A system and method that uses one or more jet engines to remove unmanned aircraft from restricted airspace. Generally, the force created by a jet engine can be used to remove drones or other unwanted objects from the restricted airspace. Once the system determines the presence of an unauthorized aircraft or object within the restricted airspace, the jet engine(s) can be activated and used to pull the drone or flying object towards the jet engine though the force created by the intake of the jet engine(s), or to expel the drone or object from the restricted area through the force created by the exhaust of the jet engine(s).

A secure system for control of at least one unmanned aerial vehicle (UAV), includes a cloud service and a ground control station. The cloud service includes a cloud-based management service having processing circuitry configured to control communications between the cloud service, the ground control station and the at least one UAV, and control and monitor the at least one UAV by way of a corresponding at least one UAV client device. The UAV client device receives messages from the at least one UAV, sends commands to the at least one UAV, verifies the sender of each of the received messages, creates a new block for each received message and sent commands as new transactions, including performs a consensus algorithm for the new block, determines a consensus to validate the new block, and updates a blockchain with the validated new block.

A method for monitoring the take-off and/or landing procedure of an aircraft (1), in particular for an electrical, vertical take-off and landing aircraft (1), in which a monitoring region of a take-off and landing site (2) is monitored by at least one microphone (4, 5) of a monitoring station to detect sound emission data of an aircraft (1) taking off or landing as it approaches or departs and the detected sound emission data are transmitted from the monitoring station to an evaluation unit. The detected sound emission data are evaluated by the evaluation unit by comparing the detected sound emission data to characteristic sound emission data.

A communication system for an aircraft comprises a communication interface with the outside of the aircraft and an avionics domain of which the security level is the highest of the communication system. It also comprises a communication domain to which is connected the communication interface and of which the security level is lower than the security level of the avionics domain. A barrier of a first type is arranged to filter the information coming from the communication interface so as to allow the information to pass into the communication domain only if the information corresponds to an authenticated communication. A barrier of a second type is arranged to filter information transmitted from the communication domain to the avionics domain, carrying out at least a syntactic filtering of the information.

Disclosed herein is a system for facilitating real pilots in real aircraft using augmented and virtual reality to meet in a virtual piece of airspace, in accordance with some embodiments. Accordingly, the system may include a communication device configured for receiving at least one first sensor data corresponding to at least one first sensor associated with a first vehicle (and receiving at least one second sensor data corresponding to at least one second sensor associated with a second vehicle). Further, the communication device may be configured for transmitting at least one second presentation data to at least one second presentation device associated with the second vehicle. Further, the system may include a processing device configured for generating the at least one second presentation data based on the at least one first sensor data and the at least one second sensor data.

A method for coordinating multiplexed communication of data among multiple piloted assets and multiple requestors via a common software application includes receiving a mission request via the common software application, defining a common mission based on the mission request via the common software application, and coordinating the multiplexed communication using multiple communication channels. The coordinating includes exchanging data with multiple piloted aerial drone assets relaying a communication from one of the piloted assets to at least one other piloted asset, via the software application. When a new piloted asset joins the common mission, communication is facilitated via the software application between the further piloted asset and the multiple piloted assets. Upon detection that a piloted asset from the multiple piloted assets is no longer associated with the common mission, communication via the software application between that piloted asset and the remaining piloted assets is prevented.

Systems, methods and non-transitory computer readable storage media for airspace management within an airspace region at a node of a peer to peer network having a plurality of nodes and maintaining a blockchain containing a current deconflicted flight schedule for the airspace region. One method includes receiving requests for airspace reservations, each including flight plan data, from other nodes over the peer to peer network, compiling the flight plan data to identify conflicts between the requests and the current deconflicted flight schedule, validating the flight plan data of the requests that do not conflict with the current deconflicted flight schedule to generate validated airspace reservations, creating a block containing the validated airspace reservations and interlinking the block with the blockchain such that the blockchain contains a new deconflicted flight schedule for the airspace region for broadcast to the other nodes over the peer to peer network.

The present disclosure provides predictive flight diversion management by: receiving weather data for a zone of air traffic control; receiving flight tracking data for a plurality of aircraft travelling in the zone of air traffic control; determining capacity rates for a plurality of airports in the zone of air traffic control, based on the flight tracking data; and in response to receiving a diversion trigger from a predictive model predicting a diversion event: determining, based on the weather data, the flight tracking data, and the capacity rates, a subset of aircraft from the plurality of aircraft that are to be diverted from original destinations in the zone of air traffic control to new destinations.

A method includes generating an initial flight context that includes a set of unresolved flight constraints. The method further includes generating a decision tree based on the initial flight context. The decision tree includes a plurality of flight contexts corresponding to leaves of the decision tree. The method also includes expanding the decision tree according to a greedy best-first strategy that selects a flight context of the decision tree for expansion based on a fitness value assigned to the flight context. The method includes selecting, as a piloting strategy, a flight context of the decision tree that includes a sequence of actions to resolve each of the unresolved flight constraints. The method further includes flying an aircraft according to the piloting strategy.

Techniques for estimating the impact of new operational conditions in a baseline air traffic scenario are described. For at least one flight, embodiments infer an aircraft intent that fits corresponding flight track data. A reconstructed trajectory is computed using the inferred aircraft intent. For at least one flight in an alternative air traffic scenario, an aircraft intent that fits new operational conditions is generated. The new operational conditions include a new air traffic management operation and a new air traffic procedure, and the generated aircraft intent conforms to the new air traffic management operation and the new air traffic procedure. Embodiments compute a generated trajectory of the at least one flight in the alternative air traffic scenario using the generated aircraft intent and compute trajectory-based analytics on each computed trajectory of the baseline and alternative air traffic scenarios using a set of metrics.