Design And Implementation Of Video Based Abnormal Event Early Warning System In Smart Pipe Gallery

With the rapid development of the economy,problems such as low operation and management level of urban underground comprehensive pipe gallery have emerged.Therefore,the smart pipe gallery came into being.Smart pipe gallery uses modern information and communication technologies such as the Internet of Things,big data,and cloud computing to make the management and operation of pipe gallery more efficient.Information management system of smart pipe gallery based on the IoT cloud platform is the "brain" of the smart pipe gallery,which can enhance the emergency handling capacity of the pipe gallery and reduce the risk of accidents.The supporting function brings great convenience to the operation and maintenance staff of the pipe gallery and makes the management and operation of the city more efficient.The research content of this article is one of the sub-modules of the smart pipe gallery system based on the IoT cloud platform.Video surveillance is one of the important modules in this system.In order to improve the comprehensive management efficiency of smart pipe gallery and the utilization rate of video surveillance content,this paper proposes a design and implementation scheme of a video-based abnormal event early warning system in smart corridors.This solution uses FFmpeg(Fast Forward MPEG),edge computing,deep learning and object detection technology to access surveillance camera video data and filter detection results according to set rules.This system can reduce the probability of false positives,provide intelligent early warning of abnormal events and greatly reduce the corridor risk of accidents and operation and maintenance labor costs.