Journal article
Application of large language models in developing conversational agents for water quality education, communication, and operations
Water practice and technology, Vol.20(10), pp.2094-2109
09/30/2025
DOI: 10.2166/wpt.2025.129
Abstract
The rapid advancement of large language models, such as ChatGPT, has opened new horizons in the field of artificial intelligence (AI), revolutionizing the way we can engage with and disseminate complex information. This paper presents an innovative application of ChatGPT in the domain of water quality (WQ) management, through the development of an AI Hub. The Hub encompasses a suite of conversational agents, each designed to address different aspects of WQ management, including nitrogen pollution, local WQ issues, and actionable planning for water conservation. These agents utilize the advanced natural language processing capabilities of ChatGPT, complemented with WQ-related data, to provide users with accurate, up-to-date, and contextually relevant information. The objective is to empower communities with the knowledge necessary to understand and address WQ challenges effectively. Our comprehensive evaluation of these agents demonstrates their proficiency in delivering valuable insights, with an overall performance accuracy exceeding 89%. This paper underscores the potential of AI-enabled platforms in enhancing public understanding and engagement in environmental conservation efforts. By bridging the gap between complex environmental data and public awareness, the AI Hub sets a precedent for the application of AI in sustainable environmental management.
Details
- Title: Subtitle
- Application of large language models in developing conversational agents for water quality education, communication, and operations
- Creators
- Jackson Samuel Ravindran - Pittsburg State UniversityYusuf Sermet - Tulane UniversityJerry Mount - University of IowaGabriel Vald - University of IowaSamrat Shrestha - Tulane UniversityDavid Cwiertny - University of Iowa, Center for Health Effects of Environmental ContaminationIbrahim Demir - Tulane University
- Resource Type
- Journal article
- Publication Details
- Water practice and technology, Vol.20(10), pp.2094-2109
- DOI
- 10.2166/wpt.2025.129
- eISSN
- 1751-231X
- Publisher
- Iwa Publishing
- Number of pages
- 16
- Grant note
- 2137891; 2230710 / National Science Foundation; National Science Foundation (NSF)
- Language
- English
- Date published
- 09/30/2025
- Academic Unit
- Electrical and Computer Engineering; Center for Health Effects of Environmental Contamination; Civil and Environmental Engineering; IIHR--Hydroscience and Engineering; Injury Prevention Research Center; Chemistry; Chemical and Biochemical Engineering
- Record Identifier
- 9985019142902771
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