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 system and method for optimizing mission fulfillment via unmanned aircraft systems (UAS) within a mission space generates or receives atmospheric models forecasting weather and wind through the mission space, the atmospheric models having an uncertainty factor. Until the projected flight time, the controller may iterate through one or more simulations of a projected flight plan through the mission space, determining the probability of successful fulfillment of mission objectives based on the most current atmospheric models (including the ability of the UAS to navigate the flight plan within authorized airspace constraints). Based on conditions and behaviors observed during a simulated flight plan, the controller may revise flight plans, flight times, or atmospheric models for subsequent simulations. Based on multiple probabilities of fulfillment across multiple simulations, the controller selects an optimal flight plan and/or flight time for fulfillment of the assigned set of mission objectives.

A flight data aggregation system for a plurality of aircraft includes one or more portable electronic devices in electronic communication with one or more central computers. The one or more portable electronic devices each monitor flight data from a corresponding aircraft. The one or more portable electronic devices analyze the flight data in real-time to determine an insight event indicating an incident of significance is presently occurring upon the corresponding aircraft. Each central computer includes one or more processors and a memory coupled to the one or more processors. The central computers are caused to receive the flight data collected during the insight event from an individual portable electronic device. The central computers determine overall flight data patterns based on the flight data collected during the insight event received from the individual portable electronic device and historical data stored in the one or more databases.

Various embodiments of a system and method for a quantitative approach and departure risk assessment are described. In one example, the system includes program instructions executable in the computing device that, when executed by the computing device, cause the computing device to: obtain a nominal flight path of an aircraft, calculate a potential crash area for a section of the nominal flight path based on a failure mode, calculate risk values based on a population data of a geographical area traveled corresponding to the nominal flight path, and display the calculated risk values plotted on a map of at least a section of the geographical area traveled corresponding to the nominal flight path. Other examples include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

An enhanced vision system comprising a camera, a memory, and a processor. The camera configured to capture video of a field of view and output a plurality of frames, each frame including a respective sensor pixel value for each of a plurality of sensor pixels. The memory configured to store the plurality of frames and a threshold sensor pixel value. The processor configured to receive the plurality of frames, identify, in each of the plurality of frames output over a first period of time, one or more sensor pixel values above a threshold sensor pixel value, enhance a current frame by changing corresponding sensor pixel values of the current frame based on each of the identified one or more sensor pixel values above the threshold sensor pixel value, and generate an enhanced video of the field of view including the enhanced current frame to be presented on a display.

A system and apparatus for assisting in determining the best course of action at any point inflight for an emergency. The system may monitor a plurality of parameters including atmospheric conditions along the flight path, ground conditions and terrain, conditions aboard the aircraft, and pilot/crew data. Based on these parameters, the system may provide continually updated information about the best available landing sites or recommend solutions to aircraft configuration errors. In case of emergency, the system may provide a pilot with a procedure for execution for landing the aircraft.

Vertical take-off and landing (VTOL) aircraft can provide opportunities to incorporate aerial transportation into transportation networks for cities and metropolitan areas. However, VTOL aircraft may be noisy. To accommodate this, the aircraft may utilize onboard sensors, offboard sensing, network, and predictive temporal data for noise signature mitigation. By building a composite understanding of real data offboard the aircraft, the aircraft can make adjustments to the way it is flying and verify this against a predicted noise signature (via computational methods) to reduce environmental impact. This might be realized via a change in translative speed, propeller speed, or choices in propulsor usage (e.g., a quiet propulsor vs. a high thrust, noisier propulsor). These noise mitigation actions may also be decided at the network level rather than the vehicle level to balance concerns across a city and relieve computing constraints on the aircraft.

A method may include detecting, during a flight of an aircraft system, a conflict with a planned route of the aircraft system, determining one or more alternate routes for the aircraft system to avoid the conflict, wherein each of the one or more alternate routes avoid secondary conflicts with active flight operations, transmitting first data to cause first visual information indicating the conflict and second visual information indicating the one or more alternate routes to be displayed to a user, receiving second data indicating one of the one or more alternate routes being selected by the user, and updating the planned route of the aircraft system to include the alternate route selected by the user.