Multi-moving-target dynamic monitoring optimization method based on diploid genetic algorithm in video sensor network

Abstract

Disclosed is a multi-moving-target dynamic monitoring optimization method based on a diploid genetic algorithm in a video sensor network. The method comprises deploying video sensor nodes randomly inside a monitored area; linearly predicting the positions of moving targets at a next moment; providing a process on how to base on the diploid genetic algorithm to schedule toe video sensor nodes to dynamically monitor the moving targets. The multi-moving-target dynamic monitoring optimization method based on the diploid genetic algorithm in the video sensor network can help compute out the required rotating angle of every monitoring node for covering as many as the moving targets, then comprehensively compute an optimal solution through a server and finally inform all the nodes to rotate. The multi-moving-target dynamic monitoring optimization method based on the diploid genetic algorithm in the video sensor network can effectively improves the covering quality of multiple moving targets, dynamically monitor the multiple moving targets and provide possibility for achieving efficient multi-target dynamic monitoring through the diploid genetic algorithm.

Description

technical field [0001] The invention belongs to a video sensor network, in particular to a method for monitoring and optimizing multiple moving targets in a video sensor network. Background technique [0002] The video sensor network has the ability to perceive, collect, process and transmit multimedia information such as data, images and videos. It is an effective means of state perception, information collection and target tracking. Application prospect. [0003] Although the video sensor network is becoming more and more mature, according to the existing research results, most of the target coverage problems are carried out for static targets. For the continuous monitoring of moving targets with random characteristics and the research of multi-moving target coverage It is still relatively lacking, which directly affects the real-time monitoring quality of the monitoring system. Therefore, it is very important to study the optimization strategy of multi-moving target mon...

AI Technical Summary

Problems solved by technology

[0008] In order to overcome the poor coverage quality of multiple moving targets in the existing video sensor network target monitoring method and the inability to meet the shortcomings of dynamic monitoring of multiple moving targets, the present invention provides a global optimization for each moment to effectively improve the quality of multiple moving targets. The coverage quality of the video sensor network based on the diploid genetic algorithm to realize the optimization method of multi-moving target dynamic monitoring in the coverage maximization

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