Lg Electronics Inc.

Korea University Research and Business Foundation

Samsung Electronics Co., Ltd.

Hanwha Techwin Co., Ltd.

Taeyup Song

Dongwoo Han

Hanseok Ko

Yeon Kyung Chae

Jae-Won Lee

Sung-Soo Kim

Younghyun Lee

Hanjun Kim

Kyungsun Lee

Dayun Han

Kwangyoun Kim

Sungyong Kim

Jaeyong Song

Jooseong Lee

Yeonkyung Chae

Bonhwa Ku

An air conditioner and a method for operating an air conditioner are provided. The air conditioner may include a case having a space formed therein and an open bottom; a panel disposed under the case and having an inlet and a plurality of outlets disposed around a circumference of the inlet; a fan disposed in the case and configured to generate an airflow from the inlet to the plurality of outlets; an airflow direction controller disposed at the plurality of outlets and configured to control an airflow direction of air flowing through the plurality of outlets in a plurality of directions; a camera disposed at one side of the panel and directed toward an indoor space; and a controller configured to control the airflow direction controller based on images corresponding to the indoor space and captured by the camera. The controller may be configured to determine an activity level of an occupant for each of a plurality of areas of the indoor space based on a plurality of images corresponding to the indoor space; determine a direction of air discharged from the plurality of outlets based on the determined activity level; and control the airflow direction controller according to the direction of the air which is determined for the plurality of outlets.

Air conditioner and method for operating an air conditioner based on user activity

Provided are an air conditioner and a control method thereof. The air conditioner may include a wind direction controller that changes the direction of air being discharged, an air volume controller that changes the amount of air being discharged, a camera that obtains an image of indoor space and provides an indoor space image, and a control unit that controls the wind direction controller and the air volume controller, wherein the control unit finds indoor space information based on the indoor space image, and controls at least one of the wind direction controller and the air volume controller based on the indoor space information.

Air conditioner and method for controlling same based on indoor space image including relative positions of walls, ceiling, and floor

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.

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

An air conditioner is controlled according to one or more zones determined by artificial intelligence. The air conditioner includes a controller for generating first space classification data for dividing a space into two or more blowing zones based on human body sensing data generated by a vision module and an image, and a communication unit for transmitting the human body sensing data to a server and receiving second space classification data from the server. The controller is configured to control operation of the air conditioner based on comparing the first space classification data to the second space classification data and dividing the space into a concentrated blowing zone and a non-concentrated blowing zone.

Method for controlling air conditioner by recognizing zone on basis of artificial intelligence, server and air conditioner

A method of operating an air conditioner, including: obtaining an image acquired by a camera; determining a distance and a direction of an occupant relative to the air conditioner, based on the image; using at least one machine-learning network to classify an air-blowable space of the air conditioner into an intensive air blowing area and a non-intensive air blowing area, based on the distance and the direction of the occupant; controlling the air conditioner to operate in an intensive operation mode with respect to the intensive air blowing area; and controlling the air conditioner to operate in a non-intensive operation mode with respect to the intensive air blowing area and the non-intensive air blowing area based on completion of the intensive operation mode. A time duration of the intensive operation mode is smaller than a time duration of the non-intensive operation mode.

Air conditioner

A method for controlling, by a controller, an electronic device is provided. The method may include: sensing, by a sensor, a first radiation signal incident on the sensor; generating, by the sensor, a first output signal based on the first radiation signal; recognizing a human body based on the first output signal; determining a position of the human body as being located in one of an indoor space or an outdoor space based on the first output signal; and generating a control signal for controlling the electronic device connected via a wired or wireless network based on the position of the human body. A learning model includes a deep neural network generated through machine learning and transmission of a control signal may be performed in an Internet of Things (IoT) environment using a 5G network.

Apparatus and method for controlling electronic device

Provided is a method of detecting a voice section, including detecting from at least one image an area where lips exist, obtaining a feature value of movement of the lips in the detected area based on a difference between pixel values of pixels included in the detected area, and detecting the voice section from the at least one image based on the feature value.

Method and device for detecting voice activity based on image information

An artificial intelligence air conditioner may include a camera to obtain an image, an area recognition module for recognizing an area in which an occupant is located in an indoor space divided into a plurality of areas from the image obtained by the camera and distinguishing a living area with respect to the plurality of areas based on a result of recognizing a location of the occupant, and an airflow controller controlling airflow based on the distinguished living area, whereby airflow optimized for each living area of the indoor space may be controlled.

Artificial intelligence air conditioner and control method thereof

A surveillance system and method are provided. The surveillance system includes an audio processing device which extracts an audio feature of an audio signal, and determines whether an abnormal event has occurred in a monitoring region, based on the audio feature; a video processing device which extracts a foreground region from a video signal, and determines whether an abnormal event has occurred in the monitoring region, based on motion information of the foreground region; and a context awareness device which calculates an audio abnormal probability and a video abnormal probability by respectively accumulating results of abnormal event occurrence/non-occurrence determinations performed on audio signals and results of abnormal event occurrence/non-occurrence determinations performed on video signals for a certain period of time, and finally determines whether an abnormal situation has occurred in the monitoring region, by using respective combined probability distribution models for a normal situation and the abnormal situation.

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Seoul, South Korea

Taeyup Song