The theme of this summit is 14 benchmark enterprises representing the city AIoT, sharing business philosophy and technology application methodology for on-site and online audiences.
In the afternoon speech session, consulting partner Zhao Weifeng gave a wonderful speech.
Zhao pointed out that judging from the development process and characteristics of urbanization in China, the United States and Japan, China's urbanization speed has been ahead of the world since the reform and opening up 40 years ago.
Various smart city construction schemes can solve a large number of problems in the city by virtue of their advanced technology, strong perception and efficient application of data resources.
At the same time, smart cities contribute to the goal of carbon neutrality by virtue of their digital and green features.
However, it should not be ignored that in smart communities, smart businesses and other scenarios, there are still problems such as system fragmentation, data islands, and low comprehensive utilization of information. For example, fragmented single-point solutions, data is not open, forming data islands.
This requires that the single-point solution of smart city fragmentation should be gradually transformed into a full-scenario, one-stop complete solution.
The future cities will follow the following laws:
From information city to smart city to people-oriented city.
The following is the full text of Zhao's speech and Lei Feng's AI Nuggets. Com has been sorted out and edited without changing its original intention: China's smart city has exceeded 4 trillion. When it comes to cities, we must compare China with the United States. The biggest difference between China and the United States at the urban level is that the pace of urbanization in the United States has lasted for nearly a hundred years, while China has only entered rapid urbanization in the last two or three decades. This difference is very important.
In the last two or three decades, the population of China has increased, science and technology have exploded, and at the same time, it is in the stage of rapid urbanization. After the superposition of these three phenomena, it is a great challenge and opportunity for the management of the whole city, how to become a service-oriented city and how to become more intelligent.
From the perspective of investment, company development and financing, challenges and opportunities coexist.
China's cities have several characteristics. First, it integrates multiple functions. For example, the megacities in China are economic centers, education centers, science and technology centers and cultural centers. In the United States, some cities are political centers, some cities are science and technology centers, and some cities are economic and financial centers, while China is a comprehensive city with a population far larger than any single mega-city in the United States.
Comprehensive and super-large cities are faced with problems such as floating population management, urban traffic congestion, fire safety hazards, residents' health challenges and serious urban pollution in urban development management.
Among them, ESG, which is popular recently, refers to the concept that it is imperative for human beings to save energy and reduce emissions by using digital empowerment to make cities greener and lower carbon. There are many opportunities in the direction of ESG.
In fact, you will find that the top-level design of the policy only talks about one thing: how to treat the city as a person. The urban brain in the top-level design is equivalent to the human brain.
Digitalization allows the city's data to precipitate. How to digitize the massive data deposited in the past 10-20 years is the first element of urban wisdom. Coping with the scene is the second step after digitalization, and the scene will bring practical needs.
Third, to strengthen network construction, it is necessary to build a neural or vascular network to transmit data and information.
It is estimated that the smart city ecology has a market scale of 4-5 trillion. The core of ESG is low carbon, energy saving and emission reduction, and digitalization. ESG exists in every track. Smart terminals such as smart cars and robots, it is an inevitable trend that smart cities will usher in the Internet of Things era. Smart cars and robots are two very important nodes of the Internet of Things. Smart car is a means of transportation and a new working and living scene for human beings. This is an urban Internet of Things scene. Compared with cars, robots have more service functions or work functions, and are constantly evolving in the ability to collect scene data, geographic information data or autonomous learning.
In the direction of smart cars, autonomous driving is an inevitable trend. No matter it will take ten or twenty years to realize it, there will be no more drivers.
From L 1 to L3 in the early stage, people need constant attention and intervention. At this stage, a lot of technical research and development is needed to ensure that the driver is in place, and the arrival time of L4 time node is also different.
Under this trend, there are two sub-tracks, one is a new energy vehicle and the other is Robotaxi. The latter requires strong operational and service capabilities, and the arrival time is definitely later than that of smart or self-driving new energy vehicles.
At present, the trend of front loading is very clear. Whether it is lidar or camera, the front-mounted market is an inevitable choice.
Yesterday, a guest said that his cooperation with the car factory was constantly rubbed on the ground by the car factory and the main engine factory, and the afterloading would gradually be replaced and go further. Cooperation with mainstream OEMs is the future trend.
Smart bicycles are far from autonomous driving. To realize the coordination of people, vehicles and roads, it is necessary to have a network and finally realize automatic driving. People become relatively free people and can't always pay attention to the state of cars and roads.
Not only communication network, but also automatic driving needs computing network, which can support millisecond intelligent driving of smart cars.
Smart bicycles are far from enough, and smart roads are needed. In the future, a large number of lidar or nodes will be arranged on the roadside and edge to store the information of cars or road conditions that have passed.
To ensure the millisecond operation of L4 autopilot, the computing power of the chip is very high.
Automatic driving in commercial vehicle industry pursues more economic returns. In a typical logistics scenario, the methodology of looking for excellent companies lies in whether it solves the pain points of the industry or whether it can persist in doing one thing well under the general trend.
The cost of self-driving drivers of commercial vehicles is rising, and drivers will make mistakes and fatigue during driving. The competition in the logistics industry is serious, it is normal for drivers to overload or work overtime, and there are many security risks. Secondly, the logistics industry is seriously involved and the operating costs remain high. In the long-distance trunk transportation scene, electric and self-driving trucks have great potential, and express delivery and logistics distribution in urban areas will also generate a lot of demand in the low-speed scene.
Let's talk about robots. Many robots are growing and financing at a very fast speed this year. The important reason is that after the artificial intelligence technology matures, there are many results in algorithms and perceptual decisions.
For service-oriented cities, the closed loop of implementation and service will be finally realized. As an IOT device that can concretize AI capabilities, robots are empowered by AI, artificial intelligence and artificial intelligence in the cloud.
Robot track, some enterprises are divided into three stages. The first stage is to make the robot, complete the equipment and deliver it to Party A or the engineering company. This is a necessary stage. Enterprises need to consider the types and orbits of robots, such as service robots, industrial robots, cooperative robots and medical robots.
In the second stage, the robot collected a lot of data in the scene, and after precipitation, it became an important data source and foundation for AI to be smarter. The second stage has a long way to go, and whether the enterprise is excellent or not can also be seen in the second stage.
The third stage is similar to Tesla's development logic. In public perception, Tesla is not only a new energy automobile enterprise, but also a big data enterprise. Robot enterprises also have this phenomenon, and robots will eventually grow into terminals with self-learning and self-optimization.
In fact, robot companies can help new IOT equipment companies become smarter. Take the autopilot service provided by Tesla as an example. In a sense, it can open source and empower other companies. In the process of opening up urban bases and realizing people-oriented urban needs, there are a large number of equipment, enterprises and Internet of Things terminals. For a city manager, a big challenge is how many networks, platforms and platforms should be built in the face of massive applications, enterprises, services and data. This is a problem that many smart cities will face at present.
Databases or operating systems will gradually appear in some cities in the future.
In the long run, the last era was the mobile Internet era, and now it is at the peak of the dividend in the mobile Internet era. All applications of mobile phones are grown on the iOS platform or Android platform.
If the next era is the Internet of Things era, will it be possible to travel an operating system similar to iOS or Android, empower enterprises based on the development of IoT devices, or improve enterprise efficiency based on development environment, application environment, iterative upgrade environment and precipitation data?
In the past, the construction of smart cities was mostly information-centered, or scene-centered. We believe that the next stage is people-centered, and people-centered needs to consider that as a service-oriented city, it needs a strong hub and base.