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Based on the current process of clothing design and development, as well as research and analysis of domestic and foreign literature, this article guides the current digitalization status of the front-end and back-end of the clothing industry and proposes the research problem of this topic. Through clothing design modeling (physical model and design of fabrics, collision detection analysis between human body and fabrics, clothing fabric rendering, and flexible 3D clothing simulation model) and dynamic virtual display of clothing, an effective method to solve the problem is constructed. It has been found that during the design phase, the real effect of clothing fabrics can be realistically restored, and the development speed can be improved, reducing labor costs. At the same time, dynamic simulation display can be used to solve the cost waste problem of sample materials. It can also improve the product selection rate and design level, and solve cost and time problems at the source.

Abstract The body area network (BAN) is composed of every wearable device network on the body to share information and data, which is applied in medical and health, especially in the direction of intelligent clothing. A wearable device is an integrated body of multi‐sensor fusion. At the same time, the multi‐dimensional needs of users and the unique problems of sensors appear. How to solve the problems of wearable sensors and sustainable design is the research focus. Based on the wearable sensor in the critical factor of wearable device fusion, this paper analyses the classification, technology, and current situation of a wearable sensor, discusses the problems of a wearable sensor for BAN from the aspects of human–computer interaction experience, data accuracy, multiple interaction modes, and battery power supply, and summarizes the direction of multi‐sensor fusion, compatible biosensor materials, and low power consumption and high sensitivity. The sustainable design direction of visibility design, identification of use scenarios, short‐term human–computer interaction, interaction process reduction, and integration invisibility are introduced. The integration research of wearable sensors is the future trend, and it has been widely used in medical and health, intelligent clothing, wireless communication, military, automobile, and other fields.

The decline in birth rates has raised concerns about the safety of infants and young children (0–18 months), particularly those who suffer suffocation or even death during sleep from their own or external causes. How to ensure that infants and young children can safely pass through this dangerous period after birth is the focus of this project. This article focuses on sleeping infants and young children as the subject of research. Blood oxygen sensors and heart rate sensors attached to socks are used to monitor changes in blood oxygen and heart rate when infants and young children experience asphyxia. The changes are then transmitted via Bluetooth to a mobile app and an alarm sound is generated to act as a good warning. At the same time, the researchers received good feedback from testing the garments on two babies and toddlers, indicating they provide an effective warning. [ABSTRACT FROM AUTHOR]

With the outbreak and ongoing spread of the COVID-19 pandemic, a wave of post-COVID-19 zeitgeist has emerged worldwide. From the perspective of fashion trends, an increasing number of consumers are demanding higher standards of health, environmental friendliness, and sustainability. Over the past 10 years, the integration of technology in clothing has facilitated continuous updates in both functionality and aesthetics. This article aims to explore the relationship between clothing technology and sustainable fashion in the post-COVID-19 era, seeking to enhance the development and innovation of sustainable fashion through the empowerment of clothing technology. This study conducts extensive research on the literature and online case studies, categorizing empowered sustainable fashion technology design cases into six major categories and four directional themes. It introduces an innovative sustainable fashion design assessment model, PCBS (Product, Customer, Business, Society). Subsequently, the knowledge framework is applied in design practice alongside consumer research to validate the system's usability. Furthermore, this research synthesizes and summarizes the methods through which fashion technology can support sustainable fashion in the post-pandemic era. Designers and practitioners can reference these insights for more advanced sustainable design initiatives, thereby promoting a lower-carbon and environmentally friendly system that drives global innovation and development in a sustainable society. [ABSTRACT FROM AUTHOR]

With the popularity of the concept of big health and the important role of wearable devices in medical health, users pay more attention to the collection and acquisition of physiological data, but wearable devices attached to human users are independent, and the degree of data sharing is low. Improving the data sharing, accuracy, and reliability of wearable device monitoring is a problem that the article needs to study and solve. Specifically, the researcher summarizes the characteristics of the physiological monitoring smart clothing, and the basic physiological data parameters of human body, and analyzes the collection of three basic signals of electrocardiogram, body temperature, and human movement. This article summarizes the requirements and key technologies of body area network transmission of smart clothing, and studies the body area network node design, energy consumption optimization mode, and network architecture of physiological monitoring smart clothing. At the same time, based on the previous research, the multi-interaction process of smart clothing is formed, and then the standard evaluation system of smart clothing body domain network for evaluation is proposed. The results show that the optimized structure of the body area network of smart clothing proposed by the researchers is efficient, convenient, and mobile, and meets the characteristics of safety, reliability, low power consumption, and portability of smart clothing, especially in the field of physiological monitoring. The standard evaluation system of smart clothing body area network provides a practice-oriented theoretical reference for the current research of smart clothing body area network.

AbstractArtificial intelligence generated content (AIGC) technology has brought challenges and opportunities for the fashion industry. However, the factors influencing the willingness of fashion industry practitioners to use AIGC tools remain unclear. This study expands the unified theory of acceptance and use of technology (UTAUT) model by incorporating the concepts of commercial value and perceived risk, and it builds a quantitative model on this basis. Data from 386 participants in the fashion industry were collected and analyzed using structural equations. The results show that most of the influencing factors proposed in the extending UTAUT model apply to the use of the AIGC tool in the fashion industry. Specifically, performance expectancy, effort expectation, social influence, facilitating conditions, and commercial value can positively and significantly impact behavioral intention. Perceived risk can negatively and significantly impact behavioral intention. The correlation between job responsibilities and creativity and the years of working can significantly interfere with the effect of intention to use AIGC tools. [ABSTRACT FROM AUTHOR]

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