Compressed Sensing for Energy Conservation Pavement Temperature Compression on Epave

Monitoring the road condition has gain significant importance in last few years. Among existing road monitoring technologies, wireless sensor network (WSN) is favored by researchers because of its low cost and flexibility in deployment. Specifically, it can collect road condition data spontaneously and transmit the information to a fusion center that can determine the damage level or status of the road surface. However, there is a big challenge preventing the wide deployment of WSN that the sensor nodes can only survive for a limited time in practice. It is because majority of the power has been spent on the continuous wireless transmission of the extensive road data to the fusion center. In this study, we propose a low-power temperature data transmission scheme based on compressed sensing in combination with self-powered road surface wireless monitoring sensor system to realize data sparseness and compression and reduce system power consumption. Experimental results show that the compressed data can reduce the power consumption requirement by 50.78% under the allowable reconstruction error by comparison with the existing approaches.