Abstract
Barrier coverage, an important research area with respect to camera sensor networks, consists of a number of camera sensors to detect intruders that pass through the barrier area. Existing works on barrier coverage such as local face-view barrier coverage and full-view barrier coverage typically assume that each intruder is considered as a point. However, the crucial feature (e.g., size) of the intruder should be taken into account in the real-world applications. In this paper, we propose a realistic resolution criterion based on a three-dimensional (3D) sensing model of a camera sensor for capturing the intruder’s face. Based on the new resolution criterion, we study the barrier coverage of a feasible deployment strategy in camera sensor networks. Performance results demonstrate that our barrier coverage with more practical considerations is capable of providing a desirable surveillance level. Moreover, compared with local face-view barrier coverage and full-view barrier coverage, our barrier coverage is more reasonable and closer to reality. To the best of our knowledge, our work is the first to propose barrier coverage for 3D camera sensor networks.
Highlights
Barrier coverage of wireless sensor networks is a fundamental issue where the objective is to construct a long narrow barrier belt area of sensors to detect intruders that attempt to cross the deployed region
Previous studies on barrier coverage mainly focused on traditional scalar sensor networks, in which the sensing range of a sensor is often modeled as a disk and an object is said to be covered or detected by a sensor if it is within the sensing range of the sensor [11,12]
This paper presented a new resolution criterion based on 3D sensing model of camera sensors
Summary
Barrier coverage of wireless sensor networks is a fundamental issue where the objective is to construct a long narrow barrier belt area of sensors to detect intruders that attempt to cross the deployed region. The issues of barrier coverage have been discussed in traditional scalar sensor networks [7,8] and camera sensor networks [9,10], respectively. Previous studies on barrier coverage mainly focused on traditional scalar sensor networks, in which the sensing range of a sensor is often modeled as a disk and an object is said to be covered or detected by a sensor if it is within the sensing range of the sensor [11,12]. Compared with traditional scalar sensors, camera sensors can provide much richer information about the environment in the forms of images or videos and have huge potential in applications
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