Machine Learning for Improving water Quality Monitoring and Management

International Journal of Multidisciplinary and Scientific Emerging Research 13 (2):914-917 (2025)
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Abstract

Water is a fundamental resource for life, yet maintaining its quality remains a significant global challenge due to pollution from industrial, agricultural, and domestic sources. Traditional water quality monitoring methods are time-consuming and limited in scope. Machine Learning (ML) offers advanced capabilities for analyzing complex datasets, predicting pollution levels, and optimizing water resource management in real-time. This paper explores the integration of ML in water quality monitoring and management, reviewing current applications, methodologies, and future research directions. We present a framework for real-time monitoring using ML models to enhance decision-making and resource planning.

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