Efficient Environmental Temperature Monitoring Using Compressed Sensing

Ali Hashemi, Mohammad Rostami, Ngai-Man Cheung

Abstract: This paper proposes a novel compressed sensing (CS) framework that exploits (i) the sparsity of the samples in some representation domain, and (ii) the governing structure of the samples, with a focus on temperature monitoring using Wireless Sensor Networks (WSN). WSN's have been used for temperature monitoring for automation and surveillance. Despite the benefits, WSN's have their own limitations in spatial and temporal resolution. We propose to tackle these problems by using CS for spatiotemporal temperature source reconstruction. We propose a Diffusive Compressive Sensing (DCS) [1] framework to leverage the domain knowledge to increase efficiency of classic CS.