Harnessing IoT and Generative AI for Weather-Adaptive Learning in Climate Resilience Education

TL;DR

This paper presents FACTS, an innovative platform that uses IoT sensors and Generative AI to create personalized, adaptive climate resilience education experiences based on real-time atmospheric data.

Contribution

The paper introduces a novel system combining IoT data, AI-generated content, and adaptive learning for climate education, advancing current educational technologies.

Findings

Participants found the system easy to use.

The system effectively enhanced climate resilience knowledge.

Personalized feedback improved learner engagement.

Abstract

This paper introduces the Future Atmospheric Conditions Training System (FACTS), a novel platform that advances climate resilience education through place-based, adaptive learning experiences. FACTS combines real-time atmospheric data collected by IoT sensors with curated resources from a Knowledge Base to dynamically generate localized learning challenges. Learner responses are analyzed by a Generative AI powered server, which delivers personalized feedback and adaptive support. Results from a user evaluation indicate that participants found the system both easy to use and effective for building knowledge related to climate resilience. These findings suggest that integrating IoT and Generative AI into atmospherically adaptive learning technologies holds significant promise for enhancing educational engagement and fostering climate awareness.