Abstract: Disclosed is a data learning server according to an embodiment. The data learning server includes a communicator configured to be communicable with an external device, a learning data acquisition unit configured to acquire production information of a home appliance and operation information using the communicator, a model learning unit configured to generate or update a learning model using the product information and the operation information, and a storage configured to store a learning model trained to estimate a new trouble detection pattern related to the trouble item as a result of the generating or updating learning model. Various embodiments are available. The data learning server may estimate a new trouble detection pattern related to a trouble of a home appliance using rule-based or AI algorithm. When estimating a region of interest using the AI algorithm, the data learning server may use machine learning, neural network, or deep learning algorithm.

Abstract: Disclosed are an air conditioning apparatus and a control method thereof. An air conditioning apparatus comprises: a driving unit for performing a pre-configured function of the air conditioning apparatus; a sensor for collecting environmental information around the air conditioning apparatus; a memory for storing the collected environmental information; and a processor for controlling an operation of the driving unit on the basis of schedule information including an operating state defined according to a time change, and modifying the schedule information on the basis of environmental information collected during a pre-configured period of time.

Abstract: Disclosed is a data learning server according to an embodiment. The data learning server includes a communicator configured to be communicable with an external device, a learning data acquisition unit configured to acquire production information of a home appliance and operation information using the communicator, a model learning unit configured to generate or update a learning model using the product information and the operation information, and a storage configured to store a learning model trained to estimate a new trouble detection pattern related to the trouble item as a result of the generating or updating learning model. Various embodiments are available. The data learning server may estimate a new trouble detection pattern related to a trouble of a home appliance using rule-based or AI algorithm. When estimating a region of interest using the AI algorithm, the data learning server may use machine learning, neural network, or deep learning algorithm.

Abstract: An air conditioning device having an indoor heat exchanger, a heat recovery ventilator, a supply fan, and an exhaust fan inside a housing and configured to perform at least one of cooling/heating, heat recovery ventilation, and pure ventilation. The air conditioning device includes a first flow path configured to guide indoor air while the cooling/heating is performed, a second flow path configured to guide the indoor air toward the heat recovery ventilator, and a third flow path configured to guide outdoor air toward the heat recovery ventilator while the heat recovery ventilation is performed. The air conditioning device includes fourth and fifth flow paths configured to guide indoor air and outdoor air, respectively, and an inlet port that corresponds to the third flow path and the fifth flow path, and a discharge port that corresponds to outlets of the second flow path and the fourth flow path.