Instrumenting wireless sensor networks for real-time surveillance

On August 30, 2005, we successfully demonstrated a large-scale, real-time, surveillance and control application on a wireless sensor network. The task was to track multiple human targets walking through a 5041 square meter sensor field and dispatch simulated pursuers to capture them. We employed a multi-target tracking algorithm that was a combination of a multi-sensor fusion algorithm for fusing binary detections and a Markov chain Monte Carlo data association (MCMCDA) algorithm that can initiate and terminates tracks autonomously and is robust to a high level of false alarms and missing measurements, a common problem in sensor networks. The tracks were used by a multi-agent coordination and control algorithm to capture the evaders. We were able to demonstrate successful pursuit of two crossing targets and successful tracking of three targets moving through a 144 node sensor field. To the authors' best knowledge, this experiment is the largest demonstration to date of a real-time tracking and control system on a wireless sensor network that does not use classification information