Coverage Optimization Of Visual Sensor Networks

With the rapid development of information technology,visual sensor networks have received extensive attention because of their rich visual perception capabilities.Visual sensor networks are equipped with a camera device,which can collect physical data information such as images and videos,and can be used for monitoring of various environments.Aiming at the problem of visual sensor network coverage optimization,this paper considers the special directional coverage characteristics of visual sensors,constructs a corresponding perception model,and proposes a fast iterative optimization algorithm based on fuzzy thinking.On this basis,an improved algorithm is proposed from a distributed perspective,and analysis and simulation are performed.The research contents of this paper are as follows:1.Based on the attenuation sensor model of visual sensor,the "total coverage intensity" optimization target is constructed,and a fast iterative algorithm based on coverage overlap rate is proposed.The algorithm combines greedy thoughts,and the sensor selects the optimal deployment in the current state as the target position at the next moment in the optimization iteration process.The key problem of the algorithm is to set the time-varying and inconsistent sensor control gain.In addition,a distributed condition that uses the sensor " coverage overlap rate" is proposed to trigger the change of control gain.The time-varying gain and distributed triggering conditions ensure that the sensor network achieves higher coverage after fewer iterations.2.Considering the geometric constraints of sensor network deployment from a distributed perspective,the concept of convex hull is introduced into the problem of coverage optimization,and the concept of " convex hull of visual field " of visual sensors is proposed.Based on the convex hull of the field of view,we define a novel coverage index—sensor density,which is used to evaluate the local coverage efficiency of the vision network.In the design of sensor control law,fuzzy control theory is used,and a fast iterative algorithm based on fuzzy thoughts is proposed.The time-varying and inconsistent sensor control gains are obtained through the fuzzy controller,including the coordinate change and heading angle change.The simulation experiment results verify that the proposed algorithm has obvious advantages in coverage optimization iteration steps and coverage.