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Making waves: The potential of generative AI in water utility operations.

作者信息

Sela Lina, Sowby Robert B, Salomons Elad, Housh Mashor

机构信息

Maseeh Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, USA.

Department of Civil and Construction Engineering, Brigham Young University, USA.

出版信息

Water Res. 2025 Mar 15;272:122935. doi: 10.1016/j.watres.2024.122935. Epub 2024 Dec 7.

Abstract

Water utilities facing increasingly complex infrastructure and operations stand to significantly benefit from artificial intelligence (AI). Current research in water distribution systems engineering primarily focuses on Specialized AI, which plays a crucial role in processing extensive datasets, identifying patterns, and extracting actionable insights to improve the resilience and efficiency of water utility operations. However, barriers of usability, accessibility, and trainability hinder broader adoption. As AI technology evolves, Generative AI is emerging as a game changer by enabling intuitive, natural language interactions with complex systems, thereby making AI more accessible. This paper explores emerging AI topics, examines key challenges in deploying AI-based tools, highlights new opportunities, and presents practical examples of AI integration in water system operations: missing data imputation, asset data processing, and water demand analysis. It also identifies critical aspects that the water research community must prioritize to advance water system research into the AI era, including promoting responsible and user-centered AI solutions, building trust in technology, integrating AI into existing workflows, enhancing data privacy and security, and strengthening partnerships.

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