Dynamic cluster structure for object detection and tracking in wireless ad-hoc sensor networks

Wireless ad-hoc sensor networks are being developed to carry out tasks such as target detection and tracking, environment monitoring, and data collection across the area of deployment. We explore the problem of using sensor networks to detect and track continuous objects, such as wild fire and bio-chemical material. The continuous objects are different from traditional one or many individual targets in that they are continuously distributed across a region and usually occupy a large area. These continuous objects tend to diffuse, increase in size, change in shape, or even split into multiple relatively smaller continuous objects. The fusion and dissemination of local boundary information becomes a very challenging problem. In the paper, we propose a dynamic cluster-based structure to track the movement of boundaries and facilitate the fusion and dissemination of boundary information in a sensor network.