IP Library › Granted Patent US 12,495,881
Granted Patent B2
US 12,495,881 · App. 17/727,625 · Granted Dec 16, 2025

Inadvertent operations in touchless lavatory

Inventors: Bruno Abreu Calfa (Vernon, CT); Brett Israelsen (Glastonbury, CT); Matthew R. Pearson (Hartford, CT); Amit Surana (Newington, CT); Kunal Srivastava (Newington, CT)
Assignee: B/E AEROSPACE, INC.
A45D44/02
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Quick Facts
Patent No.
US 12,495,881
App. No.
17/727,625
Granted
Dec 16, 2025
Kind
B2
Abstract

A method for controlling a touchless lavatory is disclosed herein. The method includes collecting, by a processor, sensor data from a sensor, the sensor data including an ambient light measurement and an indication of motion, aggregating, by the processor, the collected sensor data for a time window, extracting, by the processor, features from the aggregated sensor data, and determining, by the processor, a probability of an activity occurring based on the extracted features. The method further includes activating, by the processor, a motor based on the determining that the activity has a high probability of occurring.

Claims (46)

1 . A method of controlling a touchless lavatory, comprising:

collecting, by a processor, sensor data from a set of sensors, the sensor data including an ambient light measurement, proximity information, and an indication of motion;

aggregating, by the processor, the collected sensor data for a time window;

extracting, by the processor, features for the time window from the aggregated sensor data;

determining, by the processor, a probability of an activity of a user occurring based on the extracted features; and

activating, by the processor, a motor based on the determining that the probability exceeds a threshold, the motor being configured to control a component of the touchless lavatory,

wherein the determining the probability of the activity of the user occurring includes using at least one pretrained classification model to determine the probability of the activity, and

wherein the at least one pretrained classification model includes a first pretrained classification model to determine an occupancy status based on the aggregated sensor data and the extracted features, a second pretrained classification model to determine a sitting status based on the aggregated sensor data and the extracted features, and a third pretrained classification model to determine a gesture status based on the aggregated sensor data and the extracted features.

2 . The method of claim 1 , wherein the sensor data is collected at discrete time intervals of about 0.05 seconds to about 0.5 seconds.

3 . The method of claim 1 , wherein the time window is about 0.5 seconds to about 2 seconds.

4 . The method of claim 1 , wherein the second pretrained classification model further determines an orientation status based on the aggregated sensor data and the extracted features.

5 . The method of claim 1 , wherein the time window begins when a previous window ends.

6 . A touchless lavatory sensor control system, comprising:

a set of sensors configured to transmit sensor data;

a motor coupled to the set of sensors and configured to control a component of the touchless lavatory; and

a controller operatively coupled with the set of sensors and the motor, wherein the controller is configured to:

collect sensor data, the sensor data including an ambient light measurement, proximity information, and an indication of motion;

aggregate the collected sensor data for a time window;

extract features for the time window from the aggregated sensor data;

determine a probability of an activity of a user occurring based on the extracted features; and

and transmit instructions to activate the motor based on the probability exceeding a threshold,

wherein the determining the probability of the activity of the user occurring includes using at least one pretrained classification model to determine the probability of the activity, and

wherein the at least one pretrained classification model includes a first pretrained classification model to determine an occupancy status based on the aggregated sensor data and the extracted features, a second pretrained classification model to determine a sitting status based on the aggregated sensor data and the extracted features, and a third pretrained classification model to determine a gesture status based on the aggregated sensor data and the extracted features.

7 . The touchless lavatory sensor control system of claim 6 , wherein each sensor is configured to transmit the sensor data at discrete time intervals of about 0.05 seconds to about 0.5 seconds.

8 . The touchless lavatory sensor control system of claim 6 , wherein the time window is of about 0.5 seconds to about 2 seconds.

9 . The touchless lavatory sensor control system of claim 6 , wherein the time window overlaps with a previous time window.

10 . The touchless lavatory sensor control system of claim 6 , wherein the time window begins at the end of a previous time window.

11 . A method of controlling a touchless lavatory, comprising:

receiving, by a processor, a triggering event;

collecting, by a processor, sensor data from a set of sensors, the sensor data including an ambient light measurement, proximity information, and an indication of motion;

aggregating, by the processor, the collected sensor data for a time window;

extracting, by the processor, features for the time window from the aggregated sensor data;

determining, by the processor, whether a space is occupied, wherein determining whether the space is occupied comprises:

determining, by the processor, a probability of the space is occupied based on the extracted features; and

activating, by the processor, an overhead light based on the determining that the probability of the space being occupied exceeds a first threshold; and

determining, by the processor, a state of a user within the space, wherein determining the state of the user comprises:

determining, by the processor, a probability of an activity of the user occurring based on the extracted features; and

responsive to determining that the probability of the activity exceeds a second threshold, sending, by the processor, a command to a motor configured to control a component of the touchless lavatory in response to the state of the user.

12 . The method of claim 11 , wherein the state of the user includes one of sitting and standing.

13 . The method of claim 11 , further comprising:

responsive to determining that the probability of the activity exceeds the second threshold, determining, by the processor, a first activity of the user within the space; and

sending, by the processor, a first command to the motor to control the component of the touchless lavatory in response to the determined first activity.

14 . The method of claim 13 , wherein the first activity of the user includes a movement of user of at least one of a hand, an arm, a foot, and a leg.

15 . The method of claim 13 , further comprising:

responsive to determining that the probability of the activity exceeds the second threshold, determining, by the processor, a second activity of the user within the space; and

sending, by the processor, a second command different from the first command to the motor to control the component of the touchless lavatory in response to the determined second activity.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 6, 2022
From: RAYTHEON TECHNOLOGIES CORPORATION
To: B/E AEROSPACE, INC.
Reel/Frame 060113/0523 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 22, 2022
From: ABREU CALFA, BRUNO; ISRAELSEN, BRETT; PEARSON, MATTHEW R.; SURANA, AMIT; SRIVASTAVA, KUNAL
To: RAYTHEON TECHNOLOGIES CORPORATION
Reel/Frame 059686/0735 →
Continuity (1)
Related Publication 20230337808A1 · Oct 26, 2023
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