Sparsity-driven bandwidth-efficient decentralized tracking in visual sensor networks

Sparsity-driven bandwidth-efficient decentralized tracking in visual sensor networks

Recent developments in low-cost CMOS cameras have created the opportunity of bringing imaging capabilities to sensor networks and a new field called visual sensor networks (VSNs) has emerged. VSNs consist of image sensors, embedded processors, andwireless transceivers which are powered by batteries. Since energy and bandwidth resources are limited, setting up a tracking system in VSNs is a chal...

Improving Energy-Efficient Target Coverage in Visual Sensor Networks

Target coverage is one of the important problems in visual sensor networks. The coverage should be accompanied with an efficient use of energy in order to increase the network lifetime. In this paper, we address the maximum lifetime for visual sensor networks (MLV) problem by maximizing the network lifetime while covering all the targets. For this purpose, we develop a simulated annealing (SA) ...

Mathematical Analysis of Optimal Tracking Interval Management for Power Efficient Target Tracking Wireless Sensor Networks

In this paper, we study the problem of power efficient tracking interval management for distributed target tracking wireless sensor networks (WSNs). We first analyze the performance of a distributed target tracking network with one moving object, using a quantitative mathematical analysis. We show that previously proposed algorithms are efficient only for constant average velocity objects howev...

improving energy-efficient target coverage in visual sensor networks

target coverage is one of the important problems in visual sensor networks. the coverage should be accompanied with an efficient use of energy in order to increase the network lifetime. in this paper, we address the maximum lifetime for visual sensor networks (mlv) problem by maximizing the network lifetime while covering all the targets. for this purpose, we develop a simulated annealing (sa) ...

Coverage Quality in Visual Sensor Networks