Title : Drone-based real-time air pollution monitoring and controlling framework for smart city
Abstract:
Air pollution is a significant environmental concern that requires continuous monitoring to assess its impact on human health and the environment. Traditional ground-based monitoring stations have limited coverage, operating costs, and mobility. In recent years, drones have emerged as a promising platform for air quality monitoring due to their ability to hover, sufficient flexibility, ease of deployment, increased maneuverability, and lower operating costs. This project aims to develop a drone-mounted multi-gas sensor data collection framework that monitors and controls carbon emission concentrations accurately and efficiently. The proposed method operates based on the data collected from drone-mounted gas sensors deployed in the target area. It is divided into two hierarchical stages. First, a gated recurrent unit (GRU)--based carbon emission concentration estimation (CECE) model monitors the air quality level at each timeslot. Second, an effective catalyst technique is applied to reduce carbon emissions in the area of high pollutants concentration or when the parameter values are above air quality indicator thresholds. In conclusion, the proposed framework can offer an innovative and promising solution to address conventional air quality monitoring limitations.
