• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.151-158
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• 2021

In this paper, we analyzed the latest research trends, challenges, and potential applications of next-generation solar cell materials in various industrial fields. In addition, future prospects and possibilities of Smart Textile Hybrid Energy Harvesting Devices that will supply electricity by combining with wearable IoT devices are presented. The hybrid textile energy harvesting device fused next-generation solar cells with tribo-piezoelectric devices will develop into new 'Convergence Integrated Smart Wear' by combining the material itself with wearable IoT devices in the era of the 4th industrial revolution. The next-generation nanotechnology and devices proposed in this paper will be applied to the field of smart textile with an energy harvesting function. And we hope it will be a paradigm shift that evolves into creative products which provide AI services such as medical & healthcare by convergence with the future smart wear industry.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.790-798
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• 2021

With digital technology innovation, increased data access and mobile network use by consumers, products and services are changing toward pursuing differentiated values for personalization, and personalized markets are rapidly emerging in the fashion industry. This study aims to identify trends in digital customized automation technology by deriving types of digital customizing and analyzing cases by type, and to present directions for the development of digital customizing processes and the use of technology in the future. As a research method, a literature study for a theoretical background, a case study for classification and analysis of types was conducted. The results of the study are as follows. The types of digital customizing can be classified into three types: 'cooperative customization', 'selective composition and combination', 'transparent suggestion', and automation technologies shown in each type include 3D printing, 3D virtual clothing, robot mannequin, human automatic measurement program, AR-based fitting service, big data, and AI-based curation function. With the development of digital automation technology, the fashion industry environment is also changing from existing manufacturing-oriented to consumer-oriented, and the production process is rapidly changing with IT and artificial intelligence-based automation technology. The results of this study hope that digital customized automation technology will meet various needs of personalization and customization and present the future direction of digital fashion technology, where fashion brands will expand based on the spread of digital technology.

• Journal of the Korean Home Economics Association
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• v.44 no.1 s.215
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• pp.25-35
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• 2006

This study investigated the scheme for correctly making Korean fashion design known to the world. It attempted to increase the influence of the Eighteenth Century Costume in contemporary fashion. During the 18th century, France had an almost complete monopoly of fashion. Growing out the fairyland atmosphere of the French Court and often conceived of as ennui by personal vanity, this fashion was a product of an age which sought at any price to live life with supreme grace. Most of the special costume exhibitions in the Metropolitan Museum of Art are planned and directed by Polaire Weissman, Diana Vreeland, Richard Martin, Harold Koda. The Costume Institute has held exhibitions of the Eighteenth Century Costume several times such as "Museum Period Rooms Re-Occupied in Style," "the Eighteenth Century Women," "the Ceaseless Century," "Dangerous Liaisons," etc. Especially, the exhibition of "Dangerous Liaisons" is organized in ten parts such as the Portrait, the Levee, the Music Lesson, the Withdrawing Room, the Broken Vase, the Favorite, the Masked Beauty, the Card Game, the Late Supper, and the Shop. Using the eighteenth century as its touchstone, The Ceaseless Century proceeds differently, not seeking the short distance between a discrete present and the multiple past but rather showing the complicated navigation that comes of revivalism swing to and fro on the timeline of history and sensibility. The designers featured include Karl Lagerfeld, Gianni Versace, Vivienne Westwood, Jean Paul Gaultier, Christian Dior, Cristobal Balencicga, Christian Lacroix, Stella McCartney forChloe, Olivier Theyskens, Alexander McQueen, etc. Therefore, Korean designers should refrain from (Ed-confirm) the foreign collection without a clear purpose and should devote their effort to create with an active attitude.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.1
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• pp.28-45
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• 2021

The importance of smart clothing as a product is increasingly emphasized as further growth in the potential of the smart market is expected. There is a high understanding and sympathy for the potential of smart clothing in the mass consumer market; therefore, commercialization is not actively carried out. This study enhances the understanding of the development direction of products with a focus on technical benefits, in order for smart clothing to gain access to customers as wearable devices. This study identifies major technologies used in smart clothing through an analysis of the patent technology status of smart clothing in Korea. Smart clothing is divided into three types: passive smart, active smart and advanced smart clothing based on a reaction mechanism and functional scope. We present the smart clothing and discuss the product features for three types. According to research, smart clothing products were equipped with passive, active, and advanced smart systems as well as provided new services by converging big data and AI technologies, rather than only using technologies such as sensors, controls, and actuators. Future directions for new smart clothing product development is also discussed in the conclusion.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.

• Smart Media Journal
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• v.12 no.7
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• pp.43-51
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• 2023

As online transactions increase, the image of clothing has a great influence on consumer purchasing decisions. The importance of image information for clothing materials has been emphasized, and it is important for the fashion industry to analyze clothing images and grasp the materials used. Textile materials used for clothing are difficult to identify with the naked eye, and much time and cost are consumed in sorting. This study aims to classify the materials of textiles from clothing images based on deep learning algorithms. Classifying materials can help reduce clothing production costs, increase the efficiency of the manufacturing process, and contribute to the service of recommending products of specific materials to consumers. We used machine vision-based deep learning algorithms ResNet and Vision Transformer to classify clothing images. A total of 760,949 images were collected and preprocessed to detect abnormal images. Finally, a total of 167,299 clothing images, 19 textile labels and 20 fabric labels were used. We used ResNet and Vision Transformer to classify clothing materials and compared the performance of the algorithms with the Top-k Accuracy Score metric. As a result of comparing the performance, the Vision Transformer algorithm outperforms ResNet.