一种基于粒子群算法的视频监控网络覆盖优化方法

A Video Surveillance Network Coverage Optimization Method Based on Particle Swarm Optimization

针对视频监控网络的覆盖优化问题,以提高监控网络的覆盖率和减少设备数量为优化目标,提出一种基于粒子群算法的多目标优化方法。该方法考虑视频监控的有向感知性和可转动的特点,动态控制监控设备的位置和活动范围,并利用粒子群算法对覆盖的里程、设备数量、路段数等多个优化目标进行协同优化。实验结果表明,利用粒子群算法得到的优化结果,能够兼顾多个优化目标,有效提高监控网络的覆盖范围,同时减少设备投入。

Aiming at the coverage optimization of video surveillance network,a multi-objective optimization method based on particle swarm optimization is proposed to improve the coverage of the surveillance network and reduce the number of devices.This method considers the directional perception and rotatable characteristics of video surveillance,dynamically controls the location and activity range of surveillance equipment,and uses particle swarm optimization algorithm to co-optimize multiple optimization objectives such as covered mileage,number of equipment,number of intersections,etc.And the experimental results show that the optimization results obtained by using particle swarm optimization can take into account multiple optimization goals,effectively improve the coverage of the monitoring network,and reduce the equipment investment.