Aerial ride quality improvement system using feedback
Systems and methods for improving aerial ride quality based on user feedback accessed from an aerial vehicle and devices associated with passengers are provided. A network system receives, from one or more devices associated with a passenger on an aerial vehicle, feedback data regarding a flight, whereby the feedback data is associated with an issue experienced by the passenger. The network system then identifies a root cause of the issue experienced by the passenger on the aerial vehicle. The identifying may include correlating the feedback data with other data associated with the flight. A mitigation action to mitigate the issue is determined. The network system may determine whether to trigger the mitigation action based on a corresponding threshold and can trigger the mitigation action to occur accordingly.
1. A method comprising:
accessing, by a network system from one or more devices associated with a passenger on an aircraft, user feedback data regarding a flight, the user feedback data being associated with an issue experienced by the passenger while on the flight;
computing, by the network system, a root cause of the issue experienced by the passenger on the aircraft, the computing including correlating the user feedback data with other data associated with the flight;
computing, by the network system, a plurality of mitigation actions to mitigate the issue;
computing, by the network system, a ranking of the plurality of mitigation actions based on an impact of each of the mitigation actions, wherein:
the impact is associated with (i) a noise level of the flight or (ii) an amount of power usage associated with each of the mitigation actions; and
the ranking filters the plurality of mitigation actions based on the impact of each of the mitigation actions; and
triggering, by the network system, at least one mitigation action of the plurality of mitigation actions to occur based on the ranking of the plurality of mitigation actions.
2. The method of claim 1 , wherein accessing the user feedback data occurs while the passenger is inflight.
3. The method of claim 1 , wherein accessing the user feedback data comprises receiving sensor measurements from the one or more devices associated with the passenger, the sensor measurements indicating a weight distribution and any pressure caused by passenger movement.
4. The method of claim 1 , wherein accessing the user feedback data comprises receiving a sensor input from the one or more devices associated with the passenger, the sensor input indicating touch by the passenger.
5. The method of claim 1 , wherein accessing the user feedback data comprises monitoring for an utterance from the passenger that indicates the issue, the utterance being analyzed by a natural language processor to identify the issue.
6. The method of claim 1 , further comprising determining whether to trigger the at least one mitigation action based on a corresponding threshold.
7. The method of claim 1 , wherein triggering the at least one mitigation action to occur comprises rerouting the aircraft, causing a change in a speed of the aircraft, maneuvering the aircraft differently, or causing a change in an altitude of the aircraft.
8. The method of claim 1 , wherein triggering the at least one mitigation action to occur comprises rerouting future aircrafts operating on a same route as the aircraft or changing an aircraft type for future aircraft operating on the same route as the aircraft to avoid the issue.
9. The method of claim 1 , wherein computing the root cause comprises:
detecting a timestamp associated with the user feedback data; and
identifying a portion of a route where the issue occurred by correlating the timestamp with route data.
10. The method of claim 1 , wherein correlating the user feedback data with other data associated with the flight comprises correlating the user feedback data with one or more of vehicle flight data, route data, third-party data, and known data, the known data comprising known conditions corresponding to root causes of issues.
11. The method of claim 10 , further comprising using machine-learning to construct the known data.
12. The method of claim 1 , wherein computing the root cause comprises using a natural language processor to identify an utterance corresponding to the issue.
13. A system comprising:
one or more hardware processors; and
a memory storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
accessing, from one or more devices associated with a passenger on an aircraft, user feedback data regarding a flight, the user feedback data being associated with an issue experienced by the passenger;
computing a root cause of the issue experienced by the passenger on the aircraft, the computing including correlating the user feedback data with other data associated with the flight;
computing a plurality of mitigation actions to mitigate the issue;
computing a ranking of the plurality of mitigation actions based on an impact of each of the mitigation actions, wherein:
the impact is associated with (i) a noise level of the flight or (ii) an amount of power usage associated with each of the mitigation actions; and
the ranking filters the plurality of mitigation actions based on the impact of each of the mitigation actions; and
triggering at least one mitigation action of the plurality of mitigation actions to occur based on the ranking of the plurality of mitigation actions.
14. The system of claim 13 , wherein accessing the user feedback data comprises receiving sensor measurements from the one or more devices associated with the passenger, the sensor measurements indicating a weight distribution and any pressure caused by passenger movement.
15. The system of claim 13 , wherein accessing the user feedback data comprises receiving a sensor input from the one or more devices associated with the passenger, the sensor input indicating touch by the passenger.
16. The system of claim 13 , wherein accessing the user feedback data comprises monitoring for an utterance from the passenger that indicates the issue, the utterance being analyzed by a natural language processor to identify the issue.
17. The system of claim 13 , wherein computing the root cause comprises:
detecting a timestamp associated with the user feedback data; and
identifying a portion of a route where the issue occurred by correlating the timestamp data with route data.
18. The system of claim 13 , wherein correlating the user feedback data with other data associated with the flight comprises correlating the user feedback data with one or more of vehicle flight data, route data, third-party data, and known data, the known data comprising known conditions corresponding to root causes of issues.
19. The system of claim 18 , further comprising using machine-learning to construct the known data.
20. A machine-storage medium storing instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:
accessing from one or more devices associated with a passenger on an aircraft, user feedback data regarding a flight, the user feedback data being associated with an issue experienced by the passenger;
computing a root cause of the issue experienced by the passenger on the aircraft, the computing including correlating the user feedback data with other data associated with the flight;
computing a plurality of mitigation actions to mitigate the issue;
computing a ranking of the plurality of mitigation actions based on an impact of each of the mitigation actions, wherein:
the impact is associated with (i) a noise level of the flight or (ii) an amount of power usage associated with each of the mitigation actions; and
the ranking filters the plurality of mitigation actions based on the impact of each of the mitigation actions; and
triggering at least one mitigation action of the plurality of mitigation actions to occur based on the ranking of the plurality of mitigation actions.
21. The method of claim 1 , wherein the at least one mitigation action comprises changing a skylane in which the aircraft is traveling.