IP Library › Granted Patent US 12,243,538
Granted Patent B2
US 12,243,538 · App. 17/446,701 · Granted Mar 4, 2025

Interactive aircraft cabin environment

Inventors: Brian Cook (Savannah, GA); Tongan Wang (Savannah, GA)
Assignee: GULFSTREAM AEROSPACE CORPORATION
G10L17/22B64D11/0015G10L17/18B64D2011/0038B64D2011/0053
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Quick Facts
Patent No.
US 12,243,538
App. No.
17/446,701
Granted
Mar 4, 2025
Kind
B2
Abstract

The interactive aircraft cabin environment control system employs at least one microphone array disposed within the cabin to capture spoken utterances from a passenger and is configured to provide an estimation of passenger location within the cabin based on arrival time analysis of the spoken utterances. A data source onboard the aircraft provides flight context information. Such data sources include sensors measuring real-time parameters on the aircraft, the current flight plan of the aircraft, singly and in combination. A control processor, coupled to the microphone array, is configured to ascertain passenger identity based on the spoken utterances. The control processor is programmed and configured to learn and associate passenger preference to passenger identity. The control processor is receptive of the estimation of passenger location and is coupled to provide supervisory control over at least one device forming a part of the cabin environment according to passenger location, passenger preference obtained from passenger identity and flight context information.

Claims (32)

1. An interactive aircraft cabin environment control system comprising:

at least one microphone array disposed within the cabin to capture spoken utterances from a passenger;

data storage onboard the aircraft to store cabin environment preferences that indicate passenger-specific settings for a controllable cabin environment;

a control processor coupled to the at least one microphone array and to the data storage, the control processor being programmed and configured to:

analyze the spoken utterances captured by the at least one microphone array to ascertain identity of the passenger;

analyze the spoken utterances captured by the at least one microphone array to determine a current onboard location of the passenger;

obtain passenger-specific cabin environment preferences for the passenger, based on the ascertained identity of the passenger, wherein the passenger-specific cabin environment preferences indicate passenger-customized settings for controllable devices and systems that form a part of the controllable cabin environment;

analyze the spoken utterances captured by the at least one microphone array to detect a command or request to control at least one device or system of the controllable cabin environment; and

selectively apply the obtained passenger-specific cabin environment preferences for the passenger, based on the determined current onboard location of the passenger, wherein the selectively applied passenger-specific cabin environment preferences indicate passenger-customized settings for a controllable device or system positioned at or near the determined onboard location of the passenger, wherein the control processor provides supervisory control over the controllable device or system positioned at or near the determined onboard location of the passenger.

2. The control system of claim 1 , further comprising a data source onboard the aircraft providing flight context information, wherein:

the flight context information comprising real-time parameters of the aircraft and/or a current flight plan of the aircraft; and

at least some of the selectively applied passenger-specific cabin environment preferences indicate passenger-customized settings for the passenger that are based on the flight context information.

3. The control system of claim 1 , wherein the control processor includes a neural network trained to perform as least one of speaker identification and speaker verification.

4. The control system of claim 1 , wherein the control processor includes a neural network configured to learn at least some of the cabin environment preferences.

5. The control system of claim 1 , wherein the control processor includes a neural network configured to learn at least some of the cabin environment preferences based on spoken utterances in context of flight context information.

6. The control system of claim 1 , wherein the control processor is programmed to provide supervisory control using a device state data structure which stores information about a set of predetermined operating states of the controllable device or system positioned at or near the determined onboard location of the passenger.

7. The control system of claim 6 , wherein the device state data structure is a directed graph having nodes representing different operating states and edges representing permitted state transitions of the controllable device or system positioned at or near the determined onboard location of the passenger.

8. The control system of claim 1 wherein the controllable device or system positioned at or near the determined onboard location of the passenger is associated with a designated seat location within the aircraft.

9. The control system of claim 1 , wherein the control processor is configured to use plural and diverse inputs selected from the group consisting of speech recognition, aircraft state information, device state information, flight plan context and combinations thereof in combination with passenger preference to predict a desired cabin environment and formulate a control strategy for supervisory control over the cabin environment.

10. The control system of claim 1 , wherein the control processor is configured to control plural devices in concert using an overall supervisory control strategy to produce different cabin environments.

11. The control system of claim 1 , wherein the control processor is configured to control plural devices in concert using an overall supervisory control strategy to produce different cabin environments for different phases of a flight.

12. The control system of claim 1 , wherein the control processor is configured with different control interfaces to perform supervisory control over a diverse plurality of devices selected from the group consisting of window shade, window tint, gasper, entertainment system audio volume, entertainment system channel, seat incliner, reading light and cabin ambient lights.

13. The control system of claim 1 , wherein the control processor is configured to predict device settings that are not literally expressed in spoken utterances from the passenger.

14. An automated computer-based method of operating an interactive aircraft cabin environment control system comprising at least one microphone array disposed within a cabin of an aircraft, data storage onboard the aircraft to store cabin environment preferences that indicate passenger-specific settings for a controllable cabin environment of the aircraft, and a control processor coupled to the at least one microphone array and to the data storage, the control processor being programmed and configured to perform operations including:

analyzing spoken utterances of a passenger to ascertain identify of the passenger, the spoken utterances captured by the at least one microphone array;

analyzing the spoken utterances captured by the at least one microphone array to determine a current onboard location of the passenger;

obtaining passenger-specific cabin environment preferences for the passenger, based on the ascertained identity of the passenger, wherein the passenger-specific cabin environment preferences indicate passenger-customized settings for controllable devices and systems that form a part of the controllable cabin environment;

analyzing the spoken utterances captured by the at least one microphone array to detect a command or request to control at least one device or system of the controllable cabin environment; and

selectively applying the obtained passenger-specific cabin environment preferences for the passenger, based on the determined current onboard location of the passenger, wherein the selectively applied passenger-specific cabin environment preferences indicate passenger-customized settings for a controllable device or system positioned at or near the determined onboard location of the passenger, and wherein the control processor provides supervisory control over the controllable device or system positioned at or near the determined onboard location of the passenger.

15. The method of claim 14 , wherein the control processor is further configured to obtain flight context information provided by a data source onboard the aircraft, wherein:

the flight context information comprises real-time parameters of the aircraft and/or a current flight plan of the aircraft; and

at least some of the selectively applied passenger-specific cabin environment preferences indicate passenger-customized settings for the passenger that are based on the flight context information.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 3, 2021
From: COOK, BRIAN; WANG, TONGAN
To: GULFSTREAM AEROSPACE CORPORATION
Reel/Frame 058285/0178 →
Continuity (1)
Related Publication 20230073759A1 · Mar 9, 2023
References Cited (17)
US 7355161B2 · Romig · 2008 [cited by examiner]
US 20080048101A1 · Romig · 2008 [cited by examiner]
US 20090319902A1 · Kneller · 2009 [cited by examiner]
US 20180293221A1 · Finkelstein et al. · 2018 [cited by applicant]
US 20190266472A1 · Johnson · 2019 [cited by applicant]
US 20200406906A1 · Omari · 2020 [cited by examiner]
US 20230114137A1 · Wu · 2023 [cited by examiner]
US 20230285010A1 · Noonan · 2023 [cited by examiner]
US 20230310099A1 · Ye · 2023 [cited by examiner]
US 20230310103A1 · Noonan · 2023 [cited by examiner]
US 20230310104A1 · Alvarez · 2023 [cited by examiner]
EP 3578462A1 · 2019 [cited by examiner]
KR 20220076398A · 2021 [cited by examiner]
Google Machine Translation of European Patent Application No. EP 3 578 462 A1 to Ibrahim that was filed in 2018. [cited by examiner]
Tehrani, Ali, et al., Sound Source Localization Using Time Differences of Arrival; Euclidean Distance Matrices Based Approach, IEEE Xplore, 2018 9th International Symposium on Telecommunications (IST), Dec. 17, 2018 (ht… [cited by examiner]
Snyder, David, et al., Deep neural network-based speaker embeddings for end-to-end speaker verification, IEEE explore, 2016 IEEE Spoken Language Technology Workshop (SLT) (2016) (https://ieeexplore.ieee.org/abstract/doc… [cited by examiner]
Machine Translation of Korean Patent Application Pub. No. KR 20220164494 A to Cella that was filed in 3-211. [cited by examiner]