The Boeing Company

Pablo Costas

Javier Lopez Leones

Enrique Casado

Nicolas Pena Ortiz

Guillermo Frontera

Alejandro Guemes Jimenez

Nicolas PEÑA Ortiz

Javier LÓPEZ LEONÉS

Apparatuses, methods, systems, and program products are disclosed for dynamic selection of an aeronautical data provider. An apparatus includes a processor and a memory that stores code executable by the processor to receive a first stream of real-time aeronautical data from a first aeronautical data provider, receive at least one second stream of real-time aeronautical data from at least one second aeronautical data provider simultaneously with the first stream, provide data from the first stream and the at least one second stream to a decision model for predicting which data has a higher accuracy, and switch using data from the first stream to data from one of the at least one second streams in response to the one of the at least one second streams having a higher predicted accuracy than the first stream.

Dynamic selection of an aeronautical data provider

A device for flight data prediction includes a memory, a communication interface, and one or more processors. The memory is configured to store a departure airport map. The communication interface is configured to receive location data for a plurality of aircraft expected to arrive at or depart from a departure airport during a particular time range. The one or more processors are configured to predict, based on the location data and the departure airport map, a taxi duration or a fuel usage of a first aircraft of the plurality of aircraft. The one or more processors are also configured to generate an output based on the taxi duration or the fuel usage.

Systems and methods for predicting flight data

A method and system for autonomously operating an aircraft. The method comprises a pre-flight training step comprising: retrieving recorded surveillance data of a plurality of flights corresponding to at least one aircraft type and at least one route; inferring aircraft intent from the recorded surveillance data; computing reconstructed trajectories using the inferred aircraft intent; selecting a training dataset comprising aircraft intent and reconstructed trajectories of flights corresponding to a particular aircraft type and route; and applying a machine learning algorithm on the training dataset to obtain a mapping function between aircraft states and actions. The method further comprises a real-time control step executed during a flight of an aircraft, the real-time control step comprising: repeatedly retrieving onboard sensor data; obtaining real-time aircraft states from the onboard sensor data; determining actions associated to the real-time aircraft states using the mapping function; and executing the selected actions on the aircraft.

Method and system for autonomously operating an aircraft

A computer-implemented method and a system for providing passenger information performing the tasks of sending, from a passenger electronic device (), personal data, device geolocation and device time-stamp information; obtaining the passenger itinerary and confirming passenger identity, by a managing unit (), based upon a match between the personal data, passenger electronic device geolocation and time-stamp; information contained in the obtained passenger itinerary; accessing to updated air traffic information relevant to the passenger upon confirming the passenger identity and sending, by the managing unit (), a passenger report comprising flight status information for display on the passenger electronic device ().

Growing community of inventors

Madrid, Spain

Pablo Costas