Abstract: A system includes one or more processors to obtain a transportation event and a transportation event time of a vehicle system at a current location on a route from an origin to a destination. The one or more processors determine transportation event conditions based on historical transportation data and predict, by mathematical optimization methods, optimal transportation routes based on one or more of historical transportation routes, contractual routes, contractual junctions, and station master data. The one or more processors cluster from the historical transportation data, by a machine learning classification method, transportation event data clusters and match at the current location the transportation event data to historical transportation data machine learning classification clusters. The one or more processors predict, by a machine learning model, an estimated time of arrival (ETA) of the vehicle system to the destination.

Abstract: Disclosed are various approaches for incentivizing in-person interactions and customer engagement. A computing device can receive a first indication of attendance of a user at an event and a second indication of attendance of the user at the event. The computing device can calculate an amount of time that the user attended the event. Then, the computing device can calculate an amount of reward points based at least in part on the amount of time that the user attended the event. Finally, the computing device can award the reward points to the user account of the user.

Abstract: Disclosed are various approaches for incentivizing in-person interactions and customer engagement. These approaches can include obtaining, with a client device, a first indication of attendance of a user at an event. Then, the client device reports the first indication of the attendance of the user to a remote computing device. Later, the client device obtains an additional indication of the attendance of the user at the event and reports the second indication of the attendance of the user to the remote computing device. Meanwhile, the remote computing device can receive the first indication of attendance of a user at an event and the second indication of attendance of the user at the event. The remote computing device can calculate an amount of time that the user attended the event and an amount of reward points based at least in part on the amount of time that the user attended the event. The remote computing device can then award the reward points to the user account of the user.

Abstract: Disclosed are various approaches for incentivizing in-person interactions and customer engagement. These approaches can include obtaining, with a client device, a first indication of attendance of a user at an event. Then, the client device reports the first indication of the attendance of the user to a remote computing device. Later, the client device obtains an additional indication of the attendance of the user at the event and reports the second indication of the attendance of the user to the remote computing device. Meanwhile, the remote computing device can receive the first indication of attendance of a user at an event and the second indication of attendance of the user at the event. The remote computing device can calculate an amount of time that the user attended the event and an amount of reward points based at least in part on the amount of time that the user attended the event. The remote computing device can then award the reward points to the user account of the user.