Abstract: Baggage is connected to an aerial vehicle in a state in which the baggage is suspended by a connector such as rope. A learning unit of a server device performs machine learning on the relationship between the piloting of an aerial vehicle and the behavior of baggage on the basis of an aerial vehicle behavior history and a piloting history acquired by a first acquisition unit and a baggage behavior history acquired by a second acquisition unit. With this arrangement, the automatic piloting of the aerial vehicle at the time of lowering baggage is achieved.

Abstract: Setting unit performs the setting of each of the operating modes of a plurality of aerial vehicles on the basis of communication quality information of the planned route of the plurality of aerial vehicles that fly in a group. Specifically, setting unit firstly specifies the planned positions and periods in which each aerial vehicle is to fly from the flight plan information of the plurality of aerial vehicles that fly in a group. Next, setting unit specifies a communication quality of first wireless communication unit of each aerial vehicle in each position and each period from the communication quality information that represents the communication quality in the specified positions and periods. Then, setting unit specifies an operating mode setting schedule of main unit mode and auxiliary unit mode, which sets an aerial vehicle having a specified communication quality, and sets the remaining aerial vehicles as auxiliary units.

Abstract: A setting unit sets the operating mode of an aerial vehicle to a first operating mode that transmits, data generated by a host aerial vehicle and data received from another aerial vehicle to a processing device, or a second operating mode that transmits data generated by a host aerial vehicle to another aerial vehicle. At this time, setting unit sets the operating modes of each of a plurality of aerial vehicles using a setting method corresponding to the attributes of an airspace in which aerial vehicle flies, from among a plurality of setting methods that set the operating mode of aerial vehicle. The attributes of an airspace include attributes determined in accordance with a degree of importance pertaining to the process of transmitting data from aerial vehicle to a server device and/or attributes determined in accordance with the extent to which processes are distributed among a plurality of aerial vehicles.

Abstract: Setting unit performs the setting of each of the operating modes of a plurality of aerial vehicles on the basis of communication quality information of the planned route of the plurality of aerial vehicles that fly in a group. Specifically, setting unit firstly specifies the planned positions and periods in which each aerial vehicle is to fly from the flight plan information of the plurality of aerial vehicles that fly in a group. Next, setting unit specifies a communication quality of first wireless communication unit of each aerial vehicle in each position and each period from the communication quality information that represents the communication quality in the specified positions and periods. Then, setting unit specifies an operating mode setting schedule of main unit mode and auxiliary unit mode, which sets an aerial vehicle having a specified communication quality, and sets the remaining aerial vehicles as auxiliary units.

Abstract: A server device performs machine learning on the relationship between the content of piloting of an aerial vehicle and the behavior of the aerial vehicle in response to the content of the piloting, and generates a learning model for automatically piloting the aerial vehicle. However, the aerial vehicle is piloted in various environments and conditions, and there are environments and conditions that are unsuited for achieving highly accurate and stable automatic piloting. Therefore, the server device performs the machine learning only in an environment or a condition suited for realizing the automatic piloting.

Abstract: Baggage is connected to an aerial vehicle in a state in which the baggage is suspended by a connector such as rope. A learning unit of a server device performs machine learning on the relationship between the piloting of an aerial vehicle and the behavior of baggage on the basis of an aerial vehicle behavior history and a piloting history acquired by a first acquisition unit and a baggage behavior history acquired by a second acquisition unit. With this arrangement, the automatic piloting of the aerial vehicle at the time of lowering baggage is achieved.

Abstract: In a server device, an acquisition unit acquires information generated by a first detection unit and a second detection unit through a network. An identification unit identifies a wind condition and the state of flight of an aerial vehicle on the basis of the information acquired by the acquisition unit. More specifically, the identification unit identifies the wind direction and the wind speed, which indicate the wind condition, and the position, the flight direction, and the flight speed of the aerial vehicle, which indicate the state of flight of the aerial vehicle. The estimation unit estimates a landing area where the aerial vehicle is likely to land according to the wind condition and the state of flight of the aerial vehicle which have been identified.