Effective water quality (WQ) management is essential for protecting ecosystems and human health. Nitrogen and phosphorus runoff from agriculture can lead to harmful algal blooms and oxygen depletion, especially after heavy rainfall, highlighting the need for strategies to mitigate pollution. To promote community awareness, BlueGAP has developed conversational AI agents capable of engaging users on water quality topics, from nutrient pollution to sustainable agriculture. Geographic experts for Iowa and Tampa Bay translate local knowledge into interactive dialogues, while a community action planner assists users in organizing WQ-related events like cleanups or educational campaigns. The BlueGAP AI agents adapt to user input by adjusting language, expertise level, and tone, making the system accessible to all. By drawing on the BlueGAP knowledge base, the AI agents offer improved educational engagement and accurate information compared to standard chatbots, providing a valuable tool for WQ education, communication, and community action.
Related Articles
- Vald, G., Sermet, M., Mount, J., Shrestha, S., Samuel, D. J., Cwiertny, D., & Demir, I. (2024). Integrating Conversational AI Agents for Enhanced Water Quality Analytics: Development of a Novel Data Expert System.
DOI: https://doi.org/10.31223/x51997 - Samuel, D. J., Sermet, M., Mount, J., Vald, G., Cwiertny, D., & Demir, I. (2024). Application of Large Language Models in Developing Conversational Agents for Water Quality Education, Communication, and Operations.
DOI: https://doi.org/10.31223/x5xt4k
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A user accesses live WQ sensor data for Iowa City.
