T-Mobile Innovations LLC

Farhana Sharmin Munnee

Lance Paul Lukens

Hui-Lin Chang

Daqi Li

Shawn Derek Wallace

Systems and methods for making telecommunication network predictions on a granular geographic area-scale. The method can include receiving network key performance indicators (KPIs) associated with a plurality of user equipment (UEs) and then parsing the network KPIs into a plurality of geographic area-based categories corresponding to network KPIs obtained by cell towers or UEs located within a given geographic area, like a zip code. The method can further include combining the geographic area-based categories into clusters determined based on one or more similarities in the network KPIs of each, and predicting a most-influential one of the network KPIs within at least one of the clusters via a machine learning (ML) model. In response, the method can then cause an indicator to be generated at a user interface, the indicator indicating the most-influential one of the network KPIs within the at least one of the clusters.

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Herndon, VA, United States of America

Farhana Sharmin Munnee