Abstract: A route prediction system implements a method that utilizes real-time mobile communication network data including receiving real-time mobile communication network data. The method further includes aggregating the real-time mobile communication network data with historical data to form a training set, filtering the training data set for relevance to servicing route predictions for connected vehicles, training a plurality of offline models using the filtered training data set, and selecting a best performing propagation model from the plurality of offline models.

Abstract: A method of a route prediction system utilizing real-time mobile communication network data. The method includes receiving a route request originating from a connected vehicle, the route request identifying a route, determining segments for the route, localizing mobile communication network resources to the segments, determining key performance indicators for the segments based on at least a current offline model, and sending predicted service level indicators (SLIs) for the segments to the connected vehicle.

Abstract: A method provides route information to a connected vehicle in a brokered information prediction system. The method includes determining available mobile communication networks that can provide real-time mobile communication network data, querying a first available mobile communication network to provide key performance indicators for a route for a connected vehicle, determining service level indicators for the route based on received key performance indicators for the route where the key performance indicators meet defined thresholds, and sending predicted service level indicators for the route to the connected vehicle.

Abstract: The present disclosure relates to a method performed by a processing device (4) of a Work Force Management (WFM) system (1) for predicting timely completion of a work order for service at a remote site (3) of a telecommunication system (2). The method comprises obtaining information about a time period allowed for completion of the work order. The method also comprises selecting, based on previous knowledge about the remote site, a set of factors which may affect service at the remote site. The method also comprises updating information about the selected factors. The method also comprises, at a first point in time within the allowed time period, obtaining information about a current status of the work order. The method also comprises, based on the updated information and the work order status at said first point of time, predicting whether it is likely that the work order will be completed within the allowed time period.