A monitoring system for an aircraft uses sensors configured to sense objects around the aircraft to generate a recommendation that is ultimately used to determine a possible route that the aircraft can follow to avoid colliding with a sensed object. A first algorithm generates guidance to avoid encounters with sensed airborne aircrafts. A second algorithm generates guidance to avoid encounters with sensed non-aircraft airborne obstacles and ground obstacles. The second algorithm sends inhibiting information to the first algorithm in a feedback loop based on the position of sensed non-aircraft objects. The first algorithm considers this inhibiting information when generating avoidance guidance regarding airborne aircrafts.

A system to assess the current, or future workload of a pilot and automatically providing annunciation when needed to the pilot, as well as to resources that support the pilot. The system may automatically, and without pilot involvement, assess the workload for the pilot based on incoming events and abnormal scenarios. The predicted incoming events may be related to operation data, such as navigation information, weather, traffic avoidance, and so on. The system may also detect abnormal scenarios, such as engine warnings, fuel or other aircraft issues. The system may determine whether the predicted incoming events or the abnormal scenario satisfies one or more pre-defined criteria. Based on the event satisfying one or more criteria, the system may output an annunciation to either the pilot, resources that support the pilot, such as an additional pilot and air traffic control (ATC).

A method for supporting aerial operation over a surface includes obtaining a three-dimensional (3D) representation of the surface; converting the 3D representation of the surface to a two-dimensional (2D) representation of the surface; obtaining a 2D flight path of the aircraft based on the 2D representation of the surface; converting the 2D flight path to a 3D flight path including location coordinates; and controlling the aircraft to conduct a flight mission following the 3D flight path.

The present disclosure provides a system for monitoring unstructured environments. A predetermined path can be determined according to an assignment of geolocations to one or more agronomically anomalous target areas, where the one or more agronomically anomalous target areas are determined according to an analysis of a plurality of first images that automatically identifies a target area that deviates from a determination of an average of the plurality of first images that represents an anomalous place within a predetermined area, where the plurality of first images of the predetermined area are captured by a camera during a flight over the predetermined area. A camera of an unmanned vehicle can capture at least one second image of the one or more agronomically anomalous target areas as the unmanned vehicle travels along the predetermined path.

In an aspect of the present disclosure is a system for in-flight re-routing of an electric aircraft including a battery pack configured to provide electrical power to the electric aircraft; a sensor configured to detect at least a temperature metric of the battery pack and generate a temperature datum based on the at least a temperature metric; a controller communicatively connected to the sensor, the controller configured to: receive the temperature datum from the sensor; and re-route the electric aircraft based on the temperature datum.

The present invention relates to a method and system for gathering data along points of travel using common portable electronic devices that are typically used for other functions. More specifically, the data gathered by these portable electronic devices may be accessed, processed, validated, and used in conjunction with, or alone, to produce, augment, and/or validate other data sets across wide ranges of science and technology.

A system and method for autonomous flight control with mode selection an electric aircraft is illustrated. The system comprises an altitude-related sensor and a computing device. The altitude-related sensor is coupled to the electric aircraft and is configured to detect an altitude value. The computing device is communicatively connected to the altitude-related sensor and is configured to receive the altitude value from the altitude-related sensor, to determine a flight mode as a function of the altitude value and an altitude threshold, to determine an aircraft adjustment as a function of a determine flight mode, and to generate an autonomous function configured to enact the determined flight mode and an aircraft adjustment automatically.

A method for automatically proposing an air conflict resolution, the method includes a step of receiving air conflict and air situation data at a time when an air conflict is detected, the method comprising the steps of: determining a conflict category associated with the detected air conflict based on the conflict data; determining a degree of relevance in proposing a resolution to the air conflict according to the category and the air situation; determining one or more types of resolution to be applied to resolve the detected air conflict according to the degree of relevance; determining set of alternative trajectories corresponding to the one or more types of resolution; determining a set of candidate trajectories from among the set of alternative trajectories, a candidate trajectory being an alternative trajectory which does not generate an air conflict; selecting, from among the candidate trajectories, a candidate trajectory which fulfills a selection criterion relating to the operational relevance of the candidate trajectories and to the acceptability of the candidate trajectories by the flight plan management system; returning the candidate trajectory, the candidate trajectory being saved and re-evaluated as long as it does not generate an air conflict or has not been accepted by an air traffic controller.

According to a technical aspect of the invention, there is provided a multiple unmanned aerial vehicles navigation optimization method is performed at a ground base station which operates in conjunction with unmanned aerial vehicles-base stations which are driven by a battery to move and cover a given trajectory point set, the multiple unmanned aerial vehicles navigation optimization method including: calculating an age-of-information metric by receiving an information update from the unmanned aerial vehicles-base stations through communication, when the ground base station is present within a transmission range of the unmanned aerial vehicles-base stations; setting conditions of a trajectory, energy efficiency, and age of information of each of the unmanned aerial vehicles-base stations; and executing Q-learning for finding a trajectory path policy of each of the unmanned aerial vehicles-base stations, so as to maximize total energy efficiency of an unmanned aerial vehicles-base station relay network to which the energy efficiency and the age of information are applied. According to the invention, the following effects are obtained. Age of information (AoI) that is a new matrix used to measure up-do-dateness of data is set, an edge computing environment for a remote cloud environment is provided by using the AoI, and a computing-oriented communications application can be executed by using the edge computing environment.

The invention relates to an electronic device generating a flight plan for an aircraft, comprising: a display module configured for displaying two flight plans simultaneously and for each flight plan, for viewing, the common elements and distinct elements with regard to the other flight plan. an acquisition module configured for acquiring a copy command. a copying module configured for copying at least one of the distinct elements from one of the two flight plans to the other flight plan based on the copy command; and a processing module configured for generating a new flight plan based on the target flight plan and the distinct element or elements which were copied.