The present invention is a process and system for treating at least one piece of laundry that has a Radio-Frequency Identifier Tag, where the laundry is placed inside a double drum laundry processing system, the system including a receiver for reading signals from the RFID through openings for transmission in the inner drum to provide laundry data to processing unit which controls the cleaning cycle.

Disclosed is an artificial intelligence laundry treatment apparatus including a washing tub configured to receive laundry, the washing tub being configured to be rotatable, a motor configured to rotate the washing tub, a controller configured to control the motor such that the washing tub is rotated while being accelerated, and a current sensing unit configured to sense current of the motor, wherein the controller is configured to obtain laundry weight and laundry quality from output of an output layer of an artificial neural network pre-trained based on machine learning using a current value sensed by the current sensing unit during accelerated rotation of the washing tub as input of an input layer of the artificial neural network within a range within which the laundry moves in the washing tub.

The present invention is a process and system for treating at least one piece of laundry that has a Radio-Frequency Identifier Tag, where the laundry is placed inside a double drum laundry processing system, the system including a receiver for reading signals from the RFID through openings for transmission in the inner drum to provide laundry data to processing unit which controls the cleaning cycle.

Disclosed is an artificial intelligence laundry treatment apparatus including a washing tub configured to receive laundry, the washing tub being configured to be rotatable, a motor configured to rotate the washing tub, a controller configured to control the motor such that the washing tub is rotated while being accelerated, and a current sensing unit configured to sense current of the motor, wherein the controller is configured to obtain laundry weight and laundry quality from output of an output layer of an artificial neural network pre-trained based on machine learning using a current value sensed by the current sensing unit during accelerated rotation of the washing tub as input of an input layer of the artificial neural network within a range within which the laundry moves in the washing tub.