In Peru, a country celebrated for its vast and varied geography and vibrant cultural heritage, challenges persist regarding mobile signal coverage in educational institutions across the expansive territory. With virtual education assuming a leading role, a crucial question emerges: Are all Peruvian students afforded equal opportunities to access education?

To address this issue, we have combined several data sets, such as mobile antenna data released by the Peruvian government, images from the Aster Global Digital Elevation Model, and school locations obtained from OpenStreetMap, which were imported by our team. To determine if an educational center is in the coverage of an antenna, we use the visibility index (viewshed) with standard market parameters, in this way, we generate many binary raster images that were mixed to create coverage areas. Using this data, we developed a 3D visualization tool that highlights the range of mobile phone antennas and their physical coverage in educational institutions across the country.

The green areas represent the visible coverage of that antenna, while the lines denote the location of the antennas that provide the signal to that educational center.

Our investigation uncovers areas in Peru where mobile service quality is inadequate or entirely absent. Despite their proximity to communities, we've pinpointed antennas that experience signal disruptions due to geographical factors, thereby constraining signal access for educational institutions and nearby towns. Addressing these challenges is crucial for ensuring equitable access to education for all Peruvian students.

Some critical questions:

• What innovative strategies can be employed to improve access to education in these regions?
• What opportunities are being withheld from students lacking internet access?

Important Note: While our study adheres to standardized criteria and demonstrates consistency, it's essential to acknowledge that it may contain certain margins of error. For a more precise and comprehensive understanding, the integration of additional datasets is imperative.