Disclosed are a method for controlling a commercial washing machine by using artificial intelligence and a system for the same. The method for controlling a commercial washing machine by using artificial intelligence comprises: a step of receiving a request for use of a plurality of commercial washing machines connected to each other through a network from a user through a user terminal; a step of transmitting the request for use to a cloud server; a step in which the cloud server selects an available one of the plurality of commercial washing machines for the request for use and sets the commercial washing machine to a standby state; and a step in which the cloud server provides the user with a recommended washing course created based on a user's use history of the plurality of commercial washing machines.

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.

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.

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.

Methods, system and apparatus for the controlling laundry machines in a laundry facility. A user device receives a list of machines for a laundry facility and displays them on a machine control user interface. The user may then make a selection of a machine, a selection of an operation type and a selection of one or more operational parameters associated with the selected operation type. The selection of the operation type and the one or more operational parameters may be made on the user device or on the selected machine. The machine control user interface may then display the user selections, an estimated duration and a cost. The estimated duration and cost may be based on the selected machine, selected operation type and the one or more selected operational parameters.

A system and method are described for carrying out machine learning-based automated laundry machine error/degraded status detection and maintenance by use of acoustic sensor data rendered by the laundry machines and applied to a plurality of machine learning models for use with acoustic data rendered by the laundry machines.

An Internet of Things washing machine control method comprises the steps of, when a power module of the washing machine detects a startup signal, starting up the washing machine, and enabling a communication module to start to connect with the Internet; judging whether the communication module is successfully connected with the Internet, if yes, activating a remote control function and entering the next step, and if no, directly entering the next step; judging whether the washing machine receives an operating command of running a clothes washing program, if yes, executing the operating command and entering the next step, and if no, directly entering the next step; judging whether to shut down the washing machine, if yes, entering the next step, and if no, returning to the step; sending a shutdown signal to the power module, shutting down the washing machine, and powering off the communication module.

A method of batch processing that includes registering item types to be processed by a batch management system including care instructions for the item types; recording batch items being added to a batch processing machine; and determining compatibility of at least one of each of said batch items being added to the batch processing machine to a total batch with an item to be processed to registered item match generator of said batch management system. Determining compatibility includes matching at least one of each item being added to the batch processing machine to the care instructions of the registered item types. The method may further include reporting compatibility of at least one of each item being added to the batch processing machine.

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.

Methods, systems and apparatus for managing the servicing of dispensers including a system having a plurality of dispensers each configured to be located in a same washroom and dispense a respective consumable hygiene product; and a controller configured to be located in the washroom, remote to the plurality of dispensers and have a service mode and an operation mode different than the service mode, wherein, when in the service mode, the controller is configured cause an audible or visual indication of a servicing need of at least one of the plurality of dispensers, and wherein the servicing need is one of the at least one of the plurality of dispensers having: low or no consumable hygiene product remaining, an electrical or mechanical malfunction, and a low battery condition.