Design and Performance Analysis of a Fuzzy Logic-Based IoT System for Greenhouse Irrigation Control

Abstract

Automatic irrigation has long been used to efficiently irrigate large agricultural areas through drip irrigation systems to minimize water wastage. In greenhouse irrigation, computerized control is essential to improve productivity, as conventional control methods that rely on on-off or proportional control are often inefficient. This research introduces a novel approach to monitor greenhouse environmental conditions and control irrigation duration. The monitoring system architecture consists of sensor nodes and a gateway. The irrigation duration control uses a Fuzzy Logic Controller (FLC) based on the Mamdani method. The FLC is implemented on a NodeMCU ESP8266 board integrated with a DHT22 sensor and a soil moisture sensor. Temperature and soil moisture parameters are used as inputs for the fuzzy logic system in determining the appropriate irrigation duration. The linguistic variables used in the fuzzy membership function include soil moisture (categorized as water, wet, and dry), temperature (categorized as cold, normal, and hot), and watering time (categorized as zero, short, medium, and long). A rule base consisting of nine fuzzy rules was developed based on these membership functions. Experimental results show that the FLC implemented on the NodeMCU ESP8266 has an average accuracy of 99.41% compared to the MATLAB simulation. This shows the fuzzy logic-based system's high accuracy and effectiveness in controlling the duration of greenhouse irrigation. This developed system offers a promising solution to optimize water usage and improve irrigation management in a greenhouse environment.