operated by the government and private bicycles. Another example is the automatic compression and capacity perception of smart trash cans, which greatly reduces the labor requirements for inspection and maintenance. The associated unmanned sanitation vehicles can even turn street cleaning and trash dumping into a closed loop that is completely labor-free and data-driven, thereby improving user experience while greatly reducing operating costs. Over time, the entire city will gradually become a huge ICT product, whose operation can be driven by the logic of data. The whole digitalization of urban operations not only brings system optimization, but also provides the possibility for refined urban management. After the data of various urban infrastructure and public services are fully aggregated, the government can monitor all urban events and infrastructure components in real time without requiring a large number of inspectors and administrative procedures, and use algorithms to identify and warn of abnormal events, realizing rule-based digital management. For example, the two pain points in the shared bicycle industry, total volume control and space scheduling, are actually not difficult to solve. However, the current predicament is caused by the "human sea tactical" operation and maintenance of most manufacturers and the "bluffing" supervision of the government. If the unified data platform access of all manufacturers' data can be realized, or a unified electronic label and code for each vehicle can be realized, the location supervision of all brands of vehicles across the city can be realized, and the operational requirements for manufacturers can be truly implemented. Under such a general trend of universalization of urban facilities and services, a huge industry outlet has gradually emerged: developers, property companies and other traditional enterprises with urban operation genes, as well as ICT and the Internet that master online traffic and IoT platforms Companies will try their best to compete for more and more physical space operation rights as future traffic entrances. In the near future, it is to control new space scenarios such as smart home, new retail, and travel, especially its data collection capabilities, to reserve resources for artificial intelligence; a large amount of data will gradually release its commercial value, and data operations will become an important business model for city operators; eventually, data-driven urban operations may give birth to a new type of giant: everything operator. These companies will use the Internet of Things to operate various facilities and services in the city at low cost, ranging from small bicycles, street lights, and trash cans to large toilets and various functional spaces, until they control the entire city machine. On the one hand, they can obtain continuous service fees.
When we analyzed the paradigm of intelligent transformation of industrial ecology and the presentation logic of operators of all things, we mentioned the changes to the government governance model after the intelligent transformation of cities. In the complete urban development logic of planning, construction, operation, and management, more and more changes and interactions have taken place in the two links of operation and management, which will gradually differentiate into two new models that are completely different from the traditional ones. Perhaps this is the most important change that intelligence brings to cities. The mainstream business in the early smart city market, on the one hand, was doing digital and Internet-based transformation of government management processes, and on the other hand, it was helping municipal and infrastructure departments to digitally transform city operations. Therefore, there were business systems such as smart government affairs, smart urban management, smart transportation, smart municipal administration, smart public security, and smart sanitation that matched the government’s current division of powers and management lines. One potential reason why the government has to do these dirty jobs is that these jobs are not only difficult to make a profit, but also cannot be handed over to enterprises to operate and subsidize them because of their operational dynamic workload and effects are difficult to quantify and evaluate. With the in-depth development of the Internet of Things and artificial intelligence technology, smart cities have also entered a new period of development in the past two years. After the transformation of the Internet of Things, more and more urban scenes have the ability to operate independently or even commercially. Urban smart hardware such as shared bicycles, driverless buses, smart trash cans, smart sanitation vehicles, and smart street lights are gradually changing the operating model of the entire infrastructure and public service system, starting from partial product innovation. After more and more urban systems are transformed by IOT and artificial intelligence operation technologies, some changes will be brought about by government-led urban management. An important feature is the evolution of urban data platforms. When it comes to data platforms or informatization platforms, the government has always liked it, and of course the big screen is the one I like the most. Back then, the first generation of urban data platforms was very high-end. The most powerful platform in that era must have been the planning bureau. It was a true three-dimensional digital city. The textures on the building facades could be faked, and various static statistics and charts could be visualized. It even had planning, construction, management and other planning industry management functions. Urban design and even architectural design could carry out scheme comparison and spatial analysis. However, most of its data comes from the statistical department, and at most some summary data charts of various departments are added. The urban management we are talking about can also be called urban governance. Obviously, it is not the current narrow concept of "urban management". Secretaries and mayors, how to coordinate the healthy operation of the entire city system and various departments. But the first generation of so-called urban data platforms are just low-dimensional departmental platforms. In the past two years, with the continuous expansion of Internet data sources and the continuous aggregation of government data, the richness of data available for decision-making support is far from comparable to that of the past. However, real-time data on the operation of many cities is still difficult to obtain due to technical and institutional reasons. Therefore, our team is also continuing the research and development of urban intelligent hardware, especially various integrated urban sensors aimed at establishing a low-cost, high-density, full-service urban perception network. At the same time, with the evolution of the urban operation model mentioned above and the development of PPP, the urban operation functions of many government departments have gradually weakened, and the remaining management functions tend to be integrated across departments. The organizational structure of the city government has also undergone some changes: some cross-industry high-dimensional institutions have emerged, the most typical is the integration of planning, land and other "multi-plan integration" to natural resource management departments; large urban management departments that integrate traditional departments such as planning, urban management, sanitation, environmental protection, and municipal city appearance have gradually emerged; emergency capabilities of various urban lifelines have been separated and integrated into specialized emergency management departments; data authorities such as big data bureaus have emerged, and began to coordinate facilities and data for smart city construction from top to bottom. These high-dimensional departments directly correspond to the government's rule setting, bottom line supervision and other functions, and an important prerequisite for the exercise of these functions is the digitization of the entire city life cycle. This is also an important driving force for the central government to continuously strengthen the concept of "Digital China" since the 19th National Congress of the Communist Party of China. In the thinking model of city leaders, although the division of departments is an inevitable structure for the operation of the state machine, it is also a natural obstacle to the handling of urban affairs. The same emergency, such as traffic accidents or geological disasters, will have different dimensions of expression and information in the systems of different departments, but the previous methods are usually unable to quickly integrate these information to provide decision support. Artificial intelligence, through the learning and abstraction of a large amount of historical data, coupled with the logical synthesis of expert systems, can re-present the causal relationship and correlation of various urban problems and events with events and transactions as clues. As a complex system, cities can help decision makers quickly identify and deal with key links in this way, thereby greatly improving the efficiency and scientificity of urban management. Real-time data on city operations are still difficult to obtain due to technical and institutional reasons. Therefore, our team is also continuing the research and development of urban intelligent hardware, especially various integrated urban sensors aimed at establishing a low-cost, high-density, full-service urban perception network. At the same time, with the evolution of the urban operation model mentioned above and the development of PPP, the urban operation functions of many government departments have gradually weakened, and the remaining management functions tend to be integrated across departments. The organizational structure of the city government has also undergone some changes: some cross-industry high-dimensional institutions have emerged, the most typical is the integration of planning, land and other "multi-plan integration" to natural resource management departments; large urban management departments that integrate traditional departments such as planning, urban management, sanitation, environmental protection, and municipal city appearance have gradually emerged; emergency capabilities of various urban lifelines have been separated and integrated into specialized emergency management departments; data authorities such as big data bureaus have emerged, and began to coordinate facilities and data for smart city construction from top to bottom. These high-dimensional departments directly correspond to the government's rule setting, bottom line supervision and other functions, and an important prerequisite for the exercise of these functions is the digitization of the entire city life cycle. This is also an important driving force for the central government to continuously strengthen the concept of "Digital China" since the 19th National Congress of the Communist Party of China. In the thinking model of city leaders, although the division of departments is an inevitable structure for the operation of the state machine, it is also a natural obstacle to the handling of urban affairs. The same emergency, such as traffic accidents or geological disasters, will have different dimensions of expression and information in the systems of different departments, but the previous methods are usually unable to quickly integrate these information to provide decision support. Artificial intelligence, through the learning and abstraction of a large amount of historical data, coupled with the logical synthesis of expert systems, can re-present the causal relationship and correlation of various urban problems and events with events and transactions as clues. As a complex system, cities can help decision makers quickly identify and deal with key links in this way, thereby greatly improving the efficiency and scientificity of urban management. Real-time data on city operations are still difficult to obtain due to technical and institutional reasons. Therefore, our team is also continuing the research and development of urban intelligent hardware, especially various integrated urban sensors aimed at establishing a low-cost, high-density, full-service urban perception network. At the same time, with the evolution of the urban operation model mentioned above and the development of PPP, the urban operation functions of many government departments have gradually weakened, and the remaining management functions tend to be integrated across departments. The organizational structure of the city government has also undergone some changes: some cross-industry high-dimensional institutions have emerged, the most typical is the integration of planning, land and other "multi-plan integration" to natural resource management departments; large urban management departments that integrate traditional departments such as planning, urban management, sanitation, environmental protection, and municipal city appearance have gradually emerged; emergency capabilities of various urban lifelines have been separated and integrated into specialized emergency management departments; data authorities such as big data bureaus have emerged, and began to coordinate facilities and data for smart city construction from top to bottom. These high-dimensional departments directly correspond to the government's rule setting, bottom line supervision and other functions, and an important prerequisite for the exercise of these functions is the digitization of the entire city life cycle. This is also an important driving force for the central government to continuously strengthen the concept of "Digital China" since the 19th National Congress of the Communist Party of China. In the thinking model of city leaders, although the division of departments is an inevitable structure for the operation of the state machine, it is also a natural obstacle to the handling of urban affairs. The same emergency, such as traffic accidents or geological disasters, will have different dimensions of expression and information in the systems of different departments, but the previous methods are usually unable to quickly integrate these information to provide decision support. Artificial intelligence, through the learning and abstraction of a large amount of historical data, coupled with the logical synthesis of expert systems, can re-present the causal relationship and correlation of various urban problems and events with events and transactions as clues. As a complex system, cities can help decision makers quickly identify and deal with key links in this way, thereby greatly improving the efficiency and scientificity of urban management. Urban planning, urban management, environmental sanitation, environmental protection, municipal and city appearance and other traditional departments of large urban management departments have gradually emerged; the emergency capabilities of various urban lifelines have been separated and integrated into specialized emergency management departments; data authorities such as big data bureaus have emerged, and began to coordinate facilities and data for smart city construction from top to bottom. These high-dimensional departments directly correspond to the government's rule setting, bottom line supervision and other functions, and an important prerequisite for the exercise of these functions is the digitization of the entire city life cycle. This is also an important driving force for the central government to continuously strengthen the concept of "Digital China" since the 19th National Congress of the Communist Party of China. In the thinking model of city leaders, although the division of departments is an inevitable structure for the operation of the state machine, it is also a natural obstacle to the handling of urban affairs. The same emergency, such as traffic accidents or geological disasters, will have different dimensions of expression and information in the systems of different departments, but the previous methods are usually unable to quickly integrate these information to provide decision support. Artificial intelligence, through the learning and abstraction of a large amount of historical data, coupled with the logical synthesis of expert systems, can re-present the causal relationship and correlation of various urban problems and events with events and transactions as clues. As a complex system, cities can help decision makers quickly identify and deal with key links in this way, thereby greatly improving the efficiency and scientificity of urban management. Urban planning, urban management, environmental sanitation, environmental protection, municipal and city appearance and other traditional departments of large urban management departments have gradually emerged; the emergency capabilities of various urban lifelines have been separated and integrated into specialized emergency management departments; data authorities such as big data bureaus have emerged, and began to coordinate facilities and data for smart city construction from top to bottom. These high-dimensional departments directly correspond to the government's rule setting, bottom line supervision and other functions, and an important prerequisite for the exercise of these functions is the digitization of the entire city life cycle. This is also an important driving force for the central government to continuously strengthen the concept of "Digital China" since the 19th National Congress of the Communist Party of China. In the thinking model of city leaders, although the division of departments is an inevitable structure for the operation of the state machine, it is also a natural obstacle to the handling of urban affairs. The same emergency, such as traffic accidents or geological disasters, will have different dimensions of expression and information in the systems of different departments, but the previous methods are usually unable to quickly integrate these information to provide decision support. Artificial intelligence, through the learning and abstraction of a large amount of historical data, coupled with the logical synthesis of expert systems, can re-present the causal relationship and correlation of various urban problems and events with events and transactions as clues. As a complex system, cities can help decision makers quickly identify and deal with key links in this way, thereby greatly improving the efficiency and scientificity of urban management.
The CIM real-scene fusion technology platform of Jiadu Technology’s main product line in 2019 is based on the city-level digital twin empowerment application platform as the product direction, with virtual reality interactive control, massive front-end video fusion, multi-map integrated model rendering, and real-time video structural algorithm as the featured technology; it uses the eagle-eyed holographic real scene to observe people, vehicles, and objects, and uses the self-controllable three-in-one model capability of multi-dimensional data-video fusion-map transformation to achieve quality improvement and efficiency, visual refreshment, map-screen linkage, and detailed time and space Information scene application is an integrated general technology platform using new technology. The concept of digital twins has had a high rate of appearance in the field of smart cities in the past two years. Although the name of this concept from the industrial field is interesting, it does not have any new connotations. It is nothing more than recreating the mirror image of the physical space in the digital space. For the disciplines of architecture, planning, and geography, we also have to model the three-dimensional urban space, that is, to make the digital city mentioned before. The concept of CIM (City Information Model) that we already have is basically synonymous with digital twins. Of course, in addition to GIS and BIM that describe three-dimensional spatial information, the Internet of Things enables the interconnection of everything and real-time perception. We can realize the collection of more city operation data, and all people, objects, and flows can obtain data synchronization in the digital space. From this point of view, in fact, the city big data we have been talking about in the past few years is trying to use various data to restore a complete city operating state as much as possible. In addition to government data, traditional spatial data, and Internet data, a new urban perception network is on the horizon. Although the current cameras and environmental monitoring equipment can collect a lot of real-time data, they are still far from fully presenting the city's operating status and meeting the needs of refined management. When it comes to digital twins, people often pay attention to the highly compelling parts, such as a sandbox system that can simulate deduction, what artificial intelligence can make decisions and judge, and even live in a virtual world like Matrix or the movie "Top Player". as the ultimate goal. The so-called logic of artificial intelligence, no matter what kind of machine learning or neural network, must first learn a large amount of historical data, and we actually don’t have enough multi-dimensional data to train the AI operating in the city. At best, it can simulate the operation of some simple systems and barely match the timing of the entire traffic light. Therefore, in fact, the key to realizing digital twins is to define new technology products with global perception. This is not a single product, but a product system, and it must be continuously iterated with the development of sensors, 5G and edge computing technologies. High-density deployment, high-precision perception, and real-time structured computing backhaul are similar to unmanned high-precision maps. real-time updated full In addition to spatial information, the information city information model can also superimpose countless data dimensions. Each brick, one tile, one plant, one tree, one table, one chair, one person and one car will update location and status information at different frequencies. It is really "holographic". The amount of data and bandwidth requirements are beyond our imagination now, but they will be the norm in the 5G era. Of course, "holography" is undoubtedly an endless goal, and it may be a new cycle similar to Moore's Law pursued by the next IT field. 5G is currently the most popular ICT technology concept. Operators themselves believe that there are no real application scenarios. In fact, this is not something that equipment manufacturers should solve. So I feel that many industries are thinking about their relationship with themselves recently, including some developers and friends in urban planning. Reminiscent of the upgrade of previous generations of wireless communication technology, although the speed is hundreds of times faster, and the transmission content ranges from voice to text messages, long texts, pictures, videos, and live broadcasts, it has given birth to the mobile Internet, especially social applications such as Weibo and WeChat, as well as major video apps such as Kuaishou Douyin and Taobao Jingdong Pinduoduo. Of course, there are more fresh food e-commerce physical stores around us, and some department stores have closed down, but that's all? Why do people have different expectations for 5G? Perhaps it is because this upgrade seems to be reaching some long-awaited critical points, which will lead to a series of qualitative changes, and of course, will bring endless new business opportunities, and the impact on the planning, construction, operation and management of the city will be even greater. It can be said that all our previous innovations in the field of smart cities are the prelude to the new urban revolution that began in the 5G era. As far as technology is concerned, 5G meets almost all imaginations about wireless communication. Continuous wide-area coverage enables high-speed movement, low latency and high reliability, low power consumption, large connections, and high capacity (traffic density). The technological progress of wireless communication is nothing more than the optimization of a series of mathematical relationships around frequency, bandwidth, power, and signal-to-noise ratio. The reason why 5G is different from previous upgrades is that the spectral efficiency this time has basically reached the limit of Shannon's theorem. If there is no revolution in basic theory, this upgrade is basically the last of this round. The so-called 6G, people usually place their hopes on the terahertz frequency band, which is still only a concept at present. Millimeter wave communication is the core technical feature of 5G. The millimeter wave beam is narrow and directional. small Base station and antenna technologies such as cell and massive MIMO also serve the premise of millimeter waves. The most direct impact of these on urban space is that due to the low transmission power of micro-stations, small service radius, poor penetration, large transmission loss, and basically line-of-sight transmission, they need to be deployed very densely in cities. The emergence of smart street light pole products and business models in the past two years is basically preparing for the landing of 5G base stations. As the most dense infrastructure in the city, with power supply and broadband connection guarantee, light poles will inevitably become the most important carrier of the urban Internet of Things, especially various sensors that collect video and even 3D data streams, sound, pollutants, weather and other urban operating conditions. After full integration, they can realize holographic grid city status and event perception. In the future, these carriers and data will also be important topics for autonomous vehicle-road communication.
As a by-product, the high-density base station layout and precise orientation capabilities will bring a leap in the value of mobile phone signaling data. The positioning accuracy will be improved by an order of magnitude, comparable to the current GPS data, reaching sub-meter or even centimeter level. More importantly, it can realize high-precision positioning of indoor and outdoor integration. Signaling data will become the most neat and accurate data source describing people's location and behavior, replacing most positioning and counting tools, and providing support for refined urban planning and governance. Of course, the product form of mobile phones should be replaced in about five years, but it should be incarnated into more IoT products, especially wearable devices, to play a similar role. In terms of specific indicators, the theoretical value of the download rate is 10GB per second, which is ten times that of 4G; the theoretical delay is 1ms, which is a few tenths of 4G; the theoretical value of the number of IoT terminals in a single communication community reaches the million level, which is more than ten times that of 4G. From the perspective of high reliability and low latency, the order of 1ms is actually lower than the transmission delay of the nervous system, so it is mainly used in scenarios that require ultra-high precision or high moving speed, the most typical one is autonomous driving. Especially formation driving and remote driving as L5 transition state. In the case of high-speed driving, the braking delay of milliseconds corresponds to the braking distance of centimeters. From single-vehicle autonomous control to V2V and V2X large-scale systems, communication technology can release a large amount of perception and computing pressure on the vehicle side. The most important benefit is undoubtedly safety. The improvement of the safety of unmanned driving until the final popularization of L5 will bring the biggest changes to the city in the 5G era. This article does not focus on this part. After all, the story of Sidewalk’s entire urban-scale spatial transformation is almost based on unmanned driving, including the reduction of the sensitivity of spatial distance, the partial elimination of the difference between travel and fixed places, the need for private cars, the integration of shared travel and public transportation, the highly mixed nature of urban land use, the elimination of TOD mode, the reduction of road resource requirements, and the sharp reduction in parking lot demand... In general, unmanned driving brings about the integration of urban traffic functions and other functions. Vehicles and various generalized unmanned vehicles will become mobile urban functional spaces. The concept of urban functional zoning since the Athens Charter will be dispelled at all scales, although not necessarily completely subverted. Regardless of the size of the urban functional space, the exchange of information between each other and the connection of the physical space through road traffic will present a new relationship. In fact, it is several new ways of interaction between the digital twin space and the physical space. There is no suitable theoretical discussion yet. In addition, 5G can provide the remoteization of some precision operation scenarios. Another typical application scenario of low latency It's telemedicine. Combined with tactile robots, remote B-ultrasound and endoscopic diagnosis, and even remote surgery can be realized, helping non-urbanized or backward areas to achieve a balanced medical level and reduce medical costs. Similarly, from an industrial point of view, some high-precision operations can also introduce remote collaboration mechanisms and even remote employment. Perhaps these futures are just supplements to unmanned factories far away from cities. Typical applications for high-bandwidth applications are VR, AR, and ultra-high-definition video, and entertainment applications are usually considered. In my opinion, the point is that the bandwidth supported by 5G can probably solve some face-to-face communication problems that the video era has not yet solved. In the past, we thought that communication, voice and even video could eliminate spatial distance to a certain extent, and even realize remote communication instead of face-to-face. Until the 5G era, truly holographic VR technology can achieve this goal to a certain extent. In addition to voice and face, subtle expressions and movements can be captured, and information at the level of "aura" can be felt, and even factors that affect the realism of communication such as smell, microenvironment, and touch. It can be foreseen that when the need for immersive communication with the teachers of the island country is perfectly satisfied, other scenes should not be a big problem. Speaking of teachers, can the traditional assembly-line K12 education, with the assistance of AI and 5G, also truly realize remote interaction and individualized teaching? Low power consumption and large connections are mainly used in the field of Internet of Things. In future cities, the Internet of Everything will exceed our current imagination, not just smart home and transportation applications. The last-mile optical fiber network and even basic weak current wiring may be replaced by 5G direct connection. At present, smart home devices with various connection methods may become flat structures, which will have a considerable impact on the current market structure. Engineering construction can get rid of some cable restrictions, which will save a lot of cost, but it remains to be seen how much the actual impact on the design will be. To The early unreliable Internet of Things connection in the G era and NB-IoT will become history. Whether NB-IoT or Lora or another low-power wide-area network protocol wins or fights against each other, it will bring us a more stable and reliable IoT experience. Of course, this is the difference that will be felt by those who suffered from it before. With the development of sensor technologies such as MEMS, all urban infrastructure and even building components will be connected to the Internet of Things, and their status will be updated in real time, eventually realizing data-driven control operations. Combined with low-latency features, AI edge computing will also be integrated with the Internet of Things to solve basic AI analysis capabilities, reduce unnecessary burdens on the cloud and transport layers, and truly realize AIOT. For example, smart cameras with seamless coverage in the future, the high-definition video collected by it will complete various basic content recognition and structural processing including faces locally, which can be called on demand or even distributed retrieval, combined with other sensing capabilities, to jointly build a digital twin city that is truly refreshed frequently. 5G will undoubtedly change our cities as much as electricity and steam engines. As urban planners, we are fortunate to live in an era of imminent change that may create new paradigms of urban theory. But at present, our imagination does not seem to be able to predict the changes in the shape of cities in the future. There is no substantive new knowledge in the above, at best, it can be regarded as sorting out ideas. Already mentioned the changes in the strongest functional elements that determine the centrality of a city, such as industry, transportation, medical care, and education, together with the retail industry that has occurred long ago, although the resulting changes in spatial form seem to further disperse, mix, and even atomize urban functions. On a large scale, it may point to regionalization and networking, but the effect of superposition is unimaginable. Moreover, the greater changes in this urban revolution may not be mainly in form, but in the logic of planning, construction, operation, and management itself. 5G is not an independent technology, but together with other ICT and even material and biological technologies, presents a holographic perception and data-driven city, which can better adapt to and meet the needs of citizens through artificial intelligence, learn independently, and improve itself. Urban planners don’t need to rack their brains to imagine a different sci-fi scenario. Instead, they need to think more about how to use new technologies and data to gradually optimize our existing urban space, and learn to transform into experts in evidence-based medicine and even precision medicine in addition to surgical operations and the skills of seeing, hearing, and asking. Smart cities also need more architects and urban planners who understand ICT technology, as smart scenario planners, to create richer and more appropriate technology application scenarios. "Scene" planning is a very abstract and comprehensive concept, which I understand as The overall arrangement of various elements in the space container, urban planning focuses on its physical space elements, the scene theory of the New Chicago School has comprehensively studied urban space and social space, and smart cities need to comprehensively consider spatial elements and ICT technology elements. Smart city scene design can be compared to the scene design of movies and games. From the story line to the world view, from the lens language to the lighting props, it needs to be comprehensively analyzed from the operating logic of the entire system. Scene design has several key links or technical requirements. First, it is the understanding of the complexity of urban scenes. Everyone knows that a city is an open and complex giant system, but what does it mean? The complex connections and interactions between urban elements affect the whole body, so that it is often impossible to simplify with reductionist thinking. Similar to urban planning, solving complex problems needs to pay attention to the relevance and dynamics of things, and consider the various systems and departments in the city comprehensively. Most of the current smart city systems are built by vertical departments, forming data chimneys one by one. But in fact, all kinds of data can serve more than one system, which leads to a lot of repeated construction, especially repeated data collection. There is no unified driving force for the common needs among the various systems, and the difficulties of sharing and gathering will be reflected in all links, especially the overall planning at the municipal level, which is often difficult to deal with. For example, when we develop urban data fusion sensors, we need to sort out the perception needs of various systems such as environmental protection, urban management, transportation, and public security, merge indicators and common factors of spatial deployment, and explore the possible value of each type of data to other systems to create innovative industry applications. In addition, the characteristics of self-organization and emergence of complex systems make the sum of individuals far greater than the whole, so nonlinear thinking is an important quality. The second is the understanding of the interactive relationship between technology and space. Revolutionary technologies have the power to destroy and reshape space. Railways, electricity, automobiles, and elevators are all similar technologies that can change the shape of cities. The upcoming L4L5 autonomous driving and 5G may become similar revolutionary technologies. Referring to the deduction of the 5G urban scene in the previous article, we need to be able to detach from the technology itself, understand and identify the variable and unchanging elements in the city, observe the possible changes that technology may bring to various urban elements from the perspective of technology history, and then deduce the ensuing spatial changes. For example, if you look forward to cities dominated by driverless and shared travel, you cannot still configure parking spaces mechanically according to the current regulations. At least you must consider the flexible transformation method after the future lanes are narrowed and parking demand is reduced. And if you still use the logic of private car ownership instead of sharing to measure the demand for driverless cars, it will be a comparison. Traffic jams are a bigger disaster. Therefore, the longer-term vision of logical deduction will be the transformation of the public transportation system and the change of land use organization. This also reflects the complexity of the first article, that is, the change of each variable will bring about a series of chain reactions. The third is the sensitivity to comprehensive technology. Smart city projects are naturally inseparable from the comprehensive application of ICT technology, and innovative applications, especially long-term process reengineering projects, often require the use of a lot of cross-field technologies, and even black technology for innovative research and development, which is a huge challenge for personnel with any background. Conventional technologies such as cloud computing, Internet of Things, and sensors may not be a big problem for IT companies, but when it comes to complex wireless requirements, only Huawei has enough CT capabilities to handle them. But in more scenarios, more comprehensive technologies in materials, industrial control, energy, and even biochemical fields are involved. Even though each technology may not be very complicated, it becomes an impossible task when combined. For example, underground robots are almost the only way to monitor internal blockages and leaks in the drainage pipe network. However, most of the products on the market are still in a rudimentary form. Either it is a ball that does not know where to go, or it can only be dragged with tens of meters of wires. One well after another drains the water and puts it down for a short section by video inspection. The overall cost per kilometer is tens of thousands. Of course, now there are three-dimensional shape perception capabilities integrating video, lidar, and sonar, as well as crawler, snake, and abdominal wall travel methods, as well as long battery life. However, it can work independently without interruption, can supply power from sewage, can penetrate several meters of soil layer to communicate and locate with the ground, can deal with complex and viscous oil contamination and corrosion, and can place passive positioning tags and MEMS sensors. The requirements are actually not difficult technically. However, because the technical fields involved are too broad and the comprehensive requirements for the R&D team are high, there has been no ideal product. In the field of urban infrastructure transformation, this kind of huge market demand is everywhere, but it is usually ignored. The fourth is the ability to construct problem-oriented comprehensive scenarios. The essence of urban planning as I understand it is to coordinate various resources to solve urban problems. Of course, ICT technology should be a tool for solving problems just like spatial means. The current so-called smart city demonstration projects often put together various so-called high-tech products, but do not really consider the needs of the scene, even the Xiong'an Civic Center and Haidian Park are no exception. For example, the unmanned driving products in the park are mature, but they are usually thrown on the road as an amusement project. The fifth is a deep understanding of urban data. Regardless of intelligence or informatization, the foundation is digitalization. Re-describing and explaining cities with data is the first step of a smart city, and it also runs through the entire life cycle of a city. theme. Data is the premise of intelligence. Without the collection of massive data as training samples, there will be no recognition of the laws of various urban systems, let alone prediction and regulation; data is the clue of the scene, and various applications and products rely on data exchange to establish organic connections. Rich interoperability comes from sufficient cross-system data connections; data is the driving force of industries, and a sound data ecology that is open, shared and privacy-protected is an important prerequisite for the formation of an innovative and entrepreneurial atmosphere in smart cities. The main sources of data will range from the Internet describing people to the Internet of Things describing facilities. From various independent sensors to an integrated urban sensor network, from passive perception of traditional facilities to active data upload by digital facilities, this process of change is also the basic logic for us to transform the physical world. Finally, a holographic digital twin city is presented in the digital space, and even the main life scenes are moved from the physical space to it. The sixth is the understanding of human needs. This one is the most abstract. Most smart city projects, whether To G or To B, ultimately serve the citizens. We believe that taking citizens as the core and the full participation of multiple subjects is the basic guarantee for the success of the project. In the age of space planning, we have the tools of environmental behavior and ergonomics. However, in the digital scene, there is no corresponding methodology for the quantitative description and evaluation of people's subjective experience, sense of gain, and happiness. Many of the embarrassing products we see are the wishful thinking of engineers. The most representative is the design of many mainstream smart home products. Crappy products and interaction designs make the original effort cumbersome and boring. There are also many similar superfluous applications on the B-side and G-side. For example, the current hodgepodge-style smart light poles hang various simple ICT functional modules on the same pole, which is called smart, but none of them really seeks to integrate the collection of urban data to train urban intelligence. Maybe solving traffic problems through data is not directly To C, but may be a better solution to citizens' real problems than a cell phone charger on a street lamp. The seventh is the understanding of the laws of infrastructure operation. Smart city essentially refers to a new generation of urban support technology system, and the key to defining a city from the technical attributes lies in the new infrastructure system, which is fundamental to support all urban scale forms and operation management models. But because most of them are hidden projects, the investment is huge but it is not easy to see directly, so it is easy to be ignored. The city's water, electricity, heat pipe network and energy supply methods, together with solid waste treatment methods, are technological products of the entire industrial age. The basic method may have been stabilized, but its efficiency, safety, energy saving, and environmental protection have huge room for improvement. The basic method is to rely on ICT and new technologies such as materials, chemistry, biology, and energy to transform the existing system to support a more sustainable urban form. Today, the cities on the ground are bright and beautiful, but few cities can figure out how many pipelines are buried underground, and how many are constantly leaking, polluting the soil and groundwater, and even lurking in the risk of bursting or even explosion. The comprehensive pipe gallery is of course a good way to solve the problem by money, but in fact, a large number of stock urban infrastructure needs to be improved in a more pragmatic way. The Internet of Everything in the Internet of Things era does not focus on the lights and TVs at home, but on the real-time online control of the entire urban infrastructure system. All underground pipelines will become new ICT devices with their own nervous system, and gain sensing and data transmission capabilities, making urban operations safer, more efficient, and more resilient. The accuracy and coverage of this above-ground and underground integrated sensing and control network will far exceed current imagination. The evolution from manual inspection and empirical operation to a new city lifeline controlled by artificial intelligence will also be a very important application scenario for future 5G networks. Recently, I have to recall some infrastructure courses I took at school, and the pressure and gravity pipe network I drew by myself back then, trying to abstract the various data that may support its efficient operation and its perception methods. This may be a method that is closer to the essence of the future city. In addition, roads, as a special infrastructure, have always been the most important elements that define urban forms, together with transportation methods. The proportion of ICT investment in road infrastructure costs will increase exponentially, such as unmanned driving, vehicle-road integration, power generation and charging on the road, new public transport systems, MAAS... Groundwater, even the risk of bursting and even explosions lurks. The comprehensive pipe gallery is of course a good way to solve the problem by money, but in fact, a large number of stock urban infrastructure needs to be improved in a more pragmatic way. The Internet of Everything in the Internet of Things era does not focus on the lights and TVs at home, but on the real-time online control of the entire urban infrastructure system. All underground pipelines will become new ICT devices with their own nervous system, and gain sensing and data transmission capabilities, making urban operations safer, more efficient, and more resilient. The accuracy and coverage of this above-ground and underground integrated sensing and control network will far exceed current imagination. The evolution from manual inspection and empirical operation to a new city lifeline controlled by artificial intelligence will also be a very important application scenario for future 5G networks. Recently, I have to recall some infrastructure courses I took at school, and the pressure and gravity pipe network I drew by myself back then, trying to abstract the various data that may support its efficient operation and its perception methods. This may be a method that is closer to the essence of the future city. In addition, roads, as a special infrastructure, have always been the most important elements that define urban forms, together with transportation methods. The proportion of ICT investment in road infrastructure costs will increase exponentially, such as unmanned driving, vehicle-road integration, power generation and charging on the road, new public transport systems, MAAS... Groundwater, even the risk of bursting and even explosions lurks. The comprehensive pipe gallery is of course a good way to solve the problem by money, but in fact, a large number of stock urban infrastructure needs to be improved in a more pragmatic way. The Internet of Everything in the Internet of Things era does not focus on the lights and TVs at home, but on the real-time online control of the entire urban infrastructure system. All underground pipelines will become new ICT devices with their own nervous system, and gain sensing and data transmission capabilities, making urban operations safer, more efficient, and more resilient. The accuracy and coverage of this above-ground and underground integrated sensing and control network will far exceed current imagination. The evolution from manual inspection and empirical operation to a new city lifeline controlled by artificial intelligence will also be a very important application scenario for future 5G networks. Recently, I have to recall some infrastructure courses I took at school, and the pressure and gravity pipe network I drew by myself back then, trying to abstract the various data that may support its efficient operation and its perception methods. This may be a method that is closer to the essence of the future city. In addition, roads, as a special infrastructure, have always been the most important elements that define urban forms, together with transportation methods. The proportion of ICT investment in road infrastructure costs will increase exponentially, such as unmanned driving, vehicle-road integration, power generation and charging on the road, new public transport systems, MAAS...
A city is a complex giant system. Whether it is for the study of the city, or for governance and control, it is necessary to restore and decompose the complex system. For example, traditional urban planning decomposes the city into several subsystems such as industrial economy, public services, architectural space, green landscape, road traffic, ecological environment, and municipal infrastructure for research and planning. Another example is the city government, which decomposes the city into subsystems such as industry, commerce, construction, land, environmental protection, education, medical care, transportation, and public safety for governance and control. The two categories have a corresponding relationship but are not identical. For example, the education, science, culture and health of the government are often combined into one subsystem from the perspective of planning, because they follow the same planning logic. As for the construction system, since it is the core content of spatial planning research, the planning will further refine it: buildings, green spaces, public spaces, etc. The formation of a reduction method that conforms to its own logic is a sign of a mature discipline. In the research and practice of smart cities, it has always been mainly dependent on the reduction logic of administrative management. For example, we have seen smart medical care, smart transportation, and smart public security. It is easy to understand that such products correspond to the powers of government departments and are easier to be purchased and used. However, when we conduct in-depth research on smart cities, we need to restore the complex giant system of cities from the more essential logic of smart cities. On the one hand, it helps us think about the direction of smart cities, grasp the rhythm of product research and development and industrial development, explore the nature of problems and solutions to system islands, and help us deeply understand the combination mode of "smart" and "city". The basic logic of cybernetics is based on the information obtained by the perception system to reveal the difference between the performance and the standard, and to take corrective measures to stabilize the system at the predetermined target state through circular feedback. Perception and control (more intervention in the urban field) are the two core links. Thinking from the perspective of cybernetics, the logic of the entire smart city is actually to use ICT as the core of new technology methods to transform urban spaces into CPS (Information Physical System). However, the so-called smart cities that are popular now, except for a few areas, are mostly digitization or informatization of traditional government business, and have not yet reached this stage. From the perspective of CPS or controllability, cities can be decomposed into three systems: ecological environment, artificial built environment and crowd behavior. It is said that the intelligent feature or strategy of this type of system is "strong perception, medium intervention". At present, most of the hardware investment in smart cities is also used to monitor the behavior of citizens, but what can be realized by monitoring is more timely response to abnormal events, as well as the exploration of the temporal and spatial patterns of citizen behavior, so as to improve infrastructure and public services. real control over social systems It is impossible to achieve. To realize the healthy development of the society and the community, and even the overall development and improvement of the citizens' sense of well-being, it is still necessary to rely on the participation of the community and citizens to gradually improve the city's service capabilities. The essence of a city can be described as "a complex functional network platform that improves production efficiency and residents' happiness under the conditions of limited resources such as space, environment, and energy through the centralized supply of infrastructure and public services." Almost all urban problems we solve can be attributed to a common pain point: solving the contradiction between limited infrastructure and service capabilities and rapidly growing demands. Traffic congestion, waterlogging, energy shortage, environmental pollution, etc. reflect the lack of dynamic service capacity and efficiency of infrastructure, and public facilities such as housing supply, housing prices, education and medical care reflect the lack of layout, supply and service level of housing and public services. The core objects of perception, on the one hand, are the dynamic demand information represented by the flow of people and vehicles, environmental pollution, and negative events; On this basis, data platforms and algorithms can realize dynamic forecasting and matching of supply and demand. For systems with different degrees of intervention, some can realize fully automatic real-time intelligent intervention, some can carry out long-term policy regulation, and some can be artificially enforced.