12-16, 16:45–17:00 (Asia/Bangkok), Auditorium Hall 2
The integration of Internet of Things (IoT) technology with environmental monitoring systems has significantly enhanced the ability to collect real-time data from diverse and remote locations. However, the challenge lies in efficiently analyzing and interpreting this vast amount of data to make informed decisions. This paper explores the application of generative AI in IoT data analysis for environmental monitoring. Generative AI, with their advanced natural language processing capabilities, offer a novel approach to processing and understanding complex data patterns. By leveraging Generative AI, it is possible to automate the identification of critical environmental changes, predict trends, and provide actionable insights with unprecedented accuracy. This study demonstrates how Generative AI can enhance data analytics in environmental monitoring through case studies that highlight improvements in air quality assessment (e.g. PM 2.5). The findings suggest that Generative AI not only streamline the data analysis process but also enhance the reliability and responsiveness of environmental monitoring systems. Consequently, this research underscores the potential of Generative AI to transform IoT-based environmental monitoring, promoting more proactive and effective environmental management practices.
