An automated system and method for controlling a plurality of unmanned aerial vehicles (UAVs) is described. The system can include a receiver, a transmitter, and at least one processor in communication with a memory. The receiver receives first telemetric data from the plurality of UAVs. The transmitter is configured to transmit control data to the plurality of UAVs. The memory stores processor-issuable instructions to: substantially simultaneously determine a plurality of plans for each of the plurality of UAVs and for a predetermined time period based at least on the first telemetric data; and iteratively revise the plurality of plans.

An unmanned aerial vehicle according to the present disclosure is an unmanned aerial vehicle that can fly in midair and includes a propulsion unit configured to generate a propulsion force for fly in midair, a laser light source configured to illuminate laser light, an imaging unit configured to generate a captured image by capturing vertically below the unmanned aerial vehicle during flight in midair, and a controller configured to control an operation of the propulsion unit. The controller analyzes a captured image, extracts a light spot formed by laser light, measures a positional relationship with another unmanned aerial vehicle based on the extracted light spot, and executes a collision avoidance operation with respect to another unmanned aerial vehicle based on the measured positional relationship.

A system for flight tracking of an electric aircraft is presented. A system includes a non-volatile data storage unit. A non-volatile data storage unit is housed within a protective barrier of an electric aircraft. A non-volatile data storage unit is configured to receive flight data of an electric aircraft from a computing device. A non-volatile data storage unit is configured to record flight data. A non-volatile data storage unit is configured to categorize flight data to at least two flight data groups. A system includes a computing device. A computing device is housed within an electric aircraft. A computing device is configured to receive flight data from at least a sensor of an electric aircraft. A computing device is configured to convey flight data to a non-volatile data storage unit. A computing device is configured to transmit flight data to at least an external computing device.

A system and method for interference detection. The system and method receives flight data comprising a plurality of flights. The system and method identifies a plurality of signal drop events based on at least the flight data. The system and method determines one or more co-located signal drop event subsets based on at least the plurality of signal drop events and filter criteria. The system and method determines one or more interference events based on the one or more co-located signal drop event subsets, wherein each of the one or more co-located signal drop event subsets is based on at least two or more of the plurality of signal drop events.

A ground-based content curation platform identifies geographically-relevant content having metadata indicating a geographic relevance area which satisfies a relevance rule relative to the present location of the aircraft. The platform distributes the geographically-relevant content to an IFE system of the aircraft for local storage and access by passengers, wherein the geographically-relevant content is distributed through the at least one network interface and routed through a satellite radio communication system or a terrestrial radio communications system. The platform repeats the identification of geographically-relevant content and the distribution of the geographically-relevant content to initiate replacement of the geographically-relevant content at the IFE system, based on a threshold change in location of the aircraft.

Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.

An example system includes a processor to receive target asset information from an asset management system. The processor can generate an inspection mission based on the target asset information. The processor can generate unmanned aerial vehicle (UAV)-specific commands based on the inspection mission. The processor can transmit the UAV-specific commands to an unmanned aerial vehicle (UAV) platform. The processor can receive images and sensor data from the UAV. The processor can also send the images and sensor data to an artificial intelligence (AI) services module. The processor can receive feedback from the AI services module. The processor can further modify the inspection mission based on the feedback.

An operation management device is configured to acquire a subscriber ID to identify a subscriber joining a service using a mobile telephone line from a mobile terminal over the mobile telephone line, to acquire the position information representing the position of a flight device, which the mobile terminal acquires from the flight device before or during its flight over a wireless communication line different from the mobile telephone line, from the mobile terminal over the mobile telephone line, and to acquire a device ID to identify the flight device from the mobile terminal over the mobile telephone line.

Systems and methods for presenting an RTA waypoint with associated time constraints. The system includes a flight management system (FMS) providing an assigned flight plan with a plurality of waypoints; a display device configured to render a current location and trajectory of the aircraft in a navigation display and in a vertical display; and a controller circuit. The system locates the RTA waypoint among the plurality of waypoints, as a function of the flight plan and the current location and trajectory of the aircraft. The system identifies a time constraint associated with the RTA waypoint. The system uses the time constraint to determine a type, from among an “at”, a “before”, and an “after”, for the RTA waypoint; and, assigns a preprogrammed visual encoding scheme for the type to the RTA waypoint. The system presents the RTA waypoint, using the visual encoding scheme, on the display device.

Herein provided is an interface for use in transmitting data from an aircraft including a first connector configured for physically and removably coupling a communication module to a communication system which obtains the data on-board the aircraft from at least one data source within the aircraft, and a second connector for digitally coupling the communication module to a processing unit of the communication module producing at least one message for transmission based on the data, the at least one message comprising information of interest identified based on the data. The interface is configured for conducting the at least one message from the processing unit to at least one radio via the second connector.