Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 9 No 25 (2025): Volume 9, Special Issue of INSPIRE’25 April 2025 | Pages: 121-125
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 24-04-2025
An abstract Water Scarcity is increasingly becoming a problem in contemporary agriculture, and efficient water management is therefore a vital imperative. This project, smart agro- irrigation system for optimal water use, utilizes Artificial Intelligence (AI) and Machine Learning methods to maximize water usage in irrigation systems. The system combines Linear Regression, Clustering, and Q-Learning algorithms to study environmental factors like soil moisture, temperature, humidity, and weather conditions. Through real-time data processing, the model forecasts optimal water needs with minimal wastage of water and maximum crop health. This system improves resource utilization, minimizes manual intervention, and encourages sustainable agriculture. The use of data-driven decision-making enables farmers to harvest more with less water usage, ultimately leading to environmental protection and enhanced agricultural output.
Smart irrigation, Water optimization, Artificial intelligence (AI), Machine learning (ML), Sustainable farming, Environmental monitoring, Soil moisture forecasting, K-Means clustering
Lohitha Sree M, Shaik Salam. (2025). Smart Agro-Irrigation System for Optimal Water Use. In proceeding of International Conference on Sustainable Practices and Innovations in Research and Engineering (INSPIRE'25), published by IRJIET, Volume 9, Special Issue of INSPIRE’25, pp 121-125. Article DOI https://doi.org/10.47001/IRJIET/2025.INSPIRE20
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