Air-conditioner based on parameter learning using artificial intelligence, cloud server, and method of operating and controlling thereof

A cloud server, comprising:

• a communication unit configured to receive, from a plurality of air conditioners, at least one parameter generated during a time period for which the air conditioner is operated with a first cooling capacity based on a set temperature for the air conditioner, and transmit operation mode information to each of the plurality of air conditioners;
• a learning unit configured to receive the generated at least one parameter of a first air conditioner among the plurality of air conditioners as a learning factor and generate the operation mode information associated with an operation mode;
• and
• a server controller configured to control the learning unit and the communication unit,
• wherein the first air conditioner of the plurality of air conditioners is operated in a second operation mode associated with a second cooling capacity after the first air conditioner is operated in a first operation mode associated with the first cooling capacity for the time period, the second cooling capacity being different from the first cooling capacity,
• wherein the learning unit comprises:
• at least one input layer including the at least one parameter as at least one input node,
• at least one output layer including the operation mode information as at least one output node, and
• at least one hidden layer arranged between the at least one input layer and the at least one output layer, and
• wherein each of at least one node and at least one edge between the at least one input node and the at least one output node is associated with a weight value, the weight value being updated based on at least one of a learning process by the learning unit or an interrupt input transmitted by the first air conditioner.

A method for controlling an air conditioner based on learning, comprising:

• discharging, by a blower, air during a time period for which the air conditioner is operated with a first cooling capacity based on a set temperature;
• generating, by a parameter generator, a first set of parameters including at least one parameter during the time period;
• receiving, by a learning unit, the generated first set of parameters as a learning factor and generating operation mode information associated with an operation mode;
• providing, by a central controller, the generated operation mode information to an operation mode controller;
• updating each weight value associated with at least one nodes and at least one edges between at least one input node and at least one output node based on at least one of a learning process of the learning unit or an interrupt input of the central controller;
• and
• controlling, by the operation mode controller, at least one of the blower or an outdoor unit based on the generated operation mode information,
• wherein the air conditioner is operated in a second operation mode associated with a second cooling capacity after the air conditioner is operated in a first operation mode associated with the first cooling capacity for the time period, the second cooling capacity being different from the first cooling capacity,
• wherein the learning unit comprises at least one input layer including the at least one parameter as the at least one input node, at least one output layer including the operation mode information as the at least one output node, and at least one hidden layer between the at least one input layer and the at least one output layer.