Washing machine providing fitted default washing options for user using learning method based on artificial intelligence and a system including the same

Patent metadata

Field	Value
Publication number	US-11739464-B2
Application number	US-202016773867-A
Country	US
Kind code	B2
Filing date	Jan 27, 2020
Priority date	Nov 22, 2019
Publication date	Aug 29, 2023
Grant date	Aug 29, 2023

Abstract

An artificial intelligence apparatus determines whether a washing option in a washing course according to the input of a user is changed when input of the user is received, and collect use history information when the washing option is changed. In addition, the artificial intelligence apparatus inputs the collected use history information to an option resetting model to acquire a second washing option for resetting the washing course, and resets the washing option included in the washing course according to the second washing option.

First claim

What is claimed is:

1. A washing machine for setting default washing options of a washing course among a plurality of washing courses using a training method based on artificial intelligence (AI), the washing machine comprising:
an input interface configured to receive an input from a user; and
a processor configured to:
store the plurality of washing courses and default washing options corresponding to each of the plurality of washing courses, wherein the default washing options comprise at least one of a water temperature, a number of rinse cycles, a spin strength, a dry spin strength, or a number of dehydration cycles,
determine whether the user changed at least one default washing option of the washing course or whether the user selected the default washing options of the washing course according to the input;
acquire a use history of the washing course including the changed at least one default washing option or the selected default washing options;
acquire a result from an AI model using AI, wherein the AI model uses weights given to the changed at least one default washing option or the selected default washing options for each acquired use history among a plurality of acquired use histories for a predetermined period from a most recent acquired use history as an input, wherein a higher weight is given to the changed at least one default washing option or the selected default washing options based on how recently the acquired use history was acquired;
determine washing options to be reset as default washing options corresponding to the washing course based on the result of the AI model; and
reset the default washing options to the reset default washing options of the washing course to the determined washing options.

2. The washing machine of claim 1 , wherein the processor is further configured to:
cause an output interface to output a resetting notification related to whether the resetting of the default washing options is allowed, and
reset the default washing options when an input allowing the resetting of the default washing option is received from the user.

3. The washing machine of claim 1 ,
wherein the AI model is configured to: assign the weights given to the changed at least one default washing option or the selected default washing options for each acquired use history, and wherein the result corresponds to a maximum sum of the assigned weights.

4. The washing machine of claim 1 , wherein the acquired use history is classified in chronological order.

5. A system including a washing machine for setting default washing options of a washing course among a plurality of washing courses using a training method based on artificial intelligence, the system comprising:
a first washing machine comprising:
a wireless interface;
an input interface configured to receive input from a user; and
a first processor configured to:
store the plurality of washing courses and default washing options corresponding to each of the plurality of washing courses, wherein the default washing options comprise at least one of a water temperature, a number of rinse cycles, a spin strength, a dry spin strength, or a number of dehydration cycles,
determine whether the user changed at least one default washing option of the washing course or whether the user selected the default washing options corresponding to of the washing course according to the input,
acquire a use history of the washing course including the changed at least one default washing option or the selected default washing options,
acquire a result from an artificial intelligence (AI) model using AI, wherein the AI model uses weights given to the changed at least one default washing option or the selected default washing options for each acquired use history among a plurality of acquired use histories for a predetermined period from a most recent acquired use history as an input, wherein a higher weight is given to the changed at least one default washing option or the selected default washing options based on how recently the acquired use history was acquired,
determine washing options to be reset as default washing options corresponding to the washing course based on the result of the AI model; and
reset the default washing options of the washing course to the determined washing options; and

a server configured to:
communicate with the wireless interface of the first washing machine,
receive the reset default washing options and the washing course corresponding to the reset default washing options from the first processor of the first washing machine,
store the reset default washing options and the washing course; and

a second washing machine comprising a second processor, wherein the second processor is configured to:
acquire the washing course with the reset default washing options from the server;
determine a second washing course corresponding to the received washing course; and
reset second default washing options of the second washing course to the reset default washing options.

6. The system of claim 5 , wherein the server is configured to compensate for a difference related to washing options between the washing course of the first washing machine and the second washing course of the second washing machine corresponding to the washing course of the first washing machine based on a difference in specification between the first washing machine and the second washing machine.

7. The system of claim 5 , wherein the server is configured to store a mapping table in which matching information of the washing course of the first washing machine and the second washing course of the second washing machine corresponding to the washing course of the first washing machine is used.

8. The system of claim 5 , wherein the second processor is further configured to compensate for a difference related to washing options between the washing course of the first washing machine and the second washing course of the second washing machine corresponding to the washing course of the first washing machine, wherein the second processor is configured to compensate for the difference using specification information of the first washing machine and the second washing machine stored in a memory or a mapping table including specification matching information stored in the memory.

Assignees

• Lg Electronics Inc

Inventors

• Kim Sangwon
• Lee Jaehoon

Classifications

• D06F34/32 Primary

  characterised by graphical features, e.g. touchscreens · CPC title

• D06F33/30

  Control of washing machines characterised by the purpose or target of the control  (controlling processes of washer-dryers D06F33/50) · CPC title

• D06F34/08

  Control circuits or arrangements thereof · CPC title

• G05B13/00

  Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion (G05B19/00 takes precedence) · CPC title

• G05B13/0265

  the criterion being a learning criterion · CPC title