<![CDATA[Purpose – Ornamental plants require consistent watering to maintain optimal growth; however, manual watering often causes uneven water distribution and inefficient water usage. This study aims to develop an Internet of Things (IoT)-based automatic watering system using the Mamdani fuzzy logic method to improve watering accuracy and water efficiency. Methods – The system utilizes an ESP32 microcontroller integrated with capacitive soil moisture, DHT22 temperature, and BH1750 light intensity sensors. The Mamdani fuzzy logic method with 27 rule bases was implemented to determine adaptive watering duration. A real-time monitoring website was developed using Node.js, WebSocket, and SQLite. Findings – The system generated watering durations of 48–51 seconds under dry soil conditions, 28–32 seconds under normal conditions, and 9–12 seconds under wet soil conditions. Sensor validation produced RMSE values of ±0.48°C for temperature, ±18 lux for light intensity, and ±4.7% for soil moisture measurements. In addition, the proposed system improved water usage efficiency by approximately 60.5% compared to manual watering. Research Implications – The developed system supports smart agriculture implementation through adaptive irrigation, reduced water waste, and real-time environmental monitoring. The results demonstrate that the proposed IoT-based Mamdani fuzzy watering system can function as an adaptive and water-efficient solution for ornamental plant maintenance, although its implementation remains limited to the tested prototype environment. Originality – This research integrates multi-sensor monitoring, Mamdani fuzzy logic with 27 rule bases, and real-time web-based monitoring into a single adaptive ornamental plant watering system.]]>
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