On September 2, 2024, our laboratory conducted an in-depth project docking and exchange activity with the Shanghai High-Tech Development Center. This meeting originated from the fact that business representatives from the Shanghai High-tech Development Center showed strong interest in the platform after watching the platform’s roadshow project display during the Shanghai International Technology Import and Export Fair (Shanghai International Technology Import and Export Fair), and then took the initiative to contact the laboratory. , hoping to further understand and explore the possibility of cooperation.
During the event, Dr. Huiyu Zhi of the laboratory reported in detail the current status of the platform and introduced the research progress achieved by the project around intelligent analysis, control and optimization collaboration of smart city CPS systems. With the explosive growth in the number of IoT devices and the increasing demand for smart city applications, how to achieve efficient collaboration between the large-scale information world and the physical world has become the focus of academia and industry. This project aims to develop a visual information analysis system based on the physical and logical framework of smart cities based on ultra-complex network systems, and to study the feedback closed-loop control method between the information world and the physical world to support the operation and command and dispatch of new smart cities.
The project team also demonstrated dynamic visualization technology and software systems based on ultra-complex network theory and multi-layer, multi-dimensional, dynamic network structure feature analysis of smart city CPS systems. These technologies have been applied and verified in many fields such as smart transportation, smart fire protection, and smart parks, and have achieved remarkable results. The cooperation with Wuxi Mobile and Jiangsu Tianan Intelligent Technology Co., Ltd. is a typical case. The application of traffic signal collaborative control evolution technology and signal-object visualization technology based on reinforcement learning effectively reduces vehicle driving time and provides more Precise traffic control decisions.
In the subsequent interactive session, Professor Han Dingding patiently answered various questions from visitors and elaborated on the application prospects and cooperation possibilities of platform technology. At this event, Mr. Liu, the enterprise representative of a smart parking-related company in Wenzhou, came to communicate and expressed that he was very interested in the project and discussed the possibility of technical cooperation and market application. The successful demonstration of the project not only laid the foundation for future cooperation, but also provided broader technical support for the development of smart cities.
Professor Han Dingding, the person in charge of the platform, said that in the future, he will continue to deepen cooperation with enterprises to jointly promote the industrial application of smart city CPS system technology and assist the efficient management and sustainable development of smart cities.
