A video surveillance network coverage optimization method based on particle swarm optimization

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.