Abstract
In recent decades, video surveillance systems have become an indispensable management tool for cities. Managers can grasp the information of the scene without visiting the scene. Through the surveillance system, the effect of management and supervision can be improved, and the probability of major accidents can be reduced. However, with the advent of the Internet of Things (IoT) era, video surveillance systems will face challenges such as massive equipment access, massive data, insufficient bandwidth, vulnerable to attack, and real-time monitoring difficulties. Based on the analysis of the research and application status of video surveillance system, we propose a video surveillance system based on permissioned blockchains (BCs) and edge computing. The system uses permissioned BCs, edge computing, InterPlanetary File System (IPFS) technology and convolution neural networks (CNNs). The edge computing is used to achieve large-scale wireless sensor information acquisition and data processing. IPFS storage service is used to realize massive video data storage, and CNNs technology is used to realize real-time monitoring.
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