Disclosed herein is a washing machine and a control method thereof, and more particularly, to a technology capable of controlling washing modes in various manners by manipulating a control panel of the washing machine. The washing machine includes a display configured to display a washing mode, an inputter configured to receive a washing mode select command, a storage configured to store a selected washing mode, and a controller configured to allow a washing mode, which has the largest number of times selected during a predetermined number of times of washings, to be displayed on a first screen of the display, and in response to the number of the washing mode having the largest number of selection times being plural, configured to allow a washing mode, which is the last selected among the plurality of washing modes, to be displayed on the first screen of the display.

In a laundry treatment apparatus including a cabinet having an opening formed in one side thereof, a door rotatably coupled to the cabinet to open and close the opening, a drum rotatably provided inside the cabinet and configured to accommodate laundry introduced through the opening, a door lock unit provided inside the cabinet and configured to lock the door when the door closes the opening or release a locked state of the door in order to open the opening closed by the door, a communication unit configured to receive remote inputs of a user for communication with an external device, and a switch unit configured to connect or disconnect an external power, a locked state of the door and connection to the external power are maintained while a user maintains remote control after a preset cycle including rotation of the drum is performed.

A method and system are provided that synchronize one or more appliances to one or more users' schedules. Sensor data may be obtained from a sensor. The sensor data may indicate a state of a first appliance. A user location may be determined. A first characteristic of the first appliance may be obtained. Based upon the user location and the sensor data, a schedule indicating when the user will desire a state change of the first appliance may be determined. A feature of the first appliance may be dynamically modified to cause the first appliance to operate according to the schedule. A notice may be sent to the user that contains information about the first appliance.

A laundry dryer includes a cabinet, a user interface that is operably coupled to the cabinet, a motor that is disposed within the cabinet and communicatively coupled with the user interface, and a controller that is communicatively coupled with the user interface and the motor, respectively. The controller includes a memory storage that includes a plurality of night routines. The controller is configured with a selectable time point and is further configured to select at least one of the plurality of night routines at the selectable time point.

Provided herein are a method of controlling operation of a washing appliance and a washing appliance being controlled by the method. The method may include displaying, on a user interface of the washing appliance, an estimated duration of a selected washing program for the washing appliance; displaying, on the user interface, a degree of ecological impact caused by the selected washing program; allowing a user to operate the user interface to change the duration of the selected washing program, wherein the washing appliance adapts the selected cleaning program to comply with the changed duration; and displaying on the user interface the degree of ecological impact caused by the selected washing program when complying with the changed duration.

Provided is an electronic device. The electronic device includes a motor, a memory configured to store at least one of first frequency information associated with a sound that is generated when the motor is driven or second frequency information associated with a surrounding environment of the electronic device, and a processor configured to control the motor to be driven by avoiding a driving speed corresponding to the frequency information stored in the memory.

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.

An electronic device includes a camera to capture an image, and a processor to input an image acquired by photographing a detergent container into a trained model to acquire detergent information corresponding to the detergent container, and to guide an amount of detergent dispensed based on washing information corresponding to the detergent information. The trained model is a neural network trained using images of a plurality of detergent containers.

A method to control a laundry drying machine having a rotatable drum, a motor for rotating the drum, and a hot air generator for supplying a drying airflow to the drum. The method includes: collecting physicals quantities during an initial phase of said drying cycle, performing an estimation of polynomial coefficients of a cubic polynomial model indicative of an estimated change of a laundry moisture value over the time based on respective linear polynomial models comprising the collected physicals quantities, performing an estimation of the laundry moisture value by the cubic polynomial model based on the estimated polynomial coefficients, and controlling the motor and hot air generator during a drying cycle, based on one or more physicals quantities associated with the drum loaded with laundry, the electric motor and the hot air generator.

A home appliance and a control method for the home appliance, which is operable in an IoT environment through a 5G communication network and uses a neural network model generated according to machine learning is provided. The home appliance may include a home appliance main body; a container mounted within the home appliance main body to accommodate a treatment target; a camera arranged to photograph the inside of the container; and one or more processors configured to control an operation of the home appliance, wherein the processor is configured to determine an amount of a treatment target based on feature shapes of the container identified in an image of the inside of the container photographed by the camera.