Optimal Camera Placement for Providing Angular Coverage in Wireless Video Sensor Networks

Abstract

Wireless Video Sensor Networks (WVSNs) provide opportunities to use large number of low-cost low-resolution wireless camera sensors for large-scale outdoor remote surveillance missions. Camera sensor deployment is crucial in achieving good coverage, accuracy and fault tolerance. In particular, with the decreased costs of wireless cameras, redundant camera deployment is attractive in order to get multiple disparate views of events for improved event identification. If the capturing of an event spans ${ 360^\circ}$ , this is referred to as angular coverage. In this paper, we consider the problem of determining optimal camera placement to achieve angular coverage continuously over a given region. We develop a bi-level algorithm to find the minimum-cost camera placement. In the first level, we run a master problem that identifies the camera placement points to achieve angular coverage of a discrete set of points selected from the region of interest. Next, we use a sub-problem to identify points in the continuous region that are not covered by the cameras placed in the previous run of the master problem. We then add these uncovered points to discrete point set of the master problem and re-run the master problem. We continue running the master and sub-problems iteratively until the sub-problem becomes infeasible indicating that the entire region is covered. In the numerical experiments, we consider two cases 1) placement of homogeneous cameras with fixed resolutions; and 2) placement of heterogeneous cameras with different characteristics and resolutions. We also introduce varying resolution requirements for different parts of the region and place the cameras such that the required resolution is satisfied. The numerical results show the superiority of the bi-level approach respect to existing approaches.