The invention relates to a laundry treating appliance and method for controlling the operation of the laundry treating appliance by determining the surface area of the laundry based on image data of the laundry.

Provided are a washing apparatus that is capable of being operated in an Internet of Things (IoT) environment over a 5G communication network and estimating additional laundry that is introduced and the amount of detergent that is additionally introduced based thereon through a neural network model generated based on machine learning, and a method of controlling the same.

A laundry treating appliance for treating laundry according to an automatic cycle of operation includes a cabinet defining a cabinet interior. A drum is rotatable within the cabinet interior, and at least partially defines a treating chamber. The treating chamber has a treating chamber air inlet and a treating chamber air outlet. A drying air circuit is fluidly coupled to the treating chamber air inlet and to the treating chamber air outlet. The laundry treating appliance can include first and second air temperature sensors, at least a first humidity sensor, and a controller operably coupled with the sensors.

A washing machine appliance includes a wash basket that is rotatably mounted within a wash tub and that defines a wash chamber for receiving a load of clothes. A basket speed sensor monitors the speed of the wash basket and a camera assembly is mounted within the wash tub for taking images of the load of clothes during and/or after a wash or rinse cycle. A controller determines the basket speed, adjusts a frame rate of the camera assembly to match the basket speed, obtains a still image from the camera assembly, analyzes the image using a machine learning image recognition process to determine a remaining moisture content (RMC) of the load of clothes, and adjusts at least one operating parameter of the washing machine appliance based on the remaining moisture content, e.g., such as ending the drain cycle when a target RMC is reached.

Hardware detection in a laundry treatment appliance is provided. Data is received from the sensor providing data in relation to presence or absence of a removable agitator within the laundry treatment appliance. A configuration of the removable agitator with respect to the laundry treatment appliance is identified based on the data from the sensor, the configuration indicating at least the presence or absence of the removable agitator. Settings of the laundry treatment appliance are updated in accordance with the identified configuration of the laundry treatment appliance.

A server, a washing machine, and a washing system including the same are provided. The washing system includes a washing machine and a server configured to receive turbidity information of washing water from the washing machine at pre-set time intervals, identify an amount of change in turbidity information of the washing water for the pre-set time intervals based on the received turbidity information, predict turbidity information of the washing water based on the amount of change in turbidity information of the washing water, and transmit a control signal for controlling a washing cycle of the washing machine based on the predicted turbidity information of the washing water.

The present invention relates to a clothing processing device which, when using artificial intelligence or an algorithm provided by artificial intelligence, can cause a user to visually recognize same, and an online system comprising same.

A method for operating a dryer appliance includes, after drying articles within the dryer appliance, receiving data corresponding to an activation signal for an extended tumble from a remote user device, tracking a number of cycles for which the extended tumble is not a default setting for the dryer appliance, and automatically adjusting the extended tumble to the default setting for the dryer appliance or transmitting data corresponding to an extended tumble alert based on the tracked number of cycles.

A method of operating a dryer appliance includes predicting a removal point at which a laundry load will be removed from the tub of the dryer, the removal point being a certain amount of time after the completion of a main drying operation, determining a length of time required to perform a conditioning operation on the laundry load, determining a start time for the conditioning operation, and implementing a responsive action at the start time.

A method of operating a dryer appliance includes activating a heating system of the dryer appliance and tracking an energy output of the heating system. The method also includes determining a load score of a load of articles to be dried in the dryer appliance based on the tracked energy output and determining a termination criterion for a dry operation of the dryer appliance based on the load score. The method further includes performing the dry operation in the dryer appliance and terminating the dry operation when the determined termination criterion is reached.