Abstract: A method and system include receiving current data values for a group of vehicles, each of the current data values being generated by vehicles in the group of vehicles, and retrieving data external to the group of vehicles. They further include processing the data using two or more machine learning algorithms to identify a set of selected data values based on current operation and processing the set of selected data values, using a first and second machine learning algorithm, to generate predicted efficiency values for each vehicle. They further include determining if a predicted efficiency value of a first vehicle in the group of vehicles is less than a predicted efficiency for a second vehicle in the group of vehicles, comparing operational characteristics of the first and second vehicle based on the determination, and providing a message in order to improve efficiency for the first vehicle based on the comparison.

Abstract: A method, apparatus, and system are described. The method includes generating a set of current values associated with at least one component included on a moving vehicle and providing the set of current values over a wireless network. The values are generated by one or more sensors. An edge computing device receives the current values. The method further includes processing the set of current values in real-time using at least one machine learning algorithm to identify a value of a point in time for a failure of one of the at least one component based on the set of current values and at least one set of past values received. The past values are stored in a memory. The set of current values are transmitted with a low time latency between the generating the set of current values and the processing of the set of current values.