Optimization algorithm for coverage optimization of directed video sensor networks in multi-obstacle environments in decentralized sites

Abstract

In the process of engineering construction, the use of directed video sensors for resource sensing helps to understand the site resource situation, so that strategic adjustments can be made in response to emergencies, but when in a multi-obstacle environment, the resource sensing efficiency is low. Aiming at the characteristics of Yichang two-network project with scattered sites and multi-obstacle environment, it is necessary to study the optimization algorithm of directed video sensor network coverage under scattered sites and multi-obstacle environment to improve the ability of key resource sensing in the field. Using the probabilistic sensing model of directed sensors, multi-obstacle node optimization, node reciprocating motion optimization, boundary problem optimization and virtual force optimization, and considering the variability of node positions, we propose the optimization algorithm for the coverage of directed video sensor networks in a decentralized site with multi-obstacle environments. The experimental result show that the algorithm is optimized to improve the network coverage by 12.03%, which is a higher enhancement of network coverage and better applicability to directed video sensors with different parameters.The optimization algorithm is more applicable to different environments as well as different parameters of directed video sensors, which can provide a reference for the deployment of surveillance cameras in the actual Yichang two-network project, and help to improve the coverage of the surveillance network in the site of the Yichang two-network project.

Keywords

Yichang two-network project / directed video sensor / resource sensing / network coverage algorithm