The goal of this project was to generate mobile coverage maps based on signals emitted by SIM cards. The client wanted to understand the quality of mobile coverage across the different operating zones of their freight transport trucks. Each truck had a SIM card installed that emitted a geolocation signal every hour. In areas with poor coverage, the signal might fail to arrive, be delayed, or contain incorrect information.

A Python algorithm was developed to process the data emitted by all trucks in the fleet. First, it compared the signals across different trucks to rule out false negatives caused by isolated SIM card failures. Then, it analyzed the geolocations over time to calculate distances associated with time intervals and detect zones where signals were missing due to low mobile coverage. Finally, it filled the signal gaps along the routes with newly generated geolocation points.SIM. Luego comparaba las geolocalizaciones entre ellas para establecer distancias relacionadas con periodos temporales y así detectar zonas en las que no se emitían señales por tener baja cobertura móvil. Finalmente rellenaba los tramos de ruta sin señal con nuevos puntos de geolocalización generados para ello.

The results were visualized using the QGis mapping tool. The algorithm produced CSV files with the signal geolocations and an associated coverage level, which QGis interpreted to generate color-coded maps based on coverage quality.

The results enabled the client to identify alternative routes with better coverage, improving the safety of their transport operations.

Project duration: July 2023 – December 2023

Tools used

  • Python
  • QGis (Open Source map visualization tool)
  • Excel