Ascending hierarchical classification for camera clustering based on FoV overlaps for WMSN

Abstract

Wireless multimedia sensor networks (WMSNs) currently face the problem of rapidly decreasing energy due to the acquisition, processing and transmission of massive multimedia data. This decrease in energy affects the life of the network, resulting in higher overhead costs and a deterioration in quality-of-service. This study presents a new grouping strategy that somewhat reduces energy reduction problems. The objective is to group cameras in the WMSN according to their field of view. The proposed system begins by searching for all polygons created by the intersection of the two cameras' FoV. Based on the generated surfaces, an ascending hierarchical classification is applied to group cameras with strongly overlapping visions fields. The results obtained with 300 randomly positioned cameras show the effectiveness of the proposed method to minimise redundant detection, reduce energy consumption, increase network life, and reduce network overload.