IP Library › Granted Patent US 11,539,546
Granted Patent B2
US 11,539,546 · App. 16/869,724 · Granted Dec 27, 2022

Home appliances and method for controlling home appliances

Inventor: Yun Sik Park (Seoul, KR)
Assignee: LG ELECTRONICS INC.
H04L12/282G06N3/084G06V40/20G10L15/16G10L15/18G10L15/22H04L12/2812H04L12/2827G10L2015/223G10L2015/225G10L2015/228H04L2012/285
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Quick Facts
Patent No.
US 11,539,546
App. No.
16/869,724
Filed
May 8, 2020
Granted
Dec 27, 2022
Kind
B2
Art Unit
2444
USPC
709/223
Abstract

A method of controlling a home appliance which operates in an Internet of Things environment through a 5G communication network and which is performed using a neural network model generated by machine learning, including determining whether there is a user in the vicinity of the home appliance, capturing a motion of the user using a vision sensor based on a determination that there is a user in the vicinity of the home appliance, identifying an intention of the user based on the captured motion, and activating a speech module of the home appliance based on the intention of the user.

Claims (83)

1. A method of controlling a home appliance, the home appliance including:

a camera;

a speech engine processor for natural language processing;

a speaker;

a microphone;

a memory; and

a controller including a processor,

the method comprising:

monitoring, via the camera, a predetermined area around the home appliance;

determining, via the controller, whether there is a user in the predetermined area around the home appliance based on the monitoring of the predetermined area by the camera;

capturing, via the camera, motion of the user, when the controller determines that the user is in the predetermined area around the home appliance;

identifying, via the controller, an intention of the user based on the captured motion; and

activating the speech engine processor based on the intention of the user,

wherein the identifying the intention of the user includes using a neural network model trained to determine whether the user intends to manipulate the home appliance based on the motion, captured by the camera, of the user in the predetermined area around the home appliance, and

wherein the method further comprises:

after the activating the speech engine processor of the home appliance, determining, via the controller, that the identifying of the intention of the user using the neural network model has failed based on a command not being received by the home appliance for a predetermined time, labeling an image of the captured motion as training data in which the user does not intend to use the home appliance and updating the neural network model using the labeled image of the captured motion.

2. The method of controlling the home appliance of claim 1 , further comprising:

before the determining, recognizing, via the controller, an event occurring during an operation of the home appliance; and

storing, in the memory, information about the event,

wherein the activating of the speech engine processor includes outputting, through the speaker, a voice signal of the information about the event.

3. The method of controlling the home appliance of claim 2 , wherein the event comprises an error occurring during the operation of the home appliance, and

wherein the information about the event includes information about a history of operations performed by the home appliance until a time at which the error occurred.

4. The method of controlling the home appliance of claim 3 , further comprising:

after the recognizing of the event:

determining, via the controller, an error type of the error; and

searching, via the controller; for a solution for the error type,

wherein the information about the event further includes the solution for the error type, and

wherein the voice signal output by the speaker includes the information about the history of the operations performed by the home appliance until the time at which the error occurred and the solution according to the error type.

5. The method of controlling the home appliance of claim 4 , wherein the searching, by the controller, for the solution for the error type comprises:

providing, via the controller, a query about the solution for the error type to an external server that communicates with the home appliance; and

receiving, via the controller, the solution for the error type from the external server.

6. The method of controlling the home appliance of claim 1 , further comprising before the determining, recognizing, via the controller, an event involving completion of an operation of the home appliance; and

storing, in the memory, information about the event, including a time when the completion of the operation of the home appliance occurred,

wherein the activating of the speech engine processor of the home appliance includes:

determining, via the controller, an operation to be recommended to the user based on a time elapsed from the time at which the operation of the home appliance was completed; and

outputting, via the speaker, a voice signal of the operation to be recommended.

7. The method of controlling the home appliance of claim 1 , further comprising:

before the determining:

recognizing, via the controller, an event occurring during the operation of the home appliance; and

storing, in the memory, information about the event; and

after determining that there is no user in the predetermined area around the home appliance, transmitting the information about the event to a pre-registered user terminal.

8. The method of controlling the home appliance of claim 7 , further comprising:

after the transmitting, confirming, via the controller, whether the user has read the information about the event; and

outputting, via the speaker, a voice signal of the information about the event, in response to confirming that the user has not read the information about the event.

9. The method of controlling the home appliance of claim 1 , wherein the neural network model is trained by a supervised learning method using training data in which images of a moving user are used as input data and the intention of the user is labelled in the corresponding image.

10. The method of controlling the home appliance of claim 1 , further comprising:

recognizing a home appliance control command based on speech of a user; and

generating the home appliance control command.

11. A home appliance, comprising:

a cabinet forming an exterior of the home appliance;

a door configured to open or close a passage through which an object is to be loaded into the cabinet;

a camera configured to capture an image of outside of the home appliance;

a speech engine processor;

a speaker configured to output a voice signal generated in the speech engine processor;

a controller configured to control the home appliance, the controller including a processor; and

a memory connected to the controller, wherein the memory stores instructions configured to, when executed by the controller, cause the controller to:

determine whether there is a user in a predetermined area around the home appliance,

capture, via the camera, a motion of the user when the controller determines that the user is in the predetermined area around the home appliance,

identify an intention of the user based on the captured motion, and

activate the speech engine processor in accordance with the intention of the user,

wherein the memory stores a neural network model trained to determine whether the user intends to manipulate the home appliance based on the motion of the user in the predetermined area around the home appliance,

wherein identifying the intention of the user is performed using the neural network model, and

wherein the memory further stores instructions configured to, after the activating the speech engine processor of the home appliance, determine, via the controller, that the identifying of the intention of the user using the neural network model has failed based on a command not being received by the home appliance for a predetermined time, label an image of the captured motion as training data in which the user does not intend to use the home appliance and update the neural network model using the labeled image of the captured motion.

12. The home appliance of claim 11 , wherein the memory stores instructions configured to, when executed by the controller, cause the controller to:

before the determining whether the user is in the predetermined area around the home appliance, recognize an event of the home appliance, and store information about the event in the memory, and

wherein the activating the speech engine processor of the home appliance includes outputting, via the speaker, a voice signal of the information about the event.

13. The home appliance of claim 12 , wherein the event comprises an error occurring during the operation of the home appliance, and

wherein the information about the event includes information about a history of operations performed by the home appliance until a time at which the error occurred.

14. The home appliance of claim 12 , wherein the event includes completion of an operation of the home appliance,

wherein the information about the event includes time information about a time when the completion of the operation of the home appliance occurred, and

wherein the activating the speech engine processor further includes determining, via the controller, a solution based on a time elapsed since the operation of the home appliance was completed, and generating, via the speaker, a voice signal of the solution.

15. The home appliance of claim 11 , further comprising a proximity sensor configured to detect whether the user is in the predetermined area around the home appliance,

wherein the camera is disposed on the door and faces a front direction of the home appliance, and

wherein the memory stores instructions configured to, when executed by the controller, cause the controller to:

determine that the user is in the predetermined area around the home appliance based on the detection from the proximity sensor, and

activate the camera in response to the proximity sensor sensing that the user is in the predetermined area around the home appliance.

16. The home appliance of claim 13 , wherein the memory further stores instructions configured to, when executed by the controller, cause the controller to, after the operation of recognizing an event, determine an error type and search for a solution for the error type,

wherein the information about the event includes the solution for the error type, and

wherein the activating the speech engine processor further includes outputting, via the speaker, a voice signal of the information about a history of the operations performed by the home appliance until the time at which the error occurred and the solution for the error type.

17. The home appliance of claim 16 , further comprising a communication interface configured to communicate with an external server, and

wherein the searching for a solution for the error type includes:

providing a query about a solution for the error type to the external server through the communication interface, and

receiving the solution for the error type from the external server.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2020
From: PARK, YUN SIK
To: LG ELECTRONICS INC.
Reel/Frame 052633/0480 →
Priority Claims (1)
KR 10-2019-0145837 · Nov 14, 2019 · national
Continuity (1)
Related Publication 20210152389A1 · May 20, 2021