Energy Efficient Target Coverage in Wireless Visual Sensor Networks

Abstract

For wireless visual sensor networks, due to high redundancy incurred, it is possible to both preserve energy and enhance coverage quality by first switching off some sensors and then adjusting the orientations of the remaining ones. In this paper, we propose a novel method to automatically configure WVSN in order to maximize coverage and network lifetime in indoor environments. Based on a suitable modeling of cameras and environment, the optimization procedure determines the most appropriate camera position and settings to fulfill a given coverage objective. To achieve this goal, we use a particle swarm optimizer with an appropriate fitness function that takes into account a number of concurrent metrics and constraints. Simulation results show that our proposed approach has greater energy efficiency and can extend the network lifetime, as compared with prior approaches.