A dryer appliance includes a microphone for monitoring sound generated during operation of the dryer appliance and a controller is operably coupled to the microphone. The controller is configured for obtaining a sound signal generated during operation of the dryer appliance and converting the sound signal into a spectrogram that represents a sound frequency and a sound amplitude over time. An artificial intelligence image recognition process is used to analyze the spectrogram to identify one or more sound signatures that are associated with particular operating conditions, and operation of the dryer appliance is adjusted based at least in part on the identification of the sound signature.

A dryer appliance includes a microphone for monitoring sound generated during operation of the dryer appliance and a controller is operably coupled to the microphone. The controller is configured for obtaining a sound signal generated during operation of the dryer appliance and converting the sound signal into a spectrogram that represents a sound frequency and a sound amplitude over time. An artificial intelligence image recognition process is used to analyze the spectrogram to identify one or more sound signatures that are associated with particular operating conditions, and operation of the dryer appliance is adjusted based at least in part on the identification of the sound signature.

A laundry dryer includes a cabinet, a user interface that is operably coupled to the cabinet, a motor that is disposed within the cabinet and communicatively coupled with the user interface, and a controller that is communicatively coupled with the user interface and the motor, respectively. The controller includes a memory storage that includes a plurality of night routines. The controller is configured with a selectable time point and is further configured to select at least one of the plurality of night routines at the selectable time point.

A dryer appliance includes a microphone for monitoring sound generated during operation of the dryer appliance and a controller is operably coupled to the microphone. The controller is configured for obtaining a sound signal generated during operation of the dryer appliance and converting the sound signal into a spectrogram that represents a sound frequency and a sound amplitude over time. An artificial intelligence image recognition process is used to analyze the spectrogram to identify one or more sound signatures that are associated with particular operating conditions, and operation of the dryer appliance is adjusted based at least in part on the identification of the sound signature.

A dryer appliance includes a microphone for monitoring sound generated during operation of the dryer appliance and a controller is operably coupled to the microphone. The controller is configured for obtaining a sound signal generated during operation of the dryer appliance and converting the sound signal into a spectrogram that represents a sound frequency and a sound amplitude over time. An artificial intelligence image recognition process is used to analyze the spectrogram to identify one or more sound signatures that are associated with particular operating conditions, and operation of the dryer appliance is adjusted based at least in part on the identification of the sound signature.

A dryer is provided. The dryer includes a cabinet, a drum rotatably disposed inside the cabinet, at least one roller mounted on at least one surface inside of the cabinet to support the drum, a motor configured to provide power to rotate the drum, a motor driver configured to control the motor, and at least one processor configured to determine at least one of a first rotation velocity of the motor or a first rotation time of the motor based on a non-use time of the dryer, and control the motor driver based on the determined at least one of the first rotation velocity or the first rotation time of the motor.

A dryer is provided. The dryer includes a cabinet, a drum rotatably disposed inside the cabinet, at least one roller mounted on at least one surface inside of the cabinet to support the drum, a motor configured to provide power to rotate the drum, a motor driver configured to control the motor, and at least one processor configured to determine at least one of a first rotation velocity of the motor or a first rotation time of the motor based on a non-use time of the dryer, and control the motor driver based on the determined at least one of the first rotation velocity or the first rotation time of the motor.

A compressor frequency regulation method includes acquiring a first exhaust temperature of a compressor operating at a first operating frequency; determining that the first exhaust temperature is greater than or equal to a first preset temperature; controlling the compressor to perform frequency reduction processing, the frequency reduction processing reducing the first operating frequency to a second operating frequency, such that a second exhaust temperature of the compressor operating at the second operating frequency is less than the first preset temperature; and controlling the compressor to operate at the second operating frequency.

A compressor frequency regulation method includes acquiring a first exhaust temperature of a compressor operating at a first operating frequency; determining that the first exhaust temperature is greater than or equal to a first preset temperature; controlling the compressor to perform frequency reduction processing, the frequency reduction processing reducing the first operating frequency to a second operating frequency, such that a second exhaust temperature of the compressor operating at the second operating frequency is less than the first preset temperature; and controlling the compressor to operate at the second operating frequency.

A method for controlling a home appliance in consideration of a state of a surrounding environment is disclosed. A method for controlling a home appliance according to an exemplary embodiment of the present disclosure includes operating a home appliance using a first operation profile, identifying at least one of a behavior type of a user or a type of sound around the user, using Internet of Things (IoT) communication using 5G communication and artificial intelligence (AI), and changing an operation profile for operating a home appliance to a second operation profile, based on at least one of the identified behavior type of the user or type of sound around the user. According to the present disclosure, in accordance with the state of the surrounding environment, the operation noise can be reduced or the operation time of the home appliance can reduced without increasing the discomfort of the user, and therefore the discomfort of the user due to the operation noise can be relieved.