STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Water Resource Engineering and Management Review Article

Use of Artificial Intelligence to Access and Ensure Safe Drinking Water Supply: A Review

  1. T.P. Sulakshna Department of Civil Engineering, NSS College of Engineering, Palakkad, Kerala, India
  2. V.R. Pramod GRIP Global Pte Ltd, Far East Square, 32 Pekin Street, #05-01, Singapore 048762

Abstract

Ensuring access to safe drinking water is a critical public health challenge. Traditional water quality assessment methods are often labor-intensive and time-consuming. Artificial intelligence offers a promising alternative, providing rapid, accurate, and scalable solutions for monitoring and predicting water quality. This systematic review examines the application of AI. The review highlights various AI models, including artificial neural networks, support vector machines, decision trees, and ensemble methods, in predicting water quality parameters and detecting contamination events. The integration of artificial intelligence with Internet of Things devices for real-time monitoring is also discussed. Our findings suggest that artificial intelligence-based approaches significantly enhance water quality management, offering robust and efficient solutions for ensuring safe drinking water. The advancement in explainable artificial intelligence, has considerably elevated the trust in using AI in drinking water management

Keywords

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