Sensor Tasking for Occupancy Reasoning in a Network of Cameras

Abstract

In this paper, we study how to task camera sensor nodes to reason about the occupancy of the area around them. Occupancy information is valuable because it can be used to answer many other queries such as determining object tracks or the count of the number of people in an area. Camera sensors are challenging to include in a wireless sensor network (WSN) because they are high data rate devices. To save energy and to satisfy the bandwidth constraint, our camera nodes will only send a very limited amount of data and only a limited number of camera nodes will be tasked. Our r st result, from simulation, gives an upper bound on the number of cameras needed for a given accuracy in the occupancy. Given this number of cameras, we then compare several approaches to tasking the most relevant cameras both in simulation and in a real system of 16 camera nodes. Our incremental greedy tasking algorithm performed the best. Finally, we applied this tasking algorithm to a tracking application. We show that the tracker that used tasking outperformed the same tracker without tasking.