• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.949-958
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• 2022

Modern people have many kinds of clothes for individuals, and not just for storing clothes, but also for managing the condition of the closet, and users of smart closets created smart closets that provide daily convenience and optimal closet conditions, suggesting the possibility of developing smart furniture for various environments. In this developed system, smart closet is controlled using app inventor and touch LCD through bluetooth wireless communication, based on Arduino MEGA and user's clothes is recommended depending on the weather. In addition, this smart closet is designed with real-time weather status checking and easy ventilation function. It was implemented through the Arduino and app inventor program so that the weather can be printed on the LCD screen and the user's suitable clothes can be recommended to the application.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.245-248
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• 2023

본 논문은 스마트 옷장의 시장성과 기능에 대해 연구하고, 사용자에게 편의성과 개인화된 서비스(실시간 정보 제공, 온습도 제어, UV 살균 기능) 등 다양한 기능을 통해 사용자의 요구를 충족시키며, 스마트 기기와의 연동, 맞춤형 스타일 추천, 얼굴 인식 기술 등의 추가 기능을 통해 지속적인 개선과 혁신을 제안한다.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.357-363
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• 2021

In general, people choose clothes to wear when they go out, referring to real-time weather and temperature. However, it is difficult for an individual to use real-time weather information and his or her temperature sensitivity information to choose the right clothes from among the clothes he or she owns. Existing clothing recommendation systems developed to help with these problems have problems recommending clothes that are not clearly set in the clothing category and are not in the possession of the user. In addition, user-specific temperature sensitivity is not taken into account, resulting in inappropriate clothing recommendations for users. To solve these problems, this study developed a system that determines and registers clothing categories for the clothing owned by the user, and recommends customized clothing for each user by considering temperature sensitivity and real-time weather information. In the case of weather information, not only weather information such as temperature and wind direction, but also clothes based on temperature sensitivity were recommended based on the calculation of temperature sensitivities. A satisfaction survey of 65 university students was conducted to assess the system. As a result, 80% of the respondents were satisfied with the recommended clothing, indicating that the satisfaction of the system was good. Therefore, it is expected that this system will be highly utilized in real life as it will be recommended based on clothes owned by individuals, reflecting individual temperature sensitivity.