Smart Soil Parameters Estimation System Using an Autonomous Wireless Sensor Network With Dynamic Power Management Strategy

This paper presents the design of a wireless sensor network (WSN) system for smart estimation of soil conditions. The WSN is formed by very low-power autonomous sensor nodes and employs Internet of Things and cloud service communication protocols to generate spatial distribution maps of soil parameters at two different levels below ground. An artificial neural network is used to analyze the measured data and estimate the levels of phosphorus (P) in the soil. This feature eliminates the need to perform time-consuming laboratory analysis to continuously monitor the value of this nutrient. Considering the changing rate of soil phenomena throughout a day, a dynamic power management strategy is applied, allowing the system to establish an adaptive balance between its energy consumption and the accuracy of phosphorus estimation. The proposed precision agriculture structure allows the implementation of a flexible methodology that can be adapted to different type of crops and agricultural regions. Experimental results obtained in the lab and on the field corroborate the system's performance and reliability.