Smart Hydroponic Nutrient Monitoring and Control System using Fuzzy Logic and IoT

Hydroponic farming offers an efficient and sustainable solution for modern agriculture, although main-taining stable nutrient levels remains a key challenge. Previous systems often exhibited high overshoot and were unable to adapt to external changes or disturbances, and no existing research has adaptively regulated nutrient levels based on the plant’s growth stage. Therefore, this study aims to develop a smart nutrient monitoring and control system for hydroponics using a Sugeno-type fuzzy logic controller inte-grated with an IoT-based application. Unlike prior systems that rely on fixed setpoints or only address nutrient deficiency, this system dynamically adjusts nutrient and water levels based on real time sensor data and plant growth phase. The system utilizes nutrient, water level, and temperature sensors connected to an ESP32 microcontroller, with fuzzy logic determining solenoid valve activation duration. The control system achieved stable regulation with zero overshoot, a settling time of 840 seconds, and effective recov-ery from nutrient disturbances. Growth tests on celery showed a 102.6% improvement in height, 275% in stem diameter, and 112.5% in leaf width compared to manual control. IoT monitoring via a mobile appli-cation ensured real time visibility of hydroponic parameters. These results demonstrate the system’s ca-pability to maintain optimal nutrient levels, improve control precision, and enhance plant productivity.