Coverage Overlaps Reduction with Delaunay Triangulation for Visual Sensor Networks

Abstract

A visual sensor network (VSN) employs visual (camera) sensors instead of scalar sensors to establish the wireless network for wide area monitoring and target tracking. The visual sensing coverage of a VSN is quite related to the sensing direction and sensing angle of each camera sensors in the network. Many research issues of VSNs are similar but much different from the ones of ordinary scalar sensor networks, and the visual coverage issue is more specific. In the past years, a great number of research literatures have been proposed to address the coverage issues for ordinary scalar sensor networks. A part of the existing approaches use geometric structure concepts in the researches. However, utilizing geometric structures to solve visual sensing coverage has not drawn much attention of researches. This study, therefore, utilizes a geometric structure of Delaunay Triangulation with its characteristics to improve overall visual coverage of a sensing field for VSNs. The results of evaluation with simulations show the proposed approach performs very well and obtains a significant visual coverage improvement for VSNs. This could be a reference basis for further studies.