Verizon Communications Inc.
Systems and methods for utilizing time series and neural network models to deploy autonomous vehicles for 5G network coverage gaps

Abstract:

A device may receive historical usage data associated with a portion of a wireless network, and may train a model with the historical usage data to generate a trained model. The device may process data identifying a future time period, with the trained model, to forecast a traffic demand during the future time period, and may compare the traffic demand and a traffic capacity of the portion of the wireless network to determine whether the traffic demand is within a threshold of or exceeds the traffic capacity. The device may identify an autonomous vehicle to deploy for the portion of the wireless network when the traffic demand is within the threshold of or exceeds the traffic capacity, and may cause the autonomous vehicle to be deployed for the portion of the wireless network, wherein the autonomous vehicle is to provide a temporary wireless network.