Recently, in the 7th China Postgraduate Smart City Technology and Creative Design Competition, the graduate team of the School of Computer Science and Communication Engineering of our school (members: Wu Bin, Liang Sai, Meng Chunyun, He Xiaobing, instructor: Cheng Keyang) made outstanding achievements and won the second prize of the country with the entry "COVID-19 Connector Identification and Tracking System for Major Sports Events".

The China Postgraduate Smart City Technology and Creative Design Competition is one of the theme competitions of the "China Postgraduate Innovation and Practice Series Competition". It is a national event jointly sponsored by the China Association for Academic Degrees and Graduate Education and the Youth Science and Technology Center of the China Association for Science and Technology under the guidance of the Department of Degree Management and Graduate Education of the Ministry of Education. It is widely recognized by domestic and foreign graduate training units and enterprise industries. The final of the 7th China Postgraduate Smart City Technology and Creative Design Competition will be held in Shanghai on August 13, 2022. A total of 6716 postgraduates from 2034 teams will participate in the competition, and 18 first prizes, 30 second prizes and 56 third prizes will be awarded to the winning teams, with an award rate of only 5%.

Aiming at the problems of poor real-time screening, low efficiency of screening, and inability to track secret contacts existing in major sports events during the epidemic period, this entry designed and implemented a COVID-19's secret contact identification and tracking system for major sports events: 1) using pedestrian re identification and camera logical topology reasoning technology to achieve the identification function of COVID-19 patients and secret contacts; 2) Combining LSTM time series model and YOLO algorithm to realize real close contact identification of patients; 3) Using the multi-target tracking algorithm of end-to-end data association, the movement trajectory of the patient and the contact person is drawn; 4) The risk grade assessment of COVID-19 risk area is realized through FFM (Field Perception Decomposition Machine) model. The system can effectively improve the efficiency of epidemic prevention, reduce the economic and epidemic prevention pressure of the event organizers, and improve the participation rate and safety of spectators.