Hybrid decision support system using PLSR-fuzzy model for GSM-based site-specific irrigation notification and control in precision agriculture

In this paper, a partial least square regression (PLSR) and fuzzylogic based smart decision support system (DSS) for crop-specific irrigation notification and control in precision agriculture is proposed, and this can be implemented in farm land, green-house and poly-house. The proposed DSS model continuously acquires real-time soil and environmental data using Zigbee wireless sensor network (WSN) with WiFi gateway developed during this work. The collected data are used to predict hourly soil moisture content (MC) variation and required evapotranspiration to control farm irrigation by utilising fuzzy logic-based weather model. A comparative analysis of soil MC variations is also performed by calculating root mean square error (RMSE), R-squared error (RSE), mean squared error (MSE), ratio of performance to deviation (RPD) and algorithm running time. Cropwise evapotranspiration is also calculated using Blaney–Criddle method which is attached to the proposed DSS model by taking weather, soil, water and crop data into considerations.