Appliance, method and system for controlling the same, server and appliance controlling apparatus

A method for controlling an appliance, comprising:

• transmitting a parameter acquiring request to a server, the parameter acquiring request comprising an identifier of the appliance;
• according to the parameter acquiring request, generating a recommended parameter configuration list based on a machine learning model, wherein the machine learning model comprises a universal machine learning model and a personalized machine learning model, the recommended parameter configuration list comprises a universal recommended parameter configuration list and a personalized recommended parameter configuration list;
• receiving the recommended parameter configuration list transmitted by the server;
• configuring respective appliance parameters according to the recommended parameter configuration list;
• and
• controlling the appliance to operate according to the appliance parameters;
• wherein the generating the recommended parameter configuration list based on the machine learning model comprises:
• in determination that the personalized machine learning model is stored in a memory, generating the personalized recommended parameter configuration list based on the personalized machine learning model;
• and
• in determination that the personalized machine learning model is not stored in the memory, generating the universal recommended parameter configuration list based on the universal machine learning model.

A method for controlling an appliance, comprising:

• transmitting a parameter acquiring request to a server, the parameter acquiring request comprising an identifier of the appliance;
• according to the parameter acquiring request, generating a recommended parameter configuration list based on a machine learning model, wherein the machine learning model comprises a universal machine learning model and a personalized machine learning model, the recommended parameter configuration list comprises a universal recommended parameter configuration list and a personalized recommended parameter configuration list;
• receiving the recommended parameter configuration list transmitted by the server;
• updating the recommended parameter configuration list previously stored according to the recommended parameter configuration list received;
• and
• controlling the appliance to operate according to the updated recommended parameter configuration list;
• wherein the generating the recommended parameter configuration list based on the machine learning model comprises:
• in determination that the personalized machine learning model is stored in a memory, generating the personalized recommended parameter configuration list based on the personalized machine learning model;
• and
• in determination that the personalized machine learning model is not stored in the memory, generating the universal recommended parameter configuration list based on the universal machine learning model.

A server, comprising:

• a receiving device configured to receive a parameter acquiring request transmitted by an appliance, the parameter acquiring request comprising an identifier of the appliance;
• a generating device configured to generate a recommended parameter configuration list based on a machine learning model according to the parameter acquiring request, wherein the machine learning model comprises a universal machine learning model and a personalized machine learning model, the recommended parameter configuration list comprises a universal recommended parameter configuration list and a personalized recommended parameter configuration list;
• an acquiring device configured to acquire the recommended parameter configuration list;
• and
• a transmitting device configured to transmit the recommended parameter configuration list to the appliance to control the appliance to operate according to the recommended parameter configuration list;
• wherein to generate the recommended parameter configuration list based on the machine learning model comprises:
• in determination that the personalized machine learning model is stored in a memory, generating the personalized recommended parameter configuration list based on the personalized machine learning model;
• and
• in determination that the personalized machine learning model is not stored in the memory, generating the universal recommended parameter configuration list based on the universal machine learning model.

An appliance, comprising:

• a transmitting device configured to transmit a parameter acquiring request to a server, the parameter acquiring request comprising an identifier of the appliance;
• a receiving device configured to receive a recommended parameter configuration list corresponding to the identifier of the appliance generated and transmitted by the server;
• a configuration device configured to configure respective appliance parameters according to the recommended parameter configuration list;
• and
• a controlling device configured to control the appliance to operate according to the appliance parameters;
• wherein the recommended parameter configuration list is generated by the server based on a machine learning model according to the parameter acquiring request, wherein the machine learning model comprises a universal machine learning model and a personalized machine learning model, the recommended parameter configuration list comprises a universal recommended parameter configuration list and a personalized recommended parameter configuration list;
• wherein generating the recommended parameter configuration list based on the machine learning model comprises:
• in determination that the personalized machine learning model is stored in a memory, generating the personalized recommended parameter configuration list based on the personalized machine learning model;
• and
• in determination that the personalized machine learning model is not stored in the memory, generating the universal recommended parameter configuration list based on the universal machine learning model.

An appliance controlling apparatus, comprising:

• a transmitting device configured to transmit a parameter acquiring request to a server, the parameter acquiring request comprising an identifier of the appliance;
• a receiving device configured to receive a recommended parameter configuration list corresponding to the identifier of the appliance generated and transmitted by the server;
• an updating device configured to update a recommended parameter configuration list stored previously according to the recommended parameter configuration list received;
• and
• a controlling device configured to control the appliance to operate according to the updated recommended parameter configuration list;
• wherein the recommended parameter configuration list is generated by the server based on a machine learning model according to the parameter acquiring request, wherein the machine learning model comprises a universal machine learning model and a personalized machine learning model, the recommended parameter configuration list comprises a universal recommended parameter configuration list and a personalized recommended parameter configuration list;
• wherein generating the recommended parameter configuration list based on the machine learning model comprises:
• in determination that the personalized machine learning model is stored in a memory, generating the personalized recommended parameter configuration list based on the personalized machine learning model;
• and
• in determination that the personalized machine learning model is not stored in the memory, generating the universal recommended parameter configuration list based on the universal machine learning model.