基于云解码的视频流智能分析管控技术OA

Aiming at the problems in real-time processing of massive video streams,such as insufficient terminal computing power,high transmission delay,unbalanced task scheduling,and difficulty in balancing recognition accuracy and speed,a cloud decoding intelligent management and control system integrating WebRTC real-time transmission,improved genetic algorithm scheduling,"hardware+algorithm"video coding and decoding acceleration,and optimized YOLOv8-tiny recognition is proposed.A three-level"terminal-edge-cloud"architecture is designed,and through the collaborative optimization of multiple technologies,the following effects are achieved:transmission delay≤80 ms,video coding and decoding speed increased by 45%-60%compared with traditional schemes,abnormal event recognition accuracy reaching 93.2%,and terminal computing power demand reduced by 70%.Verification in urban security and industrial monitoring scenarios shows that this system can meet real-time management and control requirements and provide an efficient solution for intelligent video stream applications.