Optimization of wireless video surveillance system for smart campus based on Internet of Things

In order to strengthen school security and build a wireless smart campus, this article optimizes the existing wireless video surveillance system based on the Internet of Things. This paper first optimizes the surveillance quality in the video surveillance system, and proposes a zero-copy buffer strategy, a network congestion suppression strategy, and a codec rate coordination strategy. Secondly, for the distributed wide area video surveillance system, a tracking optimization method based on multi-camera fusion is proposed. Finally, this paper constructs a Bayesian monitoring event modeling method based on genetic algorithm. Experimental results show that the optimized video surveillance system has basically stable delay, significantly reduced packet loss rate, and smooth video playback. This method can effectively realize the coordinated tracking of multiple cameras in a wide-area monitoring scenario, achieve high tracking and monitoring performance, and meet the requirements of smart campus construction.