The chaotic video surveillance in mobile camera sensor networks: improving the efficiency and security

Recent years have witnessed the rapid development of camera sensor applications. Sensors and cameras are deployed everywhere. However, there are several problems in traditional camera sensor surveillance applications. First, the positions of the camera sensors are fixed so that the surveillance range is limited. Second, there is a potential security issue since criminal suspects can make an on-the-spot investigation in advance and then circumvent the surveillance area while committing criminal activities. To solve these problems, we introduced a mobile video surveillance method in this paper, which can not only extend the monitoring range, but also improve the security. We firstly design a Stadia Ant Colony Algorithm (SACA) to improve the surveillance efficiency. Based on this algorithm, a Chaotic Path Planning Algorithm (CPPA) is designed to make the moving paths of camera sensors unpredictable, which ensures the security of surveillance. Moreover, a prototype system with mobile cameras is implemented. Extensive simulation experiments validate the effectiveness of the proposed method which is an improvement of existed fixed surveillance systems.