Development of a Smart Plant Watering Robot Using Soil Moisture and Light Intensity based on Fuzzy Logic Control

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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.
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