Integrating Conversational AI Agents for Enhanced Water Quality Analytics: Development of a Novel Data Expert System

Abstract

Despite advancements in environmental monitoring, the gap between data collection and user-friendly data interpretation remains a significant challenge, especially in the domain of water quality management. This paper introduces the Artificial Intelligence Data Expert (AI-DE), a novel data analytics system that is designed to facilitate on-demand analysis of time-series sensor data related to water quality using natural language queries. The AI-DE leverages features of ChatGPT, including Named Entity Recognition, geocoding, and sentiment analysis, to enable intuitive and natural language-based data analysis. This system transformation 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 seamless integration with an integrated information system, and a data interpretation mode for detailed analysis. The AI-DE enhances user engagement and comprehension of water quality data, thereby supporting 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.