<![CDATA[Purpose – This study aims to design and implement an IoT-based automatic irrigation system for oil palm seedlings capable of determining irrigation duration based on soil moisture and ambient temperature conditions. The research addresses the limitations of manual irrigation, which may cause water deficiency or excess in the growing medium. Methods – The study employed experimental and engineering methods using an ESP32 DevKit V1 microcontroller as the control center. The system utilized an FC-28 soil moisture sensor and a DHT22 temperature sensor. Sensor data were processed using the Sugeno Fuzzy Logic method with a nine-rule base to determine irrigation duration. A relay controlled a 5V DC water pump, while Telegram was used for system monitoring and control. Findings – The system successfully generated irrigation decisions with predefined singleton outputs of 0, 5, 10, and 15 seconds and correctly executed all implemented Telegram monitoring and control commands Research implications – The system is limited by the use of the FC-28 resistive soil moisture sensor, which is susceptible to corrosion and requires periodic recalibration, while remote monitoring depends on network availability. Originality – This study differentiates itself from previous work by implementing an explicitly specified ESP32 DevKit V1, a DHT22 temperature sensor, and Telegram-based monitoring and control, whereas previous research employed a DHT11 sensor and website-based monitoring without explicitly identifying the microcontroller while using the same fuzzy input parameters and Sugeno Fuzzy Logic method.]]>
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