Abstract: The present disclosure describes various systems, methods, and apparatuses configured for transmitting updated information to mobile devices based on real-time information that is received over a wireless network. In various aspects, a computing system may calculate a respective score of a set of scores for each of a set of parameters corresponding to a respective transport orders of a set of transport orders received by the computing system over the wireless network. The computing system may transmit information associated with a respective transport order of the set of transport orders to one or more of the set of mobile devices based on the score and based on information associated with a set of transport profiles respectively associated with the set of mobile devices. The computing system may use real-time information received over the wireless network to dynamically update one or more of the set of transport orders or other information associated therewith.

Abstract: The present disclosure describes various systems, methods, and apparatuses configured for transmitting a set of properties associated with a mobile device to a computing system based on a proximity of a real-time location of the mobile device to a first location. The computing system that receives the set of properties may be associated with a second location. In some aspects, map information may be generated that includes a route from the first location to the second location based on a set of parameters associated with travel from the first location to the second location. The map information may be wirelessly transmitted to a subset of a set of profiles that is filtered based on information for each of a set of mobile devices associated with a respective profile of the set of profiles. Real-time profile locations respectively associated with the subset of the set of profiles may be wirelessly received.

Abstract: Example implementations are directed to methods and systems for predictive analytics for transport services that utilize vehicle, order, and route parameters to optimize matching using demand and suitability calculations. According to some example implementation, options for marshaling a route can be predicted and scored against other options in order to efficiently match one or more suitable transporters.

Abstract: Example implementations are directed to methods and systems for predictive analytics for transport services that utilize vehicle, order, and route parameters to optimize matching using demand and suitability calculations. According to some example implementation, options for marshaling a route can be predicted and scored against other options in order to efficiently match one or more suitable transporters.