Abstract

Video surveillance systems have become a critical tool for urban management in recent decades. Without visiting the scene, managers may grasp the scene information. The monitoring system can improve management and supervision effects and reduce the likelihood of major accidents. With both the invention of the Internet of Things (IoT) era, however, sensor networks face difficulties, like massive access to equipment, massive data, inadequate bandwidth, attack vulnerability and real-time surveillance problems. We provide an overview of the implementations situation of the visual supervision system accordance with the project blockchain and border computers. The framework uses BCs, edge processors, developments from the IPFS and transformed neural networks. Edge computing is used for huge wireless communication collection and analysis. The IPFS storage service can be used and CNN infrastructure is used in legitimate surveillance to do a large video collection.

Full Text
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