Smart Irrigation Prediction using Artificial Neural Network ANN with Evapotranspiration Rate Equations and Internet of Things IoT for Paddy Field

Abstract

It is estimated that by 2050, the world’s population will increase to 10 billion people and water scarcity is going to be a major problem due to an increase number of populations with limited water resources. One of the ways to tackle this problem is by having a precision irrigation which is by estimating the crops water need in which it can improve water utilization. This research is very suitable to be implemented for paddy since paddy consumed a lot of water compared to other types of crops. In order to be able to do it, ANN and Evapotranspiration Rate equation will be used to develop a prediction model to estimate water lost. The prediction model in theory will analyze the historical data and compared it with current data collected in the field and predict water needs based on the output concluded. IoT will act as monitoring and controlling platform for irrigation by automating the irrigation which in result, better water utilization. Prediction model and IoT combination proved that better water utilization can be achieved. The targeted result will be to achieve better water utilization using prediction model and IoT.