Abstract: A system and a method include at least one control unit that determines a de-icing time for an aircraft within a de-icing area of an airport, predicts a de-icing time for an aircraft within a de-icing area of an airport, schedules de-icing times for a plurality of aircraft within a de-icing area of an airport, and/or predicts demand for future de-icing operations of aircraft within a de-icing area of an airport.

Abstract: The present disclosure provides predictive flight diversion management by: receiving weather data for a zone of air traffic control; receiving flight tracking data for a plurality of aircraft travelling in the zone of air traffic control; determining capacity rates for a plurality of airports in the zone of air traffic control, based on the flight tracking data; and in response to receiving a diversion trigger from a predictive model predicting a diversion event: determining, based on the weather data, the flight tracking data, and the capacity rates, a subset of aircraft from the plurality of aircraft that are to be diverted from original destinations in the zone of air traffic control to new destinations.

Abstract: A system and a method include at least one control unit that determines a de-icing time for an aircraft within a de-icing area of an airport, predicts a de-icing time for an aircraft within a de-icing area of an airport, schedules de-icing times for a plurality of aircraft within a de-icing area of an airport, and/or predicts demand for future de-icing operations of aircraft within a de-icing area of an airport.

Abstract: A method to reduce aircraft fuel consumption includes determining whether a particular aircraft belongs to a runway queue associated with one or more aircraft waiting to take-off from a runway of an airport based on (i) real-time aircraft geographic location information associated with the particular aircraft and (ii) a graph associated with features of the airport. An amount of time the particular aircraft spends in the runway queue before taking off from the runway can be determined. A runway queue take-off delay associated with the runway queue can be determined based at least in part on the amount of time the particular aircraft spends in the runway queue. The runway queue take-off delay can be communicated to a controller terminal of the airport to facilitate routing a different aircraft to a different runway queue associated with a shorter runway queue take-off delay to reduce fuel consumption by the different aircraft.

Abstract: A system and a method include at least one control unit that determines a de-icing time for an aircraft within a de-icing area of an airport, predicts a de-icing time for an aircraft within a de-icing area of an airport, schedules de-icing times for a plurality of aircraft within a de-icing area of an airport, and/or predicts demand for future de-icing operations of aircraft within a de-icing area of an airport.

Abstract: A method to reduce aircraft fuel consumption includes determining whether a particular aircraft belongs to a runway queue associated with one or more aircraft waiting to take-off from a runway of an airport based on (i) real-time aircraft geographic location information associated with the particular aircraft and (ii) a graph associated with features of the airport. An amount of time the particular aircraft spends in the runway queue before taking off from the runway can be determined. A runway queue take-off delay associated with the runway queue can be determined based at least in part on the amount of time the particular aircraft spends in the runway queue. The runway queue take-off delay can be communicated to a controller terminal of the airport to facilitate routing a different aircraft to a different runway queue associated with a shorter runway queue take-off delay to reduce fuel consumption by the different aircraft.

Abstract: The present disclosure provides predictive flight diversion management by: receiving weather data for a zone of air traffic control; receiving flight tracking data for a plurality of aircraft travelling in the zone of air traffic control; determining capacity rates for a plurality of airports in the zone of air traffic control, based on the flight tracking data; and in response to receiving a diversion trigger from a predictive model predicting a diversion event: determining, based on the weather data, the flight tracking data, and the capacity rates, a subset of aircraft from the plurality of aircraft that are to be diverted from original destinations in the zone of air traffic control to new destinations.