Abstract: Disclosed herein is an intelligent robot cleaner. The intelligent robot cleaner primarily senses foreign matter sucked through a suction unit under the control of a control unit, and secondarily senses an article collected in a collection unit, if articles other than the foreign matter are sensed, thus allowing a use to recognize accurate information about the article collected in the collection unit and preventing valuables or small articles from being lost. The intelligent robot device may be associated with an artificial intelligence module, a unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, devices related to 5G services, and the like.

Abstract: An electronic device according to an embodiment includes a first biometric sensor to detect first biometric information, a second biometric sensor to detect second biometric information, a security module to normalize a first decision score for the first biometric information and a second decision score for the second biometric information, generate a decision function model for combined matching of the normalized first and second decision scores, set a threshold score corresponding to a sensitivity level in the decision function model, and perform user authentication for the first and second biometric information based on the decision function model to which the threshold score is applied, and a controller configured to control an operation of the electronic device based on a result of the user authentication performed by the security module. According to the present invention, the electronic device may perform user authentication by IOT.

Abstract: Disclosed is a control system to control a robot. The control system to control the robot according to an aspect of the present disclosure includes a transceiver and a processor. The transceiver receives information of a user within each unit zone, wherein a plurality of robots is disposed in a zone. The processor is configured to determine a density for each respective unit zone from among the plurality of zones, determine an average density for each respective group zone from among the plurality of group zones based on the determined density, determine a priority for each group zone based on the respective determined average density, and control movements of one or more robots based on the determined priority, wherein the controlling of the movements is performed by extracting a feature from the user based on machine learning and setting the priority based on the extracted feature of the user.

Abstract: A method of controlling of an autonomous vehicle according to an embodiment of the present disclosure, the method comprising the steps of: acquiring state information of a driver from a sensor mounted inside the vehicle; determining a glare state of the driver based on state information of the driver; operating a primary light source blocking when recognizing a glare state of the driver; operating, by the primary light source blocking, a light source blocking device mounted on the vehicle at the moment of recognizing the glare state of the driver, and tracking a gaze direction of the driver through a first image to acquire the gaze direction of the driver; and operating secondary light source blocking, when the acquired gaze direction of the driver is outside a predetermined range. The autonomous vehicle according to the present disclosure may be associated with an artificial intelligence module, a drone (UAV), a robot, an AR device, a VR device, a device related to 5G service, etc.

Abstract: Provided are an intelligent device and a method of correcting an image thereof. The intelligent device includes a camera received in a body; a processor for controlling to obtain subject state information from an image transmitted from the camera; and a memory for storing the subject status information, wherein the processor is configured to determine a distortion state of a size of a subject based on the obtained subject state information, to measure a distance between the camera and the subject when the distortion state of the size of the subject is recognized, to correct a size of the subject to correspond to a ratio of the measured distance, and to correct a blank of a subject background formed by the corrected size of the subject. The intelligent device may be connected to an Artificial Intelligence (AI) module, a drone (Unmanned Aerial Vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, and a device related to a 5G service.

Abstract: A home monitoring system according to an aspect of the present disclosure relates to a home monitoring system and, more particularly, to a home monitoring system that can prevent a safety accident when a child or a pet approaches a predetermined dangerous space or a home IoT device, by sensing it, controlling the home IoT device, and making a user recognize it. According to the home monitoring system of the present disclosure, one or more of an IoT device and a server of the present disclosure may be associated with an artificial intelligence module, a robot, an AR (Augmented Reality) device, a VR (Virtual Reality) device, a device associated with 5G services, etc.

Abstract: An artificial intelligence apparatus for calibrating a color of a display panel includes a camera configured to capture an image displayed by the display panel; and a processor configured to: transmit a signal for outputting a color reference image to the display panel, receive, via the camera, a captured image for the display panel, calculate a color offset for the display panel in a predetermined unit based on the color reference image and the captured image, determine an output color calibration value for the display panel using the calculated color offset, and transmit the determined output color calibration value to the display panel.

Abstract: Disclosed are an augmented reality device and a gesture recognition calibration method thereof. The gesture recognition calibration method of the augmented reality device according to an embodiment of the present disclosure has the effect in that it is possible to perform more effective gesture recognition by determining the main eyesight of a user by calculating scores using coordinate systems. An AR device of the present disclosure may be associated with an artificial intelligence module, a drone ((Unmanned Aerial Vehicle, UAV), a robot, a VR (Virtual Reality) device, a device associated with 5G services, etc.

Abstract: A robot for detecting a dangerous situation using artificial intelligence includes a memory configured to store a voice recognition model for inferring whether a current situation is the dangerous situation from voice data and an image recognition model for inferring whether the current situation is the dangerous situation from image data, and a processor configured to acquire one or more of the voice data or the image data and output a notification indicating the dangerous situation when the dangerous situation is detected from the voice data using the voice recognition model or when the dangerous situation is detected from the image data using the image recognition model.

Abstract: According to the present invention, a method of displaying status information for a device to a user comprises receiving a control command for controlling the device to display the status information, determining the user's location, selecting other areas than where the user is located as mapping candidate areas, and selecting at least any one or more of the mapping candidate areas as a mapping area and displaying the status information in the mapping area in a projection fashion. Embodiments of the present invention may be related to artificial intelligence (AI) modules, unmanned aerial vehicles (UAVs), robots, augmented reality (AR) devices, virtual reality (VR) devices, and 5G service-related devices.

Abstract: Provided are a method and apparatus for determining driver's drowsiness. The method for determining driver's drowsiness includes: mapping the biometric data to a drowsiness determination model generated in advance; determining drowsiness of the driver based on a distribution of the biometric data in the drowsiness determination model; detecting first biometric data of the driver at a predetermined first time interval; correcting the biometric data of the driver detected during a time after the first time interval based on a center of distribution of the first biometric data; and determining whether or not the driver drowses based on the corrected biometric data, thereby optimizing the drowsiness determination model for each person/situation using driver data measured on a vehicle.

Abstract: An AI apparatus for providing a notification related to a lane-change of a vehicle includes a sensor unit including at least one of an image sensor, a radar sensor or a LiDAR sensor, and a processor to receive, from the sensor unit, sensor information on a surrounding road and each of at least one external vehicle, to acquire first driving information including a position on the road, a velocity and a steering state with respect to the vehicle using the sensor information, to calculate second driving information including a position, a distance, and a velocity of each of the at least one external vehicle using the sensor information, to determine a lane-change suitability of a lane-change based on the first driving information and the second driving information, and to output a notification related to the lane-change based on the determined lane-change suitability.

Abstract: An exercise monitoring apparatus capable of allowing a user to conveniently check a progressed exercise state and capable of properly controlling an exercise amount, by comparing a progressed exercise amount measured based on scheduling information received from an external apparatus and acceleration information of the exercise monitoring apparatus, with a goal exercise amount, and by visually providing a comparison result, a system and an exercise monitoring method thereof.

Abstract: An exercise monitoring apparatus capable of allowing a user to conveniently check a progressed exercise state and capable of properly controlling an exercise amount, by comparing a progressed exercise amount measured based on scheduling information received from an external apparatus and acceleration information of the exercise monitoring apparatus, with a goal exercise amount, and by visually providing a comparison result, a system and an exercise monitoring method thereof.