On wireless video sensor network deployment for 3D indoor space coverage

Nowadays, wireless video sensor networks (WVSNs) play a prominent role in a wide range of security, industrial, medical and environmental applications. Unlike traditional sensors such as heat or light sensors often considered with omnidirectional sensing range, the sensing range of a video sensor can be deemed as a fan-shape in 2D and pyramid-shape in 3D, rendering the deployment solutions for traditional sensors and 2D sensing fields inapplicable and incapable of solving the WVSN deployment problem for 3D indoor space coverage. In this paper, we take the first attempt to address this by modeling the general problem in a continuous space and strive to minimize the number of required video sensors to cover the given 3D regions. We then convert it into a discrete version by incorporating 3D grids for our discrete model, which can achieve arbitrary approximation precision by adjusting the grid granularity. We propose a greedy heuristic and an enhanced Depth First Search (DFS) algorithm to solve the discrete version problem where the latter, if given enough time can return the optimal solution. We evaluate our solutions with a customized simulator that can emulate the actual WVSN deployment and 3D indoor space coverage. Our preliminary results demonstrate that our greedy heuristic can reduce the required video sensors by up to 50% over a baseline algorithm, and our enhanced DFS can achieve an additional reduction of video sensors by up to 20%.