Design And Implementation Of Video Quality Detection System Based On Edge Computing

With the continuous increase of urban scale,public safety is very important for urban stability.Many video surveillance systems are widely deployed in cities and surrounding areas.With the continuous expansion of the monitoring range,the number of cameras contained in the system is also increasing,which has brought many problems to the video monitoring and maintenance,and video quality detection is one of the core problems.The video quality diagnosis algorithm based on edge computing can detect common video anomalies.The proposed video failure detection scheduling algorithm can effectively reduce the mean time to detection and the waste of computing resources by dynamically adjusting the order and detection cycle of the detection queue.At the same time,the edge cloud collaborative video quality monitoring scheme realizes the edge cloud data collaboration and edge cloud application management collaboration.The edge video quality diagnosis load balancing scheme can reasonably allocate the edge video quality diagnosis tasks,balance the computing load of each node and improve the utilization of computing resources.This paper strictly follows the design idea and process of software engineering,designs and implements the video quality detection system based on edge computing.On the basis of clarifying the function and performance requirements of the system,this paper determines the system architecture scheme,completes the analysis and design of each functional module and interface of the system,then gives the implementation method of the system,and finally fully tests the system,The availability and effectiveness of the system developed in this paper are proved.The complete solution of video quality detection system based on edge computing proposed and implemented in this paper has been proved to be effective in the Internet of things competition.