Abstract:
The study aims to develop an IoT system to measure the water content in the soil and water use for plants by measuring the soil moisture dynamics throughout the entire duration of the crop growing season. Such a system can be used to automate the irrigation scheduling process and management. Irrigation scheduling is generally done based on farmed decision-making process where a farmer observe the effect of water content on plants, if the plan is wilting then water is needed. The traditional approach gives little control of water applied, and thus little is known about water content in the soil as well as water use by plants.
The study is operationalized by using two research questions: how water content in the field can be accurately estimated, and how well the soil moisture dynamics stabilizes when water is applied optimally. The study was conducted in NYAGATARE district in the Rwanda Eastern Province. The study consisted of measuring the soil moisture levels, soil temperatures and sensor data rates by using 14 sensor nodes covering a 30Ha irrigated field of Maize crops. The study showed that moisture level dynamics stabilize when water is applied based on accurate measurement of water content in the field and water use by the plant. The study opens perspectives for automating irrigation detection over large areas and thus for the improvement of irrigation water management
