Provided are a computer-implemented method, a computer program product, and a computer system for drone deployment for distributed asset maintenance and repair. Embodiments identify a fix for a problem at an asset and identify a drone to perform the fix. Embodiments generate an initial flight plan that describes a drone flight path for the drone, and embodiments generate an updated flight plan for the drone by updating the drone flight path using real-time air traffic data, real-time road traffic data, and real-time drone flight path conditions obtained from one or more edge devices. Embodiments generate an overall flight plan for the drone and one or more other drones using a predicted cost and a predicted period of time for the updated drone flight path. Embodiments send a drone flight path from the overall flight plan to the drone with instructions to fix the problem.

Systems, apparatus, and methods for providing data in a pre-determined format with minimal impact from an aircraft to an interested entity are disclosed. One system includes a data processing system configured to store executable code to receive data, wherein the data is otherwise unavailable to the interested entity via pre-existing technology, determine, in real-time, one or more first devices on the aircraft where the data is stored in a format that is non-compliant with the pre-determined format and/or one or more second devices on the aircraft where the data can be generated in the format that is non-compliant with the pre-determined format, and retrieve the data in the format that is non-compliant with the pre-determined format from the at least one of the one or more first devices and the one or more second devices. Apparatus and methods that include and/or perform the operations of the system are also disclosed.

Methods, apparatus, and systems are provided for an aircraft superhighway system comprising: at least one superhighway node and/or a plurality of spaced apart superhighway nodes/towers, wherein each superhighway node/tower has an overlapping coverage area (e.g. wireless communication coverage area and/or surveillance coverage area) with the coverage area of another adjacent superhighway node/tower and the airspace within each of the coverage areas forming a continuous airspace corridor or aircraft superhighway; and a superhighway controller in communication with at least one of the superhighway nodes/towers; wherein the superhighway controller is configured to use the superhighway nodes/towers for authorising, monitoring and controlling air traffic permitted to transit a flight path within one or more portions of the airspace corridor or aircraft superhighway.

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.

Systems, methods, and devices for automatic signal detection in an RF environment are disclosed. A sensor device in a nodal network comprises at least one RF receiver, a generator engine, and an analyzer engine. The at least one RF receiver measures power levels in the RF environment and generates FFT data based on power level data. The generator engine calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of the FFT data. The analyzer engine creates a baseline based on statistical calculations of the power levels measured in the RF environment for a predetermined period of time, and identifies at least one signal based on the first derivative and the second derivative of the FFT data in at least one conflict situation from comparing live power distribution to the baseline of the RF environment.

Various embodiments of a vision-guided unmanned aerial vehicle (UAV) system to identify and collect foreign objects from the surface of a body of water are disclosed herein. A vision system and methodology has been developed to reduce reflections and glare from a water surface to better identify an object for removal. A linearized polarization filter and a specularity-removal algorithm is used to eliminate excessive reflection and glare. A contour-based detection algorithm is implemented for detecting the targeted objects on water surface. Further, the system includes a boundary layer sliding mode control (BLSMC) methodology to reduce and minimize position and velocity errors between the UAV and object in the presence of modeling and parameter uncertainties due to variation in a moving water surface.

A system and a method include a control unit configured to monitor one or more values of one or more aircraft at one or more airports, and compare the one or more values with one or more attributes of one or more airport maps associated with the one or more airports to determine accuracy of the one or more airport maps.

A landing information determination apparatus according to this example embodiment includes an acquisition unit, a determination unit, and a communication unit. The acquisition unit acquires, for each of a plurality of landing places each including a facility on which an aircraft capable of autonomously flying can land, aircraft information being information concerning the aircraft flying in a surrounding area of a landing place, and place information being information concerning the landing place. The determination unit determines a landing place for each of the aircrafts and a flight path to the landing place, based on the aircraft information for each of the aircrafts, and the place information for each of the landing places, which are acquired by the acquisition unit. The communication unit transmits information indicating the landing place and the flight path for each of the aircrafts, which are determined by the determination unit, to the corresponding aircraft.

Provided herein are systems and methods for implementing air traffic control (ATC) voice communications over a digital aviation network, which allows one or more pilots on the ground to communicate with ATC controllers while piloting a UAS transiting the airspace of a particular ATC voice station. In one or more examples, a spectrum management system (or the ATC voice controller using information received from the spectrum management system) may designate a relay aircraft to relay very high frequency (VHF) ATC voice to operators/pilots on the aviation network. In one or more examples, upon initiation of voice communications by ATC to all UAS and other aircraft in a VHF service area or sector, the ATC analog voice message may be received by a VHF radio on the relay aircraft. In one or more examples, the relay aircraft may then relay the digital message to the ATC voice processor and/or base station.

Systems and methods for detecting potential theft and identifying individuals having a history of committing theft use an electromagnetic emission associated with a personal electronic device associated with an individual is received from at least one of a sensor that is coupled to at least one of a traffic camera or an aerial drone camera. One or more signal properties of the electromagnetic emission are analyzed to determine an emission signature. Video data and video analytics are correlated with the emission signature to identify the individual having possession of the item. The emission signature and video data are stored for later use during a checkout procedure. If an emission signature detected at a checkout station matches that of the individual having possession of the item, and the item is not processed through the checkout station, an alert is issued and the individual is flagged as a potential shoplifter.