Power-Efficient Target Tracking and Coverage in Under-Provisioned Wireless Visual Sensor Networks

Due to their ability to detect the physical environment, directional sensors have attracted a lot of attention in wireless visual sensor networks (WVSN). These sensors perform two key functions: communication and sensing. A WVSN comprises numerous configurable limited fields of view sensors, comprising distinct angular sectors, arranged with multiple targets randomly scattered in the same surrounding region. Therefore, there is a critical need to improve the network's lifetime and reduce power demand while providing complete target coverage. This paper looks at under-resourced visual networks with an inadequate number of sensors to match applications' needs and develops a viable model to expand coverage of moving targets in low-sensors scenarios. The resulting sustainable approach focuses mainly on the use of the existing Iterative Target Oriented Algorithm (ITOA). We present a modernized version of this algorithm, called MITOA, capable of efficiently accounting for covering moving targets across energy-limited WVSNs that are built with Pan Tilt Zoom (PTZ) camera sensors. Here we investigate directed sensor scope with changing orientation under a randomized deployment model of sensors and targets with objectives in order to reduce energy consumption for under-provisioned visual sensor networks. Experimental evaluations through MATLAB simulations demonstrate that MITOA improves network energy savings by 42% as compared to classical ITOA.