A laundry appliance includes a basket rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes, and a camera assembly mounted within the cabinet in view of the chamber. A controller of the laundry appliance implements a method for improving appliance operation based on the load size, the method including obtaining one or more images of the chamber using the camera assembly, estimating a load size of the load of clothes based at least in part on the one or more images, obtaining a start size threshold, determining that the load size exceeds the start size threshold, and commencing an operating cycle in response to determining that the load size exceeds the start size threshold.

A laundry appliance includes a basket rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes, a water supply valve for regulating a flow of water into the chamber, and a camera assembly mounted within the cabinet in view of the chamber. A controller is configured to determine that the water supply valve is open to permit the flow of water into the chamber, identify an anticipated fog condition within the chamber based at least in part on the water supply valve being open, obtaining one or more images of the chamber using the camera assembly, analyzing the one or more images of the chamber to determine an actual fog condition in the chamber, and implementing a responsive action if the actual fog condition is different than the anticipated fog condition, e.g., providing a user notification.

A laundry appliance includes a basket rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes and a camera assembly mounted within the cabinet in view of the chamber. A controller is configured to implement a leftover load detection method including determining that an operating cycle of the laundry appliance has been completed and that a user has removed the load of clothes. A camera then obtains one or more images of the chamber and the images are analyzed to determine whether any articles of clothing remain in the chamber. If the image analysis identifies a leftover article remaining in the chamber, the method includes implementing a responsive action, such as providing a user notification.

A method of operating a washing appliance includes obtaining images of a wash chamber using a camera assembly operating at a frame rate equivalent to the basket speed. The one or more images are analyzed, e.g., using a machine learning image recognition process, to determine a cloth coverage ratio of the load of clothes in the wash basket. The cloth coverage ratio is compared to a predetermined coverage threshold for reducing out of balance conditions. Specifically, if the cloth coverage area is greater than the threshold, the wash basket may be ramped up to a hold or plaster speed. By contrast, if the cloth coverage area is less than the threshold, the basket speed may be maintained or lowered to permit the clothes to redistribute before ramping to the hold or plaster speed.

A laundry drying machine includes: a cabinet, a drum rotatably disposed in the cabinet and configured to accommodate a target object, and an electric field generator spaced apart from the drum and configured to, based on power being applied to the electric field generator, generate an electric field. The electric field generator includes an anode electrode spaced apart from the drum, fixed to the cabinet, and configured to apply the electric field to the target object, a power supply unit configured to supply the power to the anode electrode, and a matcher configured to match a source impedance of the power and an impedance of a load side. The drum is configured to rotate at an agitating rotation speed in a state in which the power supplied to the anode electrode is stopped, the agitating rotation speed being (i) greater than 0 rpm and (ii) less than 50 rpm.

A laundry drying machine includes: a cabinet, a drum rotatably disposed in the cabinet and configured to accommodate a target object, an electric field generator spaced apart from the drum and configured to, based on power being applied to the electric field generator, generate an electric field, and an exhaust duct configured to discharge air inside the drum. The electric field generator includes: (i) an anode electrode spaced apart from the drum, fixed to the cabinet, and configured to apply the electric field to the target object, (ii) a power supply unit configured to supply the power to the anode electrode, and (iii) a matcher configured to match a source impedance of the power and an impedance of a load side. The drum is configured to, based on a reflectivity of the electric field exceeding a predetermined ratio, reduce a rotation speed.

A laundry drying machine includes: a cabinet, a drum that is rotatably disposed in the cabinet and that is configured to accommodate a target object, and an electric field generator that is spaced apart from the drum and that is configured to, based on power being applied to the electric field generator, generate an electric field inside the drum. The electric field generator includes an anode electrode that is spaced apart from the drum, that is fixed to the cabinet, and that is configured to apply the electric field to the target object accommodated in the drum. The drum is configured to rotate while the power is applied to the anode electrode.

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.

Disclosed herein is a method of controlling an intelligent washing machine includes: obtaining a laundry image of laundry placed in a washing tub; extracting laundry classification information from the laundry image; calculating an estimated water supply time on the basis of the laundry classification information; and extending the reference water supply time if the estimated water supply time exceeds a predetermined reference water supply time, and supplying water to the washing tub for the extended reference water supply time. The washing machine may be associated with an artificial intelligence (AI) module, an unmanned aerial vehicle (UAV) (or drone), a robot, an augmented reality (AR) device, a virtual reality (VR) device, and a device related to a 5G service.

Disclosed is an artificial intelligence (AI)-based laundry treatment apparatus comprising: a washing module; a camera to acquire an image of laundry; a memory for storing therein a laundry recognition model, wherein the model is trained using a machine learning or deep learning algorithm, wherein the model is configured to recognize laundry information about the laundry; and a processor configured to apply image data from the acquired image to the laundry recognition model to acquire the laundry information.