With federated AI, mobile network usage data is processed in edge mode, i.e. as close as possible to the aerial.
This makes it a technology that has significant potential to improve the reactivity of network alert systems. Unlike centralised AI, sensitive data is protected, since it does not circulate over the network. Calculations, performed locally, bring results more quickly. The models calculated during the learning phase are shared between relays. Lastly, without the need to transmit data and cool a central server, the energy efficiency of the process is improved.