On September 27, a cooperation agreement was signed between Tongji University and Shanghai Urban Operations Management Center (SUOMC) and joint achievements were released at the hall of SUOMC.
Executive Vice Mayor CHEN Yan, Vice Secretary-General of the Shanghai Municipal Government and SUOMC Director ZHAO Qi, Tongji University’s Party Secretary FANG Shouen, President CHEN Jie, Executive Vice President WU Jiang, Vice President GU Xianglin and Assistant President TONG Xiaohua attended the signing ceremony, which was chaired by Deputy Secretary of the Shanghai Municipal Government’s Office, and SUOMC Deputy Director XU Huili. Witnessed by CHEN Yan, ZHAO Qi, FANG Shouen and CHEN Jie, WU Jiang and XU Huili signed the agreement on behalf of both sides.
People from both sides at the ceremony
Signing the agreement
SUOMC is responsible for Shanghai’s urban operation management, emergency system planning, construction, and maintenance, urban operation monitoring, and coordination of joint emergency actions. It is making all efforts to fully implement the "one-network-for-all management" policy. The cooperation agreement between Tongji University and SUOMC aims at taking the advantages of both parties to further promote the cooperation in innovation, to empower Shanghai's economic and social development and urban operation and management, and to enhance the governance capacity of this international metropolis. Tongji University will give full play to its academic strengths in artificial intelligence technology, urban operation, and management, as well as to the expertise from the Shanghai Research Institute for Intelligent Autonomous Systems (SRIFIAS) led by Tongji through making good use of the resources and data aggregation capabilities at SUOMC in its efforts to contribute Tongji’s wisdom In Shanghai's urban construction and governance.
According to XU Huili, Tongji University had demonstrated its resources and expertise in AI in its wide range of cooperation with SUOMC even at the preparatory stage of SUOMC. President CHEN Jie served as Head of SUOMC's Artificial Intelligence Expert Group in support for SUOMC's construction.
After the signing ceremony, a briefing of joint achievements was made. Vice President GU Xianglin reported on the joint research results of SRIFIAS and SUOMC, detailing the achievements and application cases of both sides in critical technologies of urban management, major risk prevention and emergency management technology of urban operation. He also introduced Tongji University's latest development in the training of talents in automated hospitals and intelligent technology at both undergraduate and postgraduate levels. He mentioned that Tongji will continue to provide more technical and personnel support for Shanghai's urban operation and management in the future.
GU Xianglin demonstrating AI application cases
Seven joint research results of AI involving intelligent, autonomous, system, domain-wide, fine-perception technology, high real-time one-screen integrated digital twin management system, major risk prevention and emergency management system for urban operation were jointly released, which had turned out beneficial to the pandemic prevention, emergencies response, and operation and maintenance of facilities in the city. Since April of this year, Tongji University and SUOMC have cooperated comprehensively in the fields of policy-making, industry and research by pooling the advantages of professional management and scientific research personnel while focusing on the critical areas of urban operation. Their continued efforts are intended to promote the significant convergence of technology, services, data, and other elements, and making breakthroughs in promoting the overall perception, autonomous coordination, and automatic identification of urban operation and management. The intelligent prevention and control technology of major public health events released so far include: the coordination of a multi-target, high-precision, multi-function robot; technology fusion of a visualization system; natural speech interaction; multi-mode recognition technology; high-precision positioning navigation and autonomous control; invention of the multi-dimensional fusion rapid sensing technology of pandemic physiological characteristics; development of a heterogeneous autonomous coordinated outbreak detection robot; construction of a large data tracer and transmission early warning model for primary pandemic prevention and control; and the proposal of the construction of tented hospitals and urban emergency resilience. The practice of these technologies will enhance the city's pandemic prevention capabilities further. "We will work with researchers to explore ways of promoting these new inventions and technologies, and use more artificial intelligence to improve the city's emergency response and pandemic prevention levels," said YANG Xiaodong, deputy director of the Shanghai Emergency Management Bureau, and ZHAO Dandan, deputy director of Shanghai Health and Safety Committee.
Tongji University officials also revealed ed the development of the Intelligent Support and Disease Diagnosis Model of the Municipal Network Operation Safety. and which have been a great concern by people at grassroots levels. This Model diagnoses the overall health status of the network through machine learning, classifies the diseases within the network through deep learning, quantifies the conditions and analyzes their causes, provides intelligent early warning, and proposes a solution for the abnormal weather conditions affecting the regular use of the urban network. Jiading District Operations Center Director LI Jian gave his quick response to this model. "When the results of AI technology and big data analysis and judgment are applied to Jiading District Operations Center in the future, it will help management personnel to anticipate risks in advance and take effective measures, because they are not only more focused, but more integrated in coordinating functions of urban operations".
Photo: ZHOU You
Video: SONG Yuxing
Source: https://news.tongji.edu.cn/info/1003/75111.htm
