AI-based Air Quality Prediction with IoT and Satellite Data

The escalating concerns regarding air quality necessitate innovative approaches for accurate prediction and timely mitigation. This research addresses the imperative need for an AI-driven surface-level air quality prediction system, leveraging a synergistic blend of Internet of Things (IoT) and satellite data. By amalgamating real-time sensor data from IoT devices with satellite observations, the proposed model aims to enhance spatial and temporal resolution, providing a comprehensive understanding of air quality dynamics. The integration of artificial intelligence algorithms ensures precise predictions, enabling proactive measures to mitigate pollution. This research contributes to the evolving field of environmental monitoring, offering a sophisticated tool for policymakers and communities to combat the escalating challenges posed by deteriorating air quality.