A Practical Implementation of an Agriculture Field Monitoring Using Wireless Sensor Networks and IoT Enabled

In this work, we consider the problem of designing a state of the art energy-efficient wireless sensor network (WSN) practically deployed in a large field. The sensor nodes (SNs) are tasked to monitor a large region of interest (ROI) and report their test statistics to the fusion center (FC) over a wireless fading channel. To maximize the lifetime of the WSN and enable long range communication with minimal transmit power, the long range wide area network (LoRaWAN) communication protocol is adopted. Each of the SN is designed and enabled with several state of the art sensors in order to estimate different and diverse parameters of interest (e.g., soil moisture, soil temperature, and salinity at different soil depth; barometric pressure, ambient humidity, leaf wetness, and etc.). The core feature of the proposed solution is that the SNs learn and adopt over the sensing time. This is very important in extending the operational lifetime of the WSN. The proposed system is validated through the infield experiments using few concept devices. Experimental results show that the proposed WSN features an effective large ROI monitoring with minimal number of SNs, a significantly reduced SN transmission power required and thus an extended WSN operational lifetime.