Disclosed herein is an artificial intelligence-based laundry treating apparatus. The artificial intelligence-based laundry treating apparatus according to an embodiment of the present invention receives big data about information of an external environment capable of affecting laundry and life log data including activity information of a user wearing the laundry and automatically sets an optimal laundry management course for the laundry based on input factors including the big data and the life log data. Further, the artificial intelligence-based laundry treating apparatus may operate based on the optimal laundry management course to clean the laundry. A washing machine of the present invention may be associated with an artificial intelligence module, a drone (Unmanned Aerial Vehicle, UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to a 5G service, and the like.

Washing machine appliance ventilation systems and methods include rotating a wash basket of the washing machine appliance for an ON period, whereby a flow of ambient air is drawn through an aperture in the washing machine appliance from an ambient environment into the wash basket. The systems and methods also include comparing a humidity within the washing machine appliance to a reference humidity value. When a difference between the humidity within the washing machine appliance and the reference humidity value is greater than a threshold, the step of rotating the wash basket for the ON period is repeated. When the difference between the humidity within the washing machine appliance and the reference humidity value is less than or equal to the threshold, the ventilation cycle or method is terminated.

A laundry appliance includes a blower that delivers process air through an airflow path. A rotating drum defines a processing chamber. The processing chamber is part of the airflow path. A steam generating system disposes steam into the processing chamber. A plurality of fluid nozzles direct the steam into the processing chamber according to an operating pattern. The plurality of fluid nozzles include a first nozzle that is positioned within an upper portion of the processing chamber and a second nozzle that is positioned in a lower portion of the processing chamber.

A laundry appliance includes a drum that is rotatably mounted within a cabinet and defines a chamber for receiving articles of clothing. Primary and ambient air duct systems provide fluid communication between a conditioning system and at least one of the chamber of the drum and an ambient environment, respectively. A blower fan urges air through the conditioning system and a damper system is operably coupled to the ambient air duct system for selectively regulating a flow of ambient air. A controller is configured to receive a command to initiate a dehumidification cycle, operate the conditioning system and the blower, and regulate the damper system to permit the flow of ambient air to pass through conditioning system and through the ambient air duct system, thereby dehumidifying the ambient environment.

A clothes care apparatus includes a chamber, a first damper, a second damper, a heat exchanger, at least one blower fan, a sensor portion, and a controller. The first damper is configured to control an airflow from inside the chamber to outside the chamber. The second damper is configured to control the airflow into the chamber from the outside. The heat exchanger is provided with a compressor and configured to exchange heat with air in the chamber. The at least one blower fan is configured to generate the airflow. The sensor portion is configured to obtain a temperature and humidity inside and outside of the chamber. The controller is configured to start a drying cycle, control the first and second damper to be opened or closed, and control the heat exchanger and the at least one blower fan by comparing the internal humidity with the external humidity.

A clothes dryer comprising: a cabinet including a front panel on which an inlet is formed, a drum rotatably arranged in the cabinet and having a front opening and a rear opening, a front cover linking the inlet of the cabinet and the front opening of the drum, and including a slope portion having a diameter decreasing as being directed toward the inlet of the cabinet from the front opening of the drum, a rear cover connected to the rear opening of the drum and having an air inlet formed at the rear cover to allow air to be supplied toward the rear opening of the drum, and a sensing device arranged on the slope portion for sensing humidity in air discharged from the front opening of the drum.

A dryer is disclosed. The dryer includes a heat exchanger configured to remove moisture from air flowing and heat and discharge the moisture-removed air, a drum containing a material to be dried, a humidity sensor configured to detect a humidity of the air flowing from the drum, a fan configured to generate a flow of the air flowing along a flow path formed so that the air discharged from the heat exchanger flows to the heat exchanger via the drum and the humidity sensor, and a processor configured to determine a dried state of the material to be dried based on the humidity detected through the humidity sensor, and the humidity sensor is disposed at a position where a flow velocity of the air is equal to or higher than a predetermined velocity in the flow path formed between the drum and the heat exchanger.

The present disclosure relates to an artificial intelligence (AI) dryer. The AI dryer according to an embodiment of the present disclosure includes: a casing; a washing tub disposed in the casing; a motor configured to rotate the washing tub; a driver configured to drive the motor and including an output current detector for detecting an output current flowing through the motor; a heat supplier configured to supply heat to the washing tub; and a controller configured to control the driver, wherein the controller performs learning using DNN based on the output current detected by the output current detector, determines a load of laundry in the washing tub by the learning, and determines operation course information based on information of load of the laundry, thereby providing optimal operation course information corresponding to the information of load of the laundry.

A clothes dryer using an LED light source is proposed. Instead of using a heater, a blowing fan, and a heat exchanger, the clothes dryer employs a plurality of LED light source modules provided in a body and efficiently arranged therein and an air circulation structure of an air circulation part having a blowing fan arranged in the inner rear side thereof, and is configured to sterilize air through an air sterilization part, absorb and dry moisture by a ceramic filter, and then finally discharge the air to the outside through an exhaust fan. Therefore, without requiring a separate water discharge treatment process in an existing method, the clothes dryer can achieve efficient drying of clothes and drying of clothes without damage.

In embodiments of the invention, cartridge bins of laundry are disposed into drums for continuous flow (progressive) laundry processing. Each drum is supported by a carriage; the carriage is configured to articulate the drum and to cooperate with a space-saving processing track.