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

An autonomous base station for unmanned aerial vehicles (‘UAVs’) is disclosed, which includes a landing surface for a UAV, configured with at least one power transfer bus for supplying power to a power source of a UAV thereon. The base station further includes a networking module and data processing means operably connected to, and configured to control, the power transfer bus and the networking module. The data processing means is operably connected to the UAV through the networking module, and further configured to receive, store and process data from the UAV or another. The base station further includes a power supply operably connected to the or each power transfer bus, the or each networking module and the data processing means. A network of at least two such base stations is also disclosed, for sensing, modelling and monitoring an environment with UAVs.

A system for exploiting a transmitted signal from an aircraft or drone to determine parameters of the aircraft or drone's motion. The system includes at least one antenna for receiving the transmitted signal from the aircraft, and an analysis system for analyzing the transmitted signal as compared with stored characteristic anomalies associated with any of the aircraft or drone, and the at least one antenna, for confirming parameters of the aircraft or drone's motion.

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.

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.

A system for preconditioning a power source of an electric aircraft is presented. The apparatus includes a power source of an electric aircraft, a computing device, and a user device. The computing device is configured to receive a flight plan, determine a predicted power usage model as a function of the flight plan, and initiate a power source modification on the electric aircraft as a function of the predicted power usage model. The user device is configured to display a flight performance infographic as a function of the predicted power usage model.

A system for flight control system using simulator data for an electric aircraft is presented. The system includes a computing device, the computing device configured to receive a plurality of measured flight data, simulate a plurality of aircraft performance model outputs as a function of a flight simulator and the plurality of measured flight data, determine a moment datum as a function of the plurality of measured flight data and the plurality of aircraft performance model outputs, generate an allocation command datum as a function of the moment datum and the plurality of aircraft performance model outputs, and perform a torque allocation on a flight component of a plurality of flight components as a function of the allocation command and the moment datum.

A distributed airborne acoustic anti-drone intelligence system (DAAADS) which senses an unmanned aerial vehicle (UAV) approaching a protected site, predicts trajectories of the UAV which intersect the protected site and identifies the type of the UAV. When at least one of the trajectories intersect the protected site, an alarm and predicted trajectories are transmitted to an air defense unit, which neutralizes the UAV. Debris generated by the neutralization is tracked and trajectories of the debris are predicted. When a trajectory of the debris is predicted to intersect with the protected site, an alert is transmitted to the protected site.

A flight management system for unmanned aerial vehicles (UAVs), in which the UAV is equipped for cellular fourth generation (4G) flight control. The UAV carries on-board a 4G modem, an antenna connected to the modem for providing for downlink wireless RF. A computer is connected to the modem. A 4G infrastructure to support sending via uplink and receiving via downlink from and to the UAV. The infrastructure further includes 4G base stations capable of communicating with the UAV along its flight path. An antenna in the base station is capable of supporting a downlink to the UAV. A control centre accepts navigation related data from the uplink. In addition, the control centre further includes a connection to the 4G infrastructure for obtaining downlinked data. A computer for calculating location of the UAV using navigation data from the downlink.

The invention discloses a method to support the trajectory planning considering both the flight trajectory and the visual images (VI) from air traffic control (ATC) system for air traffic controllers (ATCOs) (VI from ATC system for ATCOs), comprising the following steps: Step 1: acquire the VI and the flight trajectory to serve as the method inputs, and extract features of the VI and the relative position of the aircraft; Step 2: construct reinforcement learning-based methods to support the decision-making for flight path planning and conduct the training procedures of the models in the proposed method; Step 3: based on the optimized reinforcement learning-based methods, predict the required operation sequence to guide the flight to the target waypoint. The method of the invention can support the flight path planning for air traffic operation in a safe and efficient manner and is able to reduce the workload of air traffic controllers.