A Novel Fuzzy Inference-Based Decision Support System for Crop Water Optimization

A logic-based decision support system (DSS) for agriculture support system is presented. The primary focus is on the algorithm used to correctly predict how much water should be poured to the agriculture for the optimal growth of the crops. Over-watering as well as under-watering has always been a big problem in farming. The proposed system uses three input parameters; namely field moisture, field humidity, and field temperature. However, for predicting the proper amount of water so as to get the optimized best growth of the crop, few more parameters also play a vital role, but in this work for simplicity purpose, we have taken these three parameters as input. Mamdani inference engine is used to deduce from the input parameters. Design of the proposed system is given with the fuzzy logic controller and simulation is being done using MATLAB (Matrix Laboratory) for solving the water irrigation issue. The proposed system is simple, using only three parameters (moisture, humidity, and temperature) as input. Through decision support system, the meaning of transferred data is translated into linguistic variables for use by the crop cultivation users. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.