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AI Applications in Drinking-Water Management
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Author(s): P. Selvakumar (Nehru Institute of Technology, India), Ratan Rajan Srivastava (Shri Ramswaroop Memorial College of Engineering and Management, India), Sumanta Bhattacharya (Maulana Abul Kalam Azad University of Technology, India), Abhijeet Das (C.V. Raman Global University, Bhubaneswar, India), T. C. Manjunath (Rajarajeswari College of Engineering, India)and Sandeep Gupta (Graphic Era University, Dehradun, India)
Copyright: 2025
Pages: 30
Source title:
Smart Water Technology for Sustainable Management in Modern Cities
Source Author(s)/Editor(s): Jorge A. Ruiz-Vanoye (Universidad Politécnica de Pachuca, Mexico)and Ocotlán Díaz-Parra (Universidad Politécnica de Pachuca, Mexico)
DOI: 10.4018/979-8-3693-8074-1.ch013
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Abstract
This introduction explores the transformative potential of AI technologies in addressing complex challenges facing drinking water systems, while also examining the ethical considerations and technical hurdles that must be navigated for responsible and effective deployment. Drinking water is a fundamental resource essential for human health, economic prosperity, and ecosystem integrity. However, managing water quality and distribution systems presents significant challenges, exacerbated by population growth, urbanization, climate change impacts, aging infrastructure, and emerging contaminants. Traditional methods of water quality monitoring and management rely on periodic sampling, laboratory analysis, and manual intervention, which are often time-consuming, resource-intensive, and may not provide real-time insights needed to prevent waterborne diseases or respond swiftly to contamination events. Firstly, AI enables real-time detection of water quality deviations and potential contaminants through advanced sensor networks and predictive analytics.
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