Using Rotatable and Directional (R&D) Sensors to Achieve Temporal Coverage of Objects and Its Surveillance Application

Due to hardware design or cost consideration, sensors may possess sector-like sensing coverage. Furthermore, by stepper motors, sensors can rotate to cover the objects around them. This type of sensors are called rotatable and directional (R&D) sensors. Through rotation, R&D sensors provide temporal coverage to objects by "periodically” detecting their existence. In the paper, we first develop an event-driven surveillance system by R&D sensors, where objects are monitored by the sensors equipped with infrared detectors and cameras. When an object is taken away, the sensor monitoring the object reports a warning message along with detailed snapshots from the surroundings. Then, motivated by the system, we formulate an R&D sensor deployment problem, which tries to deploy the minimum number of R&D sensors to cover a given set of objects such that each object is covered by 0 < \delta \le 1 ratio of time in every frame. We show this problem to be NP-hard and propose two efficient heuristics. The maximum covering deployment (MCD) heuristic iteratively deploys a sensor to cover more objects, and performs well when objects congregate together. The disk-overlapping deployment (DOD) heuristic deploys sensors to cover the joint sectors of overlapped disks, so it works better when objects are arbitrarily placed in the sensing field. The paper contributes in defining a new temporal coverage model by R&D sensors, developing a surveillance application for this model, and proposing efficient heuristics to reduce the deployment cost.