AI-based laundry course recommending apparatus and method of controlling the same

Patent metadata

Field	Value
Publication number	US-11525202-B2
Application number	US-201916603815-A
Country	US
Kind code	B2
Filing date	Jun 28, 2019
Priority date	Jun 28, 2019
Publication date	Dec 13, 2022
Grant date	Dec 13, 2022

Abstract

Disclosed is an artificial intelligence (AI)-based self-control air conditioner. The AI-based self-control air conditioner includes a communication unit configured to receive an image including member data for identifying the member from an image acquisition apparatus corresponding to a group including at least one member, and a processor configured to recognize the member data from the received image, to acquire operation data including an operation condition of an air conditioner, which is desired by the member, based on the recognized data, to store member information including the member data and the operation data in a database, and to acquire and analyze the operation condition of the air conditioner, which is desired by the member, with respect to at least one member from a plurality of pieces of member information corresponding to the group stored in the database, wherein the air conditioner is autonomously driven according to control of the processor. Accordingly, the air conditioner learns members itself and controls an operation in an optimum state to reduce power consumption and is driven according to an operation condition set for each member to enhance personal convenience of the member.

First claim

What is claimed is:

1. An artificial intelligence (AI)-based laundry course recommendation apparatus comprising:
a detector configured to classify at least one laundry item inside a washing machine into a plurality of regions and to photograph the plurality of regions at a plurality of angles, respectively, to acquire at least one image related to a type and a material of the at least one laundry item;
a database configured to store laundry data and laundry course corresponding to the laundry data, wherein the laundry course is input by a user; and
a processor configured to:
acquire the at least one image from the detector,
classify a plurality of pieces of laundry information on the type and material of the at least one laundry item from the at least one image,
store the laundry information in the database,
compare the laundry information with the laundry data to determine a similarity in material between the laundry information and the laundry data,
when the laundry information matches with the laundry data based on the similarity in material, extract the laundry course corresponding to the matched laundry data, and
when the laundry information does not match the laundry data based on the similarity in material, infer, using a convolutional neural network (CNN) the laundry information of the at least one laundry item distributed on the plurality of regions and extract a pre-learned laundry course corresponding to the inferred laundry information.

2. The AI-based laundry course recommendation apparatus of claim 1 , wherein the detector further includes:
a camera configured to photograph the plurality of regions of the at least one laundry item at a plurality of angles, respectively; and
a light configured to provide a light source to acquire the image during photograph of the camera.

3. The AI-based laundry course recommendation apparatus of claim 2 , wherein the light is installed on an upper portion of the washing machine to maintain predetermined illumination in the laundry distributed on the plurality of regions, and is operated while the detector acquires the image.

4. The AI-based laundry course recommendation apparatus of claim 1 , wherein the processor is further configured to: extract at least one laundry course to be applied to the laundry information, apply a score to suitability of the laundry information and the at least one laundry course, and extract a laundry course with a highest score.

5. The AI-based laundry course recommendation apparatus of claim 4 , wherein the processor is further configured to: exclude a laundry course set by the user to not to be applied to the laundry when the processor extracts the laundry course with the highest score.

6. The AI-based laundry course recommendation apparatus of claim 5 , wherein the processor is further configured to: output a notification when all laundry courses are excluded.

7. The AI-based laundry course recommendation apparatus of claim 1 , further comprising a memory configured to store a laundry data recognition model that is trained using a machine learning or deep learning algorithm and is used to recognize the laundry information from the at least one image.

8. The AI-based laundry course recommendation apparatus of claim 1 , wherein the processor further includes a controller configured to control the washing machine according to any one of a laundry course that is manually input by the user or a laundry course that is automatically extracted.

9. A control method of an artificial intelligence (AI)-based laundry course recommendation apparatus, the method comprising:
a first operation of classifying at least one laundry item inside a washing machine into a plurality of regions and photographing the plurality of regions at a plurality of angles, respectively, to acquire at least one image related to a type and a material of the at least one laundry item;
a second operation of acquiring laundry information on the type and material of the laundry from the image and storing the laundry information in a database; and
a third operation of comparing a plurality of pieces of laundry information corresponding to the plurality of regions, which is stored in the database, with laundry data and laundry course pre-input by a user, and extracting a laundry course of the at least one laundry item, wherein the third operation further comprises:
classifying the laundry information distributed on the plurality of regions;
comparing the laundry information with the laundry data to determine a similarity in material between the laundry information and the laundry data; and
when the laundry information matches with the laundry data based on the similarity in material, extracting the laundry course corresponding to the matched laundry data, and
when the laundry information does not match the laundry data based on the similarity in material, inferring, using a convolutional neural network (CNN) the laundry information of the at least one laundry item distributed on the plurality of regions and extract a pre-learned laundry course corresponding to the inferred laundry information.

10. The method of claim 9 , wherein the first operation includes receiving at least one still image or video image indicating the type and material of the laundry from the user or a mobile device of the user.

11. The method of claim 9 , wherein the second operation includes:
classifying the laundry into the plurality of regions;
generating laundry information by matching with a type and a material corresponding to the plurality of regions; and
storing a result in the database by matching the laundry and the laundry information corresponding to the plurality of regions.

12. The method of claim 9 , wherein the third operation includes:
extracting at least one laundry course to be applied to the laundry information;
applying a score to suitability of the laundry information and the at least one laundry course; and
extracting a laundry course with a highest score.

13. The method of claim 12 , further comprising: excluding a laundry course set by the user to not to be applied to the laundry.

14. The method of claim 13 , further comprising outputting a notification to the user when all laundry courses are excluded.

15. The method of claim 9 , further comprising controlling the washing machine according to any one of a laundry course that is manually input by the user or a laundry course that is automatically extracted.

Assignees

• Lg Electronics Inc

Inventors

• Lee Jooseong
• Song Taeyup
• Han dayun

Classifications

• D06F34/18 Primary

  Condition of the laundry, e.g. nature or weight · CPC title

• D06F33/32 Primary

  Control of operational steps, e.g. optimisation or improvement of operational steps depending on the condition of the laundry · CPC title

• G06V20/52

  Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69) · CPC title

• G06V10/82

  using neural networks · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title