Systems and methods are disclosed for transporting people using air vehicles.

A user terminal generates a virtual drone camera image, as an estimated captured image where it is assumed that a virtual drone camera mounted on a drone has captured an image of a planned landing position on the basis of a captured image obtained by capturing the planned landing position of the drone with the user terminal, and transmits the generated virtual drone camera image to the drone. The drone collates the virtual drone camera image with the image captured by the drone camera and lands at the planned landing position in the image captured by the drone camera. The user terminal generates a corresponding pixel positional relationship formula indicating a correspondence relationship between a pixel position on the captured image of the user terminal and a pixel position on the captured image of the virtual drone camera, and generates the virtual drone camera image using the generated relationship formula.

A method comprises receiving a route of an aircraft, identifying a plurality of service providers to provide data services for the aircraft based on the route, receiving data from the plurality of service providers associated with the data services, transmitting the data received from the plurality of service providers to the aircraft, determining a total amount associated with all of the data services provided by the plurality of service providers, and transmitting information on the total amount associated with all of the data services provided by the plurality of service providers.

Locating, aiding, and communicating with users and personnel in emergency situations by traversing a defined path utilizing an unmanned vehicle, detecting a user within a threshold distance of the defined path, logging a geolocation of the user within the unmanned vehicle, and determining whether to dispatch assistance to the user.

A population density map of a region is generated by dividing the region into cells and allocating a population of the region only to the cells that are accessible to people, or are believed to be populated. Each of the cells is classified based on one or more ground features of the cells, and an adjustment factor for each of the cells is determined based at least in part on the classifications. Equal shares of the population of the region are allocated to each of the cells that is accessible or populated, and the equal shares are multiplied by the adjustment factors determined for the respective ones of the cells to calculate a population for each of such cells.

Navigation beacons may be trained to receive signals of opportunity from one or more vehicles, to recognize their own position based on such signals, and to transmit information regarding their own position to one or more other vehicles accordingly. The navigation beacons may be of small size and feature a basic construction including one or more transceivers, power sources and the like, and may communicate via a Bluetooth® Low Energy, Ultra Wideband or long-range low-power wireless standard, or any other standard. The navigation beacons may be installed in any location, preferably being mounted to one or more existing fixed structures or facilities (e.g., transportation structures or facilities), and may operate in active and/or passive modes when learning their positions or servicing position information to one or more remote devices.

An aircraft includes a short-range radar that is configured to detect a trajectory, which is specified based on a position detection of the aircraft by a ground station.

An information processing apparatus includes an accumulation unit that accumulates history information regarding a flight history of an aircraft. A specification unit, based on the history information accumulated by the accumulation unit, specifies a candidate to be an operation assistant who assists an operation planned by an assisted operator. An output unit outputs information regarding the candidate to be the operation assistant specified by the specification unit.

The present disclosure aims to implement UAV (unmanned aerial vehicle) logistics operation and air traffic control in flyable airspace technically through a UAV task planning system, which depends on blockchain technology to carry out UAV air traffic surveillance on flight segments in a predetermined barrier-free airway and optimize air traffic according to a safe separation distance for fewest UAV operators, air traffic controllers, communications links and airborne loads.

Provided is a user equipment for controlling a drone. The user equipment analyzes an original video to control the drone to photograph a reproduction video giving a feeling identical to or similar to the original video. An electronic device may be connected to an artificial intelligence module, a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G service, and the like.