Divide- and conquer-based surveillance framework using robots, sensor nodes, and RFID tags
Sensor networks are adopted in many surveillance applications. A traditional method for such applications is to deploy sensor nodes all over the surveillance region in order to cover as much area as possible. However, this way not only waste huge amounts of money for sensor nodes and resources, but it is also unnecessary and unrealistic sometimes. It provides huge amounts of garbage in the form of dead sensor nodes and batteries. It invokes many data collisions and places a serious burden on network protocols. In many applications, we have no need to have detail on every point inside the area, but only in some critical places. For example, in a forest fire surveillance application, covering the whole forest is unnecessary and unrealistic. In this paper, we propose a divide- and conquer-based surveillance framework, in which a large surveillance area is divided into small areas by critical points and critical lines. Sensor nodes, sinks, robots, and RFID tags are all used. We only deploy sensor nodes along critical lines instead of all over the region. Our aim is to do surveillance with efficient deployment of sensor nodes and sinks, and to detect, track, and even capture targets, e. g., an intrusion tank or forest fire, with the collaboration of robots and sensor nodes. We study boundary coverage along critical lines. Robots perform tasks of patrolling, handling incidents, communicating with sensor nodes/sinks, and even being capable of deploying/throwing-out sensor nodes/RFID tags. Finally, we evaluate perimeter coverage, robot patrol routing, and so on. Copyright (C) 2009 John Wiley & Sons, Ltd.
robot sensor rfid