Experiments in Instrumenting Wireless Sensor Networks for Real-Time Surveillance (Video)

Phoebus Chen, Songhwai Oh, Michael Manzo, Bruno Sinopoli, Cory Sharp, Kamin Whitehouse, Gilman Tolle, Jaein Jeong, Prabal Dutta, Jonathan Hui, Shawn Schaffert, Sukun Kim, Jay Taneja, Bonnie Zhu, Tanya Roosta, Michael Howard, David Culler, and Shankar Sastry

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.

International Conference on Robotics and Automation (ICRA), Orlando, FL, May 2006

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