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The Chaotic Video Surveillance in Mobile Camera Sensor Networks: Improving the Efficiency and Security

机译:移动相机传感器网络中的混沌视频监控:提高效率和安全性

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摘要

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.
机译:近年来见证了相机传感器应用的快速发展。传感器和摄像头无处不在。然而,在传统的相机传感器监视应用中存在一些问题。首先,摄像机传感器的位置是固定的,因此监视范围受到限制。其次,存在潜在的安全问题,因为犯罪嫌疑人可以事先进行现场调查,然后在进行犯罪活动时绕开监视区域。针对这些问题,本文介绍了一种移动视频监控方法,不仅可以扩大监控范围,而且可以提高安全性。首先,我们设计了Stadia蚁群算法(SACA)以提高监视效率。基于该算法,设计了一种混沌路径规划算法(CPPA),使摄像机传感器的移动路径无法预测,从而保证了监控的安全性。此外,实现了带有移动相机的原型系统。大量的仿真实验验证了该方法的有效性,该方法是对现有固定监视系统的改进。

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