DOI : https://doi.org/10.62527/ijasce.7.2.261

Fuzzy Logic and IoT-Based Monitoring for Solar-Powered Precision Mist Irrigation

Imam Hidayat (1), Akhmad Wahyu Dani (2), Mawardi Amin (3), Irvan Hermala (4), Abdurohman (5)
(1) Department of Mechanical Engineering, Universitas Mercu Buana, Indonesia
(2) Department of Electrical Engineering, Universitas Mercu Buana, Indonesia
(3) Department of Electrical Engineering, Universitas Mercu Buana, Indonesia
(4) Department of Management, Universitas Mercu Buana, Indonesia
(5) Master of Electrical Engineering, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
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How to cite (IJASCE) :
Hidayat, I., Dani , A. W., Amin , M., Hermala , I., & Abdurohman. (2025). Fuzzy Logic and IoT-Based Monitoring for Solar-Powered Precision Mist Irrigation. International Journal of Advanced Science Computing and Engineering, 7(2), 53–59. https://doi.org/10.62527/ijasce.7.2.261
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The increasing unpredictability of environmental conditions, such as temperature fluctuations, humidity variations, seasonal shifts, and changing water availability, presents a significant challenge for sustainable food production. The increasing unpredictability of environmental conditions, including temperature fluctuations, humidity variations, seasonal shifts, and changing water availability, poses a significant challenge for sustainable food production. Although they are suitable for simple decision-making, conventional Type-1 Fuzzy Logic-based irrigation systems struggle to manage sensor noise, environmental uncertainty, and changing field conditions, resulting in sometimes ineffective water use and uneven irrigation management. This work presents a solar-powered mist irrigation system that integrates Interval Type-2 Fuzzy Logic (IT2FLS) and Internet of Things (IoT) technologies to improve precision irrigation management and address these issues. The proposed system employs IoT-based real-time environmental monitoring via Blynk and ThingSpeak to enable dynamic irrigation adjustments in response to temperature and soil moisture fluctuations. Type-2 Fuzzy Logic offers more reliable relay activation choices and greater robustness to sensor noise by incorporating Upper and Lower Membership Functions (UMF & LMF) and a Footprint of Uncertainty (FoU) than conventional Type-1 FIS. Experimental data demonstrate that the Type-2 Fuzzy model significantly reduces erroneous irrigation activations, maximizes water distribution, and increases system flexibility in response to environmental changes. Using solar power further improves energy efficiency, thereby reducing dependence on grid electricity and supporting environmentally friendly irrigation practices. This work demonstrates that, for contemporary agriculture, Type-2 Fuzzy Logic-based smart irrigation offers a scalable, flexible, and cost-effective alternative. This study shows how integrating renewable energy, advanced Type-2 fuzzy control, and IoT can create resource-efficient, adaptive irrigation systems supporting sustainable farming amid environmental challenges.

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