A method for providing medical services to a patient, including: receiving a medical service request associated with a patient location; selecting an aircraft, located at an initial location, from a plurality of aircraft based on the patient location and the initial location; determining a flight plan for flying the aircraft to a region containing the patient location; at a sensor of the aircraft, sampling a first set of flight data; at a processor of the aircraft, autonomously controlling the aircraft to fly based on the flight plan and the set of flight data; selecting a landing location within the region; and landing the aircraft at the landing location, including: sampling a set of landing location data; determining a safety status of the landing location based on the set of landing location data; outputting a landing warning observable at the landing location; at the sensor, sampling a second set of flight data; and in response to determining the safety status and outputting the landing warning, autonomously controlling the aircraft to land at the landing location based on the second set of flight data.

A terminal area noise management method includes receiving, at a processor, aircraft information for an aircraft operating in a region in proximity to an airport; accessing a plurality of terminal area flight paths available to the aircraft; estimating a plurality of noise profiles for the aircraft, one estimated noise profile for the aircraft for each of the plurality of flight paths; calculating a plurality of cumulative noise fairness measures using each estimated noise profile; calculating a plurality of operational efficiency values for the aircraft, one or more of the calculated operational efficiency values for the aircraft for each of the flight paths; calculating a plurality of cumulative operational fairness measures using each of the calculated operational efficiency values; and selecting a flight path for the aircraft based on maximizing a cumulative noise fairness measure and a cumulative operational fairness measure.

Unmanned Aerial Vehicle (UAV) air traffic control and monitoring systems and methods implemented by a consolidated system include communicating with a plurality of servers each configured to communicate with a plurality of UAVs in a geographic or zone coverage; consolidating data from the plurality of servers to provide a visualization of a larger geography comprising a plurality of geographic or zone coverages; providing the visualization via a Graphical User Interface (GUI); and performing one or more functions via the GUI for air traffic control and monitoring at any of a high-level and an individual UAV level.

The invention relates to systems, methods and computer readable medium to construct map(s) of an aerodrome mapping database (AMDB). A method digitizes imagery for constructing AMDB, including entering data of the imagery into computer memory, displaying the imagery on a computer, displaying user selectable predefined target feature types that correspond to features of the imagery on the computer screen, displaying user selectable attributes of each of the predefined target feature types, automatically populating each predefined target feature type with subfeatures, associating attributes with each predefined target feature type and subfeature, snapping each predefined target feature type to coincide with the center of a pixel to provide predictability of horizontal accuracy, displaying a Bézier curve template to align a curved part of a predefined target feature type to a curved part of the imagery producing a digitized map and storing the digitized map in an AMDB.

Disclosed are an airport control decision support system and method based on semantic recognition of a controller instruction. The system includes a speech acquisition module, a noise processing module, a speech recognition module, a semantic recognition module, a conflict recognition module, and an alarm display terminal. The system can effectively eliminate accidents and potential accidents thereof caused by human factors in a control process, and can improve safety of aircraft ground operation. Different from ordinary speech recognition and semantic recognition, data annotation of pronunciation and intonation is performed based on special pronunciation of air traffic control, and finally a speech database that conforms to airport control standard phrases is constructed. The airport control decision support system is implemented by installing a speech acquisition device and the alarm display terminal in a control seat, and thus the system is economical and practical.

A method for providing medical services to a patient, including: receiving a medical service request associated with a patient location; selecting an aircraft, located at an initial location, from a plurality of aircraft based on the patient location and the initial location; determining a flight plan for flying the aircraft to a region containing the patient location; at a sensor of the aircraft, sampling a first set of flight data; at a processor of the aircraft, autonomously controlling the aircraft to fly based on the flight plan and the set of flight data; selecting a landing location within the region; and landing the aircraft at the landing location, including: sampling a set of landing location data; determining a safety status of the landing location based on the set of landing location data; outputting a landing warning observable at the landing location; at the sensor, sampling a second set of flight data; and in response to determining the safety status and outputting the landing warning, autonomously controlling the aircraft to land at the landing location based on the second set of flight data.

The method of the present invention comprises acquiring input data of both aircraft performance characteristics and atmospheric data, and defining trajectory parameters to which the aircraft trajectory must be subjected, the method further comprising defining aircraft trajectory parameters; acquiring a plurality of atmospheric forecast ensembles; calculating a predicted trajectory from each atmospheric forecast of an atmospheric forecast ensemble, said predicted trajectory having associated information regarding a certain figure of merit of the aircraft trajectory, wherein an ensemble of predicted trajectories is obtained from each atmospheric forecast ensemble, each predicted trajectory of the ensemble of predicted trajectories having an associated probability derived from the probability of each atmospheric forecast within an atmospheric forecast ensemble; the system of the present disclosure comprising all the necessary equipment to carry out the method of the present disclosure.

Described is an airborne monitoring station (“AMS”) for use in monitoring a coverage area and/or unmanned aerial vehicles (“UAVs”) positioned within a coverage area of the AMS. For example, the AMS may be an airship that remains at a high altitude (e.g., 45,000 feet) that monitors a coverage area that is within a line-of-sight of the AMS. As UAVs enter, navigate within and exit the coverage area, the AMS may wirelessly communicate with the UAVs, facilitate communication between the UAVs and one or more remote computing resources, and/or monitor a position of the UAVs.

A method to operate a system in support of air traffic control of an airport provides, automatically, to operators, in the same screen, status information for the systems required during low visibility operation, meteorological information and runway category of operation, making easier the operation of the controller and increasing airport security. The method comprises monitoring the status of all low visibility operation systems, calculation of a category more convenient for the operation of the airport runway, and degradation automatic (down grade) when it degrades a key system and upgrade or downgrade manually the category by operator decision. The method includes an architecture oriented for high availability with three blocks (Management, Input/Output and Visualization) and uses an application “alive” that performs automatic switching between servers, in case of failure or malfunction of one of them, increasing the availability of the system.

A computation of the processing complexity of an air-traffic-control situation is provided. In particular, the processing complexity of an air-traffic-control situation is computed using a supervised learning engine, trained using the result of analytical functions for computing the processing complexity of air-traffic-control situations.