Mobile cellular network-Based Positioning using Machine Learning

Abstrakt

Positioning systems are essential for various
applications, ranging from navigation to location-based services.
In the case of mobile cellular networks. This study explored the use
of mobile cellular network signals to develop a positioning system
for beehives. Our research introduces a new approach for
positioning using mobile cellular (LTE, UMTS, and GSM) radio
signal data. We trained a machine learning model to predict
geographic coordinates (latitude and longitude) based on various
parameters extracted from the intercepted radio signals. These
parameters include the Cell Identity, Mobile Country Code
(MCC), Mobile Network Code (MNC), Location Area Code (LAC),
and additional relevant identifiers.Our study offers a novel
approach for precise position determination by utilizing
information provided by mobile cellular signals.