An apparatus, which is a drive apparatus, includes: a drive unit; a controller that obtains an application including a plurality of blocks, and executes the application to control the drive unit in accordance with the plurality of blocks; a first sensor; and a second sensor. Each of the plurality of blocks includes an end condition. When, during execution of a first block, the first driving state detected by the first sensor meets the end condition of the first block and the second driving state detected by the second sensor meets a block insertion condition, the controller: inserts a new block before a second block contiguous to the first block; and controls the drive unit in accordance with the new block and the second block.

Disclosed are an operating mode determining method and an operating mode determining device for determining an operating mode of a clothing treatment apparatus using image information by executing an artificial intelligence (AI) algorithm and/or machine learning algorithm in a 5G environment connected for the Internet of Things. According to an embodiment of the present disclosure, the operating mode determining method includes obtaining first image information obtained by photographing clothing through a camera of the clothing treatment apparatus, obtaining second image information obtained by photographing an entrance and exit of a user wearing the clothing through a camera for monitoring an entrance and exit of a room, and determining an operating mode of the clothing treatment apparatus according to an analysis result of the first image information and the second image information.

A method of controlling load volume in a laundry drying appliance where a load of wet laundry is place in a drum of the laundry drying appliance and the load volume of the wet laundry is sensed or determined according to the method. A condition of the drum of the laundry drying appliance is actively monitored and a determination is made if a proper load volume is present in laundry drying appliance.

A clothing treatment apparatus includes a cabinet which forms a treatment space for accommodating clothing, a duct in which an inside air channel which sucks inside air from the treatment space and guides the inside air to discharge the inside air to the treatment space, and an outside air channel which sucks outside air from an outer space of the cabinet and guides the outside air to discharge the outside air to the treatment space are preset, a fan which moves air in the duct, and (i) an opening and closing module which is operated to change whether or not a through-channel including at least one of an outside air inlet channel between the outer space and the outside air channel and (ii) an exhaust outlet channel between the treatment space and the outer space is blocked.

A laundry appliance includes a drum rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes, a door pivotally mounted to the cabinet for providing selective access to the chamber, and a user interface for controlling operation of the laundry appliance. A controller is configured to monitor the number of wash cycles that have occurred in the laundry appliance since the last self-clean cycle. Once the laundry appliance reaches a predetermined number of wash cycles without an intervening self-clean cycle, an automatic self-clean cycle is initiated upon the next selection of a drying cycle by the user, wherein the drying cycle provides an indication that the chamber is empty of article of laundry and that the user has no further immediate washing needs. In these circumstances, the controller is configured to reconfigure the selected drying cycle into a combination cycle including a self-clean cycle which is automatically followed by the desired drying cycle.

A washing machine appliance and methods for the same may include authorizing a user of the washing machine appliance and loading testing software into a partitioned memory of a controller. The testing software may include a testing sequence. The method may further include receiving a single testing prompt from a remote device following loading testing software and executing the testing sequence of the testing software from the partitioned memory in response to receiving the single testing prompt, whereby a mechanical component of the washing machine appliance is operated. The method may still further include exiting a remote testing mode after executing the testing software and deleting the testing software from the partitioned memory when exiting the remote testing mode.

A laundry appliance includes a basket rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes, a door pivotally mounted to the cabinet for providing selective access to the chamber, and a camera assembly mounted within the cabinet in view of the chamber. A controller is configured to initiate an automatic self-clean cycle, the method comprising determining that the door is closed, obtaining one or more images of the chamber using the camera assembly, determining that there is no load in the chamber based at least in part on the one or more images, determining that a self-clean condition is satisfied, and commencing the self-clean cycle.

The present disclosure discloses a control method of a multi-drum washing machine. The control method includes setting an oscillating program in the multi-drum washing machine. The oscillating program is a program in which oscillation generated by at least one washing device is used as an oscillating source to drive washing water and laundries in another at least one washing device to generate an interaction and achieve a washing effect. When at least one washing device oscillates, another at least one washing device and washing water and laundries in the washing device are driven to oscillate; and the vibration or jumping of the washing water in a drum is used to realize a function of soft washing of laundries and solve the problem of washing damage to soft laundries due to agitating type washing or beating type washing.

Disclosed is a washing system capable of detecting a level of contamination of a laundry tub by executing a big data, an artificial intelligence (AI) algorithm and/or a machine learning algorithm in a 5G environment connected for things Internet. The washing system capable of detecting a level of contamination of a laundry tub according to one embodiment of the present disclosure includes a composite sensor for detecting a level of contamination of a laundry tub, a washing machine controller that receives a digital signal from the composite sensor to determine a level of contamination of the laundry tub, and a server communicating with the washing machine. The washing machine controller or the server learns AI model with the training data set through a machine learning algorithm in order to predict a progressing degree of contamination of the laundry tub.

An artificial intelligent laundry treatment apparatus according to an embodiment of the present invention includes: a door including an external cover and an internal glass and configured to open and close a laundry entrance; a gasket formed on an inner circumferential surface of the laundry entrance; a door imaging sensor disposed to face the internal glass and configured to acquire a door image; a gasket imaging sensor configured to acquire a gasket image including a region of the gasket; and a processor configured to classify a state of the door on the basis of the door image, to acquire a gasket contamination degree on the basis of the gasket image, and to determine whether inside cleansing is required for a region including an inside of a drum on the basis of at least one of the classification result of the state of the door or the acquired gasket contamination degree.