An air conditioner system comprising: an air conditioner comprising a compressor, an outdoor heat exchanger configured to perform heat exchange using a refrigerant discharged from the compressor, a camera module configured to photograph the outdoor heat exchanger to obtain a digital image of the outdoor heat exchanger, a sensing unit which has a plurality of sensors, and a communication unit configured to transmit image data of the image of the outdoor heat exchanger photographed by the camera module and sensing data detected by the sensing unit; and a server comprising a communication unit configured to receive the transmitted image data and the transmitted sensing data, and a defrost controller configured to determine whether the outdoor heat exchanger is frosted based on the image data, and predict a frosting timing based on the sensing data, wherein the defrost controller comprises: a frosting detection unit configured to classify the image data of the outdoor heat exchanger into image data of frosting and normal states, by using a Convolutional Neural Network, CNN,-based image classification model; and a frosting start timing prediction unit configured to predict a remaining time until frosting, by using one or more machine learning models, when cycle operation data of the air conditioner is input, a defrost control unit configured to control the air conditioner to perform a defrost operation when the frosting detection unit determines a frosting state; a frosting prevention control unit configured to control to perform a frosting prevention operation, when the remaining time until frosting predicted by the frosting start timing prediction unit is less than or equal to a threshold value, and wherein the air conditioner system is configured such that in the defrost operation, when the air conditioner was in a heating operation, the air conditioner is switched to a cooling operation to operate until the frosting detection unit determines a normal state, and in the frosting prevention operation, the compressor is driven at an operating frequency lower than an operating frequency of the compressor of a normal state. an air conditioner comprising a compressor, an outdoor heat exchanger configured to perform heat exchange using a refrigerant discharged from the compressor, a camera module configured to photograph the outdoor heat exchanger to obtain a digital image of the outdoor heat exchanger, a sensing unit which has a plurality of sensors, and a communication unit configured to transmit image data of the image of the outdoor heat exchanger photographed by the camera module and sensing data detected by the sensing unit; and a server comprising a communication unit configured to receive the transmitted image data and the transmitted sensing data, and a defrost controller configured to determine whether the outdoor heat exchanger is frosted based on the image data, and predict a frosting timing based on the sensing data, wherein the defrost controller comprises: a frosting detection unit configured to classify the image data of the outdoor heat exchanger into image data of frosting and normal states, by using a Convolutional Neural Network, CNN,-based image classification model; and a frosting start timing prediction unit configured to predict a remaining time until frosting, by using one or more machine learning models, when cycle operation data of the air conditioner is input, a defrost control unit configured to control the air conditioner to perform a defrost operation when the frosting detection unit determines a frosting state; a frosting prevention control unit configured to control to perform a frosting prevention operation, when the remaining time until frosting predicted by the frosting start timing prediction unit is less than or equal to a threshold value, and wherein the air conditioner system is configured such that in the defrost operation, when the air conditioner was in a heating operation, the air conditioner is switched to a cooling operation to operate until the frosting detection unit determines a normal state, and in the frosting prevention operation, the compressor is driven at an operating frequency lower than an operating frequency of the compressor of a normal state. a frosting detection unit configured to classify the image data of the outdoor heat exchanger into image data of frosting and normal states, by using a Convolutional Neural Network, CNN,-based image classification model; and a frosting start timing prediction unit configured to predict a remaining time until frosting, by using one or more machine learning models, when cycle operation data of the air conditioner is input, a defrost control unit configured to control the air conditioner to perform a defrost operation when the frosting detection unit determines a frosting state; a frosting prevention control unit configured to control to perform a frosting prevention operation, when the remaining time until frosting predicted by the frosting start timing prediction unit is less than or equal to a threshold value, and wherein the air conditioner system is configured such that in the defrost operation, when the air conditioner was in a heating operation, the air conditioner is switched to a cooling operation to operate until the frosting detection unit determines a normal state, and in the frosting prevention operation, the compressor is driven at an operating frequency lower than an operating frequency of the compressor of a normal state.