IOT-BASED SMART IRRIGATION SYSTEM USING FUZZY LOGIC, TEMPERATURE, AND SOIL MOISTURE FOR MELON CULTIVATION
DOI:
https://doi.org/10.35261/barometer.v11i3.13243Abstract
This study aims to design and develop a smart irrigation system that integrates Fuzzy Logic with IoT technology to maintain optimal soil moisture and temperature for melon growth. The precision of irrigation volume is crucial because insufficient irrigation can reduce production by up to 25%. Overcoming the weaknesses of conventional scheduled irrigation systems, this research offers novelty in formulating the fuzzy rule base, which is specifically designed based on water conservation principles to prevent melon root rot; where the pump actuator is forced to shut off completely when the soil moisture exceeds 80%, regardless of the air temperature. The methods include hardware design (ESP32, DS18B20 temperature sensor, soil moisture sensor, DC pump) and software design using the Mamdani Fuzzy Inference System (FIS) with the Weighted Average defuzzification method. The test results indicate that the DS18B20 sensor is highly precise with an average error of 0.4. Blynk integration successfully transmits real-time data with a minimal delay of 200 ms. Algorithm validation across various environmental fluctuation scenarios proves that the system can dynamically modulate pump actuation duration (0 to 7 seconds), with a specific test at 24.8°C and 58% moisture producing an actuation of 4.57 seconds, which is precise and equivalent to mathematical calculations. Based on this adaptive computation, the system is theoretically capable of increasing Water-Use Efficiency compared to manual watering. The practical implications of this prototype can be realized in both greenhouse and open-field melon cultivation to reduce operational labor costs and minimize water waste.
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