Self Adaptive Communication based on Soil Moisture for Wireless Underground Sensor Networks

Abstract

In wireless underground sensor networks, channel estimation for communication success requires absolute information about deployment and properties of soil. These properties include soil composition (sand, silt, clay), soil density, soil temperature, inter-node distance, node depth, operating frequency and soil moisture. However, only soil moisture shows most temporal and spatial variation and affects the underground communication in long term. Therefore, we propose only soil moisture based self adaptive communication approach that overcomes the requirement of precise knowledge about the parameters of soil and underground deployment. This approach strives to find the maximum soil moisture threshold for successful communication for any given deployment. And, the sensor nodes conserve energy by avoiding the communication in times of increased soil moisture. Our proposed method is proved to be 5 times more energy efficient than terrestrial medium access control methods i.e.\ B-MAC for underground monitoring applications under extreme weather conditions.% One such application requires to analyse the efficiency of reforestation techniques to combat desertification of large fields in Cameroon. However persistent rains in the region present communication and reduced battery life challenges for underground networks. Self adaptive approach allows the sensor nodes to conserve more energy by forbidding the communication in times of increased soil moisture without requiring any soil information.