Video Recognition-Based Emergency Event Early Warning System

This paper designs and develops an intelligent early warning system based on emergency event recognition, centered on the innovative needs in the security field, aiming to provide comprehensive and accurate security warning services for public security departments, transportation hubs, campuses and scenic spots and other user groups to provide comprehensive, timely and accurate security warning services. The platform enhances the safety protection ability of public places through the core functions of emergency event recognition and warning, AI emergency linkage disposal, and cross-camera target tracking. The system can accurately identify more than 20 types of emergency events, including violent conflicts, abnormal vehicle movement, fire events, etc. It adopts 3DCNN-based video abnormal behavior event detection algorithm and graph convolution network-based human violence detection algorithm to automatically locate and accurately analyze the abnormal events, and the system is equipped with multi-camera collaborative operation capability, and with the help of federated learning technology, it realizes target tracking in the whole area. At the same time, the system uses Echarts and other tools for visualization and big data analysis. With the development of intelligence, the platform is expected to form a closed-loop management system of “intelligent perception-accurate warning-rapid response-coordinated disposal”, which will greatly enhance the overall security resilience of society and the efficiency of emergency disposal. [1]