In this project, students utilize a custom-built autonomous drone equipped with an independent IoT data logger (NodeMCU + PM2.5 + BME680 + External GPS) to analyze air quality near industrial zones. Unlike standard monitoring stations, this system allows for dynamic "Grid Sampling" missions. Students will program the drone to fly autonomous patterns downwind of factory chimneys to capture the dispersion of Particulate Matter (PM2.5) and Volatile Organic Compounds (VOCs). The recorded data (CSV) is then visualized using Kepler.gl to create 3D volumetric heat maps, enabling students to scientifically assess how pollution spreads and affects their school environment.