Implementation of Compressive Sensing Algorithm for Wireless Sensor Network Energy Conservation

Huge data processing contributes many factors in wireless sensor network such as network traffic and energy constraint. Using compressive sensing a new technique in data acquisition which reduced the required sampling rate to reconstruct the original signal will therefore lessen the power consumption. This paper will implement the compressive sensing algorithm of the wireless sensor network installed in the greenhouse. The primary objective of the design is to reduce the power consumption on wireless system network by maximizing the data packet payloads while minimizing the transmission activity of the Wireless Sensor Network. The sensor and receiver node consumes more power when transmission of data is taking place. The main contributions of this paper are to apply the compressive sensing algorithm in the greenhouse monitoring system to lessen the power consumption of the WSN, to serve as a reference for the new design of analog to digital converter using sampling rate lower than the traditional Nyquist rate and to give ideas to other researchers that compressive sensing can be applied to other WSN applications. This study will do the compression of the measured data in the sensor node and transmit it over a specified time. Matlab will be used to simulate and recover the original signal for verification of the results. The results will compare the power consumption of the existing system of the Precision Agriculture group in our laboratory.