N-queens-based algorithm for moving object detection in distributed wireless sensor networks
This addresses energy constraints in wireless sensor networks for applications like intruder detection, but appears incremental as it builds on existing moving object detection techniques.
The paper tackles the high energy consumption problem in wireless sensor networks for image communication by developing a local in-network image processing algorithm for intruder detection, achieving energy savings better than traditional techniques by a factor of (N/2).
The main constraint of wireless sensor networks (WSN) in enabling wireless image communication is the high energy requirement, which may exceed even the future capabilities of battery technologies. In this paper we have shown that this bottleneck can be overcome by developing local in-network image processing algorithm that offers optimal energy consumption. Our algorithm is very suitable for intruder detection applications. Each node is responsible for processing the image captured by the video sensor, which consists of NxN blocks. If an intruder is detected in the monitoring region, the node will transmit the image for further processing. Otherwise, the node takes no action. Results provided from our experiments show that our algorithm is better than the traditional moving object detection techniques by a factor of (N/2) in terms of energy savings.