Electronic device and operation method of collecting data from multiple devices for generating an artificial intelligence model

Patent metadata

Field	Value
Publication number	US-12393871-B2
Application number	US-202117604202-A
Country	US
Kind code	B2
Filing date	Sep 15, 2021
Priority date	Sep 18, 2020
Publication date	Aug 19, 2025
Grant date	Aug 19, 2025

Abstract

An electronic device includes a communication interface, a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory. The processor is configured to execute the one or more instructions to obtain first data and characteristic information of the first data, control the communication interface to transmit a data request to an external device and receive characteristic information of second data from the external device, control the communication interface to receive the second data from the external device, based on the characteristic information of the first data and the characteristic information of the second data, determine training data including at least a portion of the first data and at least a portion of the second data, and generate the AI model, based on the determined training data.

First claim

The invention claimed is:

1. An electronic device for collecting training data for generating an artificial intelligence (AI) model, the electronic device comprising:
a sensor;
a communication interface;
memory storing one or more instructions; and
a processor configured to execute the one or more instructions stored in the memory,
wherein the processor is configured to execute the one or more instructions to:
obtain first data by sensing data about a user of the electronic device using the sensor,
obtain a first distribution information of the first data,
control the communication interface to transmit a data request to an external device and receive a second distribution information of second data from the external device,
determine whether to receive the second data from the external device, based on a collection amount of the first data, the first distribution information and the second distribution information,
control the communication interface to receive the second data from the external device, based on the collection amount of the first data being less than a preset value and a difference between the first distribution information and the second distribution information less than a first threshold value, or based on the collection amount of the first data being greater than or equal to the preset value and the difference between the first distribution information and the second distribution information is greater than a second threshold value,
determine training data including at least a portion of the first data and at least a portion of the second data, and
generate the AI model, based on the determined training data,
wherein the first distribution information of the first data includes at least one of an average, a standard deviation, a variance, a maximum value, a minimum value, or a distribution curve of the first data, and
wherein the second distribution information of the second data includes at least one of an average, a standard deviation, a variance, a maximum value, a minimum value, or a distribution curve of the second data.

2. The electronic device of claim 1 , wherein the processor is further configured to execute the one or more instructions to determine the training data so that a preset balance of characteristic information for the training data is maintained.

3. The electronic device of claim 1 ,
wherein the processor is further configured to:
execute the one or more instructions to obtain a first demographic information of the user of the electronic device, based on the data of the user of the electronic device,
control the communication interface to receive a second demographic information of a user of the external device, and
determine whether to receive the second data from the external device, based on the collection amount of the first data, the first demographic information and the second demographic information.

4. The electronic device of claim 3 ,
wherein the sensor is further configured to obtain at least one of touch information, voice information, location information, or step distance information of the user of the electronic device, and
wherein the processor is further configured to execute the one or more instructions to obtain the first demographic information of the user of the electronic device, based on at least one of the touch information, voice information, location information, step distance information of the user of the electronic device, or keyboard type information used by the user of the electronic device.

5. The electronic device of claim 3 , wherein the processor is further configured to execute the one or more instructions to determine the training data so that at least one of a preset balance of characteristic information for the training data or a preset balance of demographic information for the training data is maintained.

6. The electronic device of claim 1 , wherein the processor is further configured to:
execute the one or more instructions to search for the external device located around the electronic device, and
control the communication interface to transmit the data request to the external device, in response to a found external device satisfying a preset condition.

7. The electronic device of claim 1 , wherein the processor is further configured to:
execute the one or more instructions to control the communication interface to transmit information of a number of necessary data samples to the external device, and
receive the second data sampled based on the information of the number of necessary data samples.

8. An operation method of an electronic device for collecting training data for generating an artificial intelligence (AI) model, the operation method comprising:
obtaining first data by sensing data about a user of the electronic device using a sensor;
obtaining a first distribution information of the first data;
transmitting a data request to an external device;
receiving a second distribution information of second data from the external device;
determining whether to receive the second data from the external device, based on a collection amount of the first data, the first distribution information and the second distribution information;
receiving the second data from the external device, based on the collection amount of the first data being less than a preset value and a difference between the first distribution information and the second distribution information less than a first threshold value, or based on the collection amount of the first data being greater than or equal to the preset value and the difference between the first distribution information and the second distribution information is greater than a second threshold value;
determining training data including at least a portion of the first data and at least a portion of the second data; and
generating the AI model, based on the determined training data,
wherein the first distribution information of the first data includes at least one of an average, a standard deviation, a variance, a maximum value, a minimum value, or a distribution curve of the first data, and
wherein the second distribution information of the second data includes at least one of an average, a standard deviation, a variance, a maximum value, a minimum value, or a distribution curve of the second data.

9. A non-transitory computer-readable recording medium storing a computer program, which, when executed by a computer, performs the method of claim 8 .

Assignees

• Samsung Electronics Co Ltd

Inventors

• Huh Junho
• Lee Hosun
• Lee Choonghoon

Classifications

• G06N3/09

  Supervised learning · CPC title

• G06F18/2193 Primary

  based on specific statistical tests · CPC title

• G06F18/214

  Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• G06N20/00 Primary

  Machine learning · CPC title

• G06N3/08

  Learning methods · CPC title