Methods, devices, and systems for recording a flight segment
View Patent ↗Disclosed herein are methods, devices, and systems for facilitating pilots in determining current and predicted performance specifications of their aircraft. According to one embodiment, a method is implemented on a mobile computing device. The method includes receiving static pilot data, receiving static aircraft data associated with an aircraft, receiving dynamic aircraft data over a time period, determining aircraft performance data based on the static aircraft data and the dynamic aircraft data, providing the aircraft performance data to a graphical user interface (GUI) associated with the mobile computing device, and storing the static pilot data and the aircraft performance data.
1 . A method implemented on a mobile computing device, the method comprising:
receiving dynamic aircraft data associated with an aircraft over a time period;
determining aircraft performance data associated with the aircraft based on the dynamic aircraft data, and static aircraft data associated with the aircraft, wherein:
the aircraft performance data comprises turbulence data;
the turbulence data comprises quantitative turbulence data, qualitative turbulence data, and turbulence location data;
providing the turbulence data to a remote server over a wide area network (WAN), wherein the remote server is configured for:
receiving a plurality of turbulence datasets from a plurality of aircraft; and
generating turbulence mapping data in near-real-time associated with the plurality of turbulence datasets;
receiving the turbulence mapping data;
and
providing the turbulence mapping data and at least a portion of the aircraft performance data associated with the aircraft to a graphical user interface (GUI) associated with the mobile computing device.
2 . The method of claim 1 further comprising receiving static pilot data via the GUI and determining the aircraft performance data is further based on the static pilot data.
3 . The method of claim 1 further comprising receiving the static aircraft data via the GUI.
4 . The method of claim 1 , wherein the mobile computing device is at least one of a smart phone and a smart tablet.
5 . The method of claim 1 , wherein the aircraft performance data comprises at least one of rate of climb data and rate of descent over the time period.
6 . The method of claim 1 , wherein:
determining the aircraft performance data is further based on airport data; and
the airport data is provided based on a current location of the mobile computing device.
7 . The method of claim 1 , wherein:
determining the aircraft performance data is further based on weather data; and
the weather data is provided by a weather server over a wide area network (WAN).
8 . The method of claim 1 , wherein the aircraft performance data comprises pitch data, yaw data, and roll data over the time period.
9 . The method of claim 1 wherein the aircraft performance data comprises velocity data and altitude data over the time period.
10 . The method of claim 1 , wherein:
a first portion of the dynamic aircraft data is provided by a plurality of mobile device sensors embedded in the mobile computing device; and
a second portion of the dynamic aircraft data provided by at least one of a personal area network (PAN) connection and a local area network connection (LAN).
11 . The method of claim 10 , wherein the second portion of the dynamic aircraft data is further provided by at least one of an aircraft aviation system embedded within the aircraft and a mobile high performance sensor device.
12 . The method of claim 1 , wherein:
the mobile computing device is configured for installation within a cockpit of the aircraft; and
the method further includes receiving at least a portion of the dynamic aircraft data over an internal communication bus within the aircraft.
13 . The method of claim 1 , wherein the aircraft performance data is determined by a remote server.
14 . The method of claim 1 , wherein the aircraft performance data is determined by the mobile computing device.
15 . The method of claim 10 , wherein the plurality of mobile device sensors comprises at least three of a global positioning system (GPS) receiver, an accelerometer, an electronic compass, a barometer, a microphone, and an orientation detector.
16 . The method of claim 7 , wherein the weather data is provided by at least one of a National Weather Service application programming interface (API), an Open WeatherMap API, a Weatherbit API, an AccuWeather API, a Dark Sky API, a Weather2020 API, a ClimaCell API, a Visual Crossing API, and a Aeris Weather API.
17 . The method of claim 1 , wherein the static aircraft data is provided by another remote server over the WAN.
18 . The method of claim 1 , wherein the method is performed by an application specific program and the application specific program is at least one of an iOS® app and an Android® OS app.
19 . A mobile computing device comprising
a memory; and
a processor electrically coupled with the memory, processor configured for:
receiving dynamic aircraft data associated with an aircraft over a time period;
determining aircraft performance data associated with the aircraft based on the dynamic aircraft data, and static aircraft data associated with the aircraft, wherein:
the aircraft performance data comprises turbulence data;
the turbulence data comprises quantitative turbulence data, qualitative turbulence data, and turbulence location data;
providing the turbulence data to a remote server over a wide area network (WAN), wherein the remote server is configured for:
receiving a plurality of turbulence datasets from a plurality of aircraft; and
generating turbulence mapping data in near-real-time associated with the plurality of turbulence datasets;
receiving the turbulence mapping data;
and providing the turbulence mapping data and at least a portion of the aircraft performance data associated with the aircraft to a graphical user interface (GUI) associated with the mobile computing device.
20 . A non-transitory computer readable medium comprising a plurality of machine-readable instructions which when executed by one or more processors of a mobile computing device are adapted to cause the mobile computing device to perform a method, the method comprising:
receiving dynamic aircraft data associated with an aircraft over a time period;
determining aircraft performance data associated with the aircraft based on the dynamic aircraft data, and static aircraft data associated with the aircraft, wherein:
the aircraft performance data comprises turbulence data;
the turbulence data comprises quantitative turbulence data, qualitative turbulence data, and turbulence location data;
providing the turbulence data to a remote server over a wide area network (WAN), wherein the remote server is configured for:
receiving a plurality of turbulence datasets from a plurality of aircraft; and
generating turbulence mapping data in near-real-time associated with the plurality of turbulence datasets;
receiving the turbulence mapping data;
and
providing the turbulence mapping data and at least a portion of the aircraft performance data associated with the aircraft to a graphical user interface (GUI) associated with the mobile computing device.