This project focused on developing a system for monitoring and visualizing air quality data using low-cost mobile sensors. The system integrates GNSS technology for location tracking, Raspberry Pi for data processing, and web development for visualization.
The solution provides real-time air quality monitoring with spatial context, allowing for the identification of pollution hotspots and trends over time.
The system uses a network of low-cost sensors connected to Raspberry Pi devices that collect air quality data including particulate matter (PM2.5, PM10), carbon monoxide, nitrogen dioxide, and ozone levels. The collected data is geotagged using GNSS and transmitted to a central database.
A web application provides visualization tools including heat maps, time-series graphs, and comparative analysis features. Users can monitor air quality in real-time or analyze historical patterns to identify pollution sources and trends.
