Development of a Smart Plant Watering Robot Using Soil Moisture and Light Intensity based on Fuzzy Logic Control - Ayu Martini, Ni Putu Devira; Lukmana, Muhammad Arifudin; Pradana, Sigit (DPTE FT UNY, 2025)
Urban agriculture offers a strategic solution to improve food security and environmental sustainability in cities. However, challenges such as limited land and inefficient irrigation often hinder its effectiveness. This research proposes a smart automatic irrigation system tailored for small-scale urban farming. The system combines fuzzy logic and a two-axis cartesian robot to deliver water precisely based on real-time light intensity and soil moisture data. The fuzzy logic controller dynamically adjusts watering frequency and volume, ensuring efficient water use. Experimental results show the robot achieved a movement error rate of only 3.63%, while the fuzzy logic system reached a decision accuracy of 93.1%. Post-irrigation testing also revealed a 94.83% average increase in soil moisture, indicating the system's ability to restore optimal growing conditions. This approach demonstrates a scalable and sustainable solution for plant care in urban settings, supporting resource-efficient and productive farming in limited spaces.