Methods, devices, and systems for aircraft identification are described herein. In some examples, one or more embodiments include a computing device comprising a memory and a processor to execute instructions stored in the memory to simulate virtual light detection and ranging (Lidar) sensor data for a three-dimensional (3D) model of an aircraft type to generate a first point cloud corresponding to the 3D model of the aircraft type, generate a classification model utilizing the simulated virtual Lidar sensor data of the 3D model of the aircraft type, and identify a type and/or sub-type of an incoming aircraft at an airport by receiving, from a Lidar sensor at the airport, Lidar sensor data for the incoming aircraft, generating a second point cloud corresponding to the incoming aircraft utilizing the Lidar sensor data for the incoming aircraft, and classifying the second point cloud corresponding to the incoming aircraft using the classification model.

A vehicle connectivity and communication device includes at least one transmitter/receiver for establishing and maintaining communications with a system for controlling and/or monitoring vehicles and/or traffic over at least two different communications infrastructures, at least one sensor for measuring and reporting a performance characteristic of communication over the different communications infrastructures, and a controller for selecting an active communications infrastructure based on the measured performance characteristic.

Concepts and technologies disclosed herein are directed to intelligent drone traffic management via a radio access network (“RAN”). As disclosed herein, a RAN node, such as an eNodeB, can receive, from a drone, a flight configuration. The flight configuration can include a drone ID and a drone route. The RAN node can determine whether capacity is available in an airspace associated with the RAN node. In response to determining that capacity is available in the airspace associated with the RAN node, the RAN node can add the drone ID to a queue of drones awaiting use of the airspace associated with the RAN node. When the drone ID is next in the queue of drones awaiting use of the airspace associated with the RAN node, the RAN node can instruct the drone to fly through at least a portion of the airspace in accordance with the drone route.

Various embodiments of the present disclosure provide method and apparatus for aircraft traffic management. The method performed by an aircraft traffic management device comprises determining at least one cell shaping parameter based on cell information and a flight route of an aircraft. The method further comprises sending a request for creating at least one cell shaping beam for covering at least a part of the flight route of the aircraft to an operations support system, OSS, wherein the request includes the at least one cell shaping parameter.

In an electronic monitoring system, an array of ground-level sensors and aircraft sensors are integrated to provide comprehensive security and privacy sensing of different types of threats. Information from the ground-level sensors may be used to augment the detection and identification of aircraft such as piloted airplanes or unmanned drones, and a white list system may be used to reduce false positive alerts for routine delivery aircraft and the like.

The present invention discloses a receiver and transmitter of enroute aircraft data (RATEAD) system and method of tracking missing aircraft by the system. The system comprising: a plurality of network enabled devices at a plurality of locations; and said plurality of network enabled devices are communicatively coupled to an aircraft passing within a pre-defined range, wherein a data of said in range aircraft is communicatively transmitted in real-time to a network device of said plurality of network enabled devices with which said aircraft is connected.

A vessel monitoring service obtains transponder data of a vessel operating within a navigable area. In response to obtaining the transponder data of the vessel, the vessel monitoring service evaluates the transponder data and a plurality of travel segments recorded for a plurality of vessels to identify a travel segment to which the transponder data corresponds. The vessel monitoring service updates the travel segment using the transponder data and determine whether the vessel is engaged in an unauthorized activity. If so, the vessel monitoring service provides an indication that the vessel is engaged in the unauthorized activity.

A generation method of a sequence (Ot1, OT2 . . . 0Tn) of arrival times at the IAF of a plurality of aircrafts (A1, A2 . . . An) which must arrive at a specific airport (IC) is described, said method comprising:—Establishing (B1, B2 . . . Bn) at least one first (LT1, LT2 . . . LTn) and a second (ET1, ET2 . . . ETn) estimate arrival times at the IAF as a function of the minimum (Vmin1, Vmin2 . . . Vminn) and the maximum (Vmax1, Vmax2 . . . Vmaxn) cruise speed of each aircraft and as a function of the cruise altitude (H1, H2 . . . Hn) and the descendent angle (ANG1, ANG2 . . . ANGn) of the aircraft by means of a first device (1) arranged inside each aircraft of the plurality of aircrafts;—Sending (C1, C2 . . . Cn) said first and second estimate arrival times at the IAF of each aircraft from the first device (1) arranged inside each aircraft of the plurality of aircrafts to a second device (2) arranged inside said specific airport (IC) when each aircraft of the plurality of aircraft (A1 . . . An) is in flight towards the specific airport (IC);—Defining (F2) a sequence (BS, NS) of arrival times at the IAF for each single aircraft of said plurality of aircrafts as a function of said first and second estimate arrival times at the IAF and at least the wake turbulence data (WT1, WT2 . . . WTn) of each aircraft and the airport receptivity (RA) of said specific airport (IC), said defining step comprising:—Extracting (F21, F41) from a database (DWT) said wake turbulence data (WT1, WT2 . . . WTn) of the plurality of aircrafts (A1, A2 . . . An); Grouping (F22, F42) the aircrafts having the same wake turbulence category and the arrival time at the IAF of which is inside a time window comprised between the first and second estimate arrival times at the IAF and considering as time distance among the different arrival times at the IAF the time distance (DS) due to the wake turbulence of the preceding aircraft in the sequence of arrival times at the IAF or the airport receptivity (RA) in the case wherein said airport receptivity (RA) is larger than said time distance (DS), said method comprising successively:—Sending (F3) the defined arrival time at the IAF (OT1, OT2 . . . 0Tn) for each single aircraft which is defined by said second device with the definition of the defined sequence of arrival times at the IAF to each first device of the single aircraft of the plurality of aircrafts for the arrival at

In a method of real-time network monitoring and location updating, a location report is received by an unmanned aerial system application enabler (UAE) server from a location management (LM) server. The location report indicates location information of a user equipment (UE). A first network event notification associated with the UE is received by the UAE server from a network resource management (NRM) server. The first network event notification indicates a connection status of the UE with a network. In response to detecting a re-connected status of the UE, a second networking event notification is received by the UAE server from the NRM server. The second networking event notification indicates that the UE reconnects to the network. Further, (i) the second networking event notification, (ii) an identity of the UAE server, and (iii) most recently updated location information of the UE from the LM server are recorded by the UAE server.

A management system comprises a movement management unit that communicates via a communication device with a plurality of moving bodies including an autonomous moving body provided with an autonomous control unit for moving autonomously, and that manages the movement of the plurality of moving bodies. The movement management unit comprises a priority/subordination determination unit that determines the degree of priority/subordination relating to the respective movements of the plurality of moving bodies on the basis of individual information of the moving bodies. The autonomous moving body comprises: a priority/subordination comparison unit that compares another priority/subordination degree, which is a degree of priority/subordination determined by the priority/subordination determination unit for another moving body that is a moving body, from among the plurality of moving bodies, different from the autonomous moving body, and the host priority/subordination degree, which is a degree of priority/subordination determined by the priority/subordination determination unit for the autonomous moving body; or a priority/subordination reception unit that receives the comparison results of the host priority/subordination degree and the other priority/subordination degree obtained by comparisons by the moving body management unit.