Impact on Compressed Sensing for IoT Used Indoor Environment Monitoring System

Abstract

This paper proposes a method to save power consumption for Wireless Sensor Network (WSN) based environment monitoring system by using compressed sensing technique. Reconstruction process of compressed sensing data is complicated but compressed process is itself simple. On the other hand, although sensor nodes can use limited resources, the server has affluent resources. Therefore, sensor nodes compress time series measured environment data and the server reconstruct the compressed data. At the environment data collection stage, a sensor node uses compressed sensing for transmitting measured environment data. The server reconstructs the received environment data. This study develops the ZigBee WSN based time series indoor environment data collection system. Then this study investigates the impact on compressed sensing technique for WSN. Experiment results show that when setting compression ratio = 40%, the power consumption was reduced by 40% with satisfying the coefficient of determination > 0.8, which showed the effectiveness of the proposed method.