Logo image
A novel intelligent expert system for exploring water quality data
Journal article   Open access   Peer reviewed

A novel intelligent expert system for exploring water quality data

Gabriel Vald, Yusuf Sermet, Jerry Mount, Samrat Shrestha, Dinesh Jackson Samuel, David Cwiertny and Ibrahim Demir
Water science and technology, Vol.93(4), pp.411-427
02/01/2026
DOI: 10.2166/wst.2026.199
url
https://doi.org/10.2166/wst.2026.199View
Published (Version of record) Open Access

Abstract

Despite advancements in environmental monitoring, the gap between data collection and user-friendly data interpretation remains. This paper introduces the Artificial Intelligence Data Expert (AI-DE), a novel data analytics system designed to facilitate on-demand analysis of time-series monitoring data for water quality using natural language queries. The AI-DE leverages features of ChatGPT, including named entity recognition, geocoding, and sentiment analysis, enabling natural language-based data analysis. This system allows for immediate, ad-hoc querying and interpretation of environmental data, tailored to the needs of diverse user groups. Key features include chat controls that customize user interaction, a chat bypass enabling data synchronization with an information system, and a data interpretation mode for detailed analysis. The AI-DE enhances user engagement with an understanding of water quality data, aiming to support informed decisions and actions for environmental management. The AI-DE represents a step forward in increasing access to complex environmental data through conversational AI technologies.Despite advancements in environmental monitoring, the gap between data collection and user-friendly data interpretation remains. This paper introduces the Artificial Intelligence Data Expert (AI-DE), a novel data analytics system designed to facilitate on-demand analysis of time-series monitoring data for water quality using natural language queries. The AI-DE leverages features of ChatGPT, including named entity recognition, geocoding, and sentiment analysis, enabling natural language-based data analysis. This system allows for immediate, ad-hoc querying and interpretation of environmental data, tailored to the needs of diverse user groups. Key features include chat controls that customize user interaction, a chat bypass enabling data synchronization with an information system, and a data interpretation mode for detailed analysis. The AI-DE enhances user engagement with an understanding of water quality data, aiming to support informed decisions and actions for environmental management. The AI-DE represents a step forward in increasing access to complex environmental data through conversational AI technologies.
artificial intelligence large language models natural language processing sensor network time-series data water quality

Details

Metrics

1 Record Views
Logo image