Abstract: A method for predicting at least one parameter representative of a signal quality and/or service quality liable to be delivered to a device when it is connected to one radiofrequency antenna among a plurality of antennas that are configured to establish a connection with said device. The method includes: obtaining at least one parameter of decrease in the signal and/or service quality, predicting at least one parameter representative of a signal and/or service quality by applying at least one prediction model configured to predict at least one parameter representative of a signal quality and/or service quality, on the basis of an estimated parameter of decrease in the signal and/or service quality, and of an indication of a moment and of a position of the device for which the prediction must be carried out, the prediction model having been trained beforehand via supervised learning on a training database.

Abstract: A method for predicting a value representative of a quality of connection of a vehicle to a cellular network from a target location on a road network including: training a prediction model on the basis of a determined characteristic of propagation between an access point and the position of a training vehicle and on the basis of a value representative of a quality of the connection of the vehicle to said access point; and predicting a second value representative of a quality of connection to a cellular network at the target location on a road network on the basis of a second characteristic of propagation of a radio signal between the target location and an identified target access point by applying the trained model.

Abstract: A method for predicting, for a vehicle that is connected to a current cellular access point and is traveling on a road network, at least one characteristic associated with a modification of the linkage conditions of the vehicle to the cellular network. The method includes: training a first prediction model associated with the current access point from crowdsourced data collected from at least one training vehicle, the data comprising at least a first location, a speed and a direction of the training vehicle as well as a second location of the training vehicle collected when a disconnection from the current access point is detected; and predicting a third location at which a second vehicle will be disconnected from the current access point while traveling on the road network by applying the prediction model to a location, a speed, and a direction of the second vehicle.