Search Results (379)

Sustainable road safety continues to be a major concern worldwide, with failure to wear seatbelts representing a significant risk, particularly in developing countries. In this study, we propose a deep learning-based framework for the automatic detection of seatbelt violations, leveraging a custom dataset collected on Moroccan roads that captures different vehicle types, driver clothing color variations, and environmental conditions. We explore the YOLO family of object detection models, from YOLOv8 to YOLOv26, evaluating 23 variants ranging from nano to large architectures. Each model was trained to classify drivers as Person–Seatbelt or Person–No-Seatbelt. Experimental results on this diverse dataset demonstrate that the proposed approach achieves a validation mAP@0.5:0.95 of 63.5% and a test mAP@0.5:0.95 of 56.1% on three entirely unseen vehicles, highlighting its robustness across previously unseen driver and vehicle conditions. To assess real-world deployment, the best-performing models are further benchmarked on the NVIDIA Jetson Orin Nano embedded platform using PyTorch and TensorRT FP16 formats in MAXN mode, with the most efficient configuration sustaining 94.4 FPS inference at 6.40 W. This work contributes to sustainable road safety by developing traffic violation detection systems and provides a foundation for future automated monitoring of driver behavior in real-world conditions. Full article

Textile waste has become a major environmental challenge associated with increasing levels of production and consumption in the fashion industry. The fast fashion business model, characterised by rapid production cycles, low prices, and frequent replacement of clothing items, contributes significantly to growing volumes of textile waste and the depletion of natural resources. This study examines students’ perceptions of the environmental impacts of textile waste and fast fashion, with particular emphasis on sustainable consumption practices and textile waste management in Croatia. The study combines a review of the scientific literature with an online questionnaire survey conducted among a non-probability convenience sample of 79 students enrolled in different study programmes in Croatia. The results indicate a high level of environmental awareness and familiarity with textile waste issues among respondents. However, despite generally positive attitudes towards sustainability, willingness to modify purchasing behaviour or pay higher prices for sustainable clothing remained limited, indicating a clear attitude–behaviour gap. Price emerged as a particularly important factor influencing purchasing decisions, while limited access to textile collection facilities was identified as an important barrier to proper textile waste management. Chi-square tests of independence did not identify statistically significant associations between environmental concern and support for sustainable fashion or between level of education and the examined sustainability-related consumption responses. The findings suggest that environmental awareness alone may not be sufficient to encourage sustainable consumption and highlight the importance of combining environmental education with economically accessible sustainable alternatives and adequate textile collection infrastructure. The study provides exploratory insight into the relationship between environmental awareness, consumer behaviour, and self-reported textile management practices among the surveyed students and contributes to the discussion on promoting more sustainable textile consumption within a circular economy. Full article

The three-dimensional (3D) documentation of the Similaun mummy (Ötzi the Iceman) and the associated Copper Age equipment and clothing presents unique challenges due to diverse material properties and strict conservation constraints. This study presents a comprehensive digital preservation workflow, primarily utilizing Structure from Motion (SfM) close-range photogrammetry (a method that reconstructs precise 3D geometry from overlapping 2D digital photographs), integrated with Image-Based Modeling (IBM) and Neural Radiance Field (NeRF) algorithms (a machine learning approach that models a complex scene as a continuous volumetric function method). To overcome the non-Lambertian properties of the mummy’s protective ice layer and wet skin (surfaces that reflect light specularly rather than diffusely, creating glares that can disorient standard reconstruction algorithms), a specialized Polarized Light Photography (PLP) strategy was implemented using custom-built hardware. This integration required advanced anatomical segmentation to resolve postural discrepancies caused by taphonomic processes. The resulting web-based application provides the scientific community with a metrically accurate digital twin, featuring interactive tools for cross-sectioning and X-ray visualization. By adopting a Free/Libre and Open-Source Software (FLOSS) ecosystem, this project establishes a sustainable, modular framework for future forensic investigations and diachronic monitoring, ensuring the long-term digital life of one of the world’s most significant archaeological finds. Full article

The transition to a circular economy requires professionals to adopt new strategies and a systemic approach to product development. This shift demands continuous learning and the development of new competencies to understand and apply circular economy principles. In this context, innovative educational approaches that foster engagement and lifelong learning (LLL) are essential. Gamification can support this process by enhancing motivation, creativity, problem-solving, and knowledge retention, while interactive tools help learners critically examine and operationalise circular economy principles. This article discusses the design and application of the “Circularity Deck of Cards,” a learning resource developed as part of a European-funded project Be@t, to facilitate the circular design of products and services. The study follows a mixed-methodological approach encompassing three phases: a systematic mapping of international tools and methodological approaches; the conceptual and visual development of the resource; and its implementation and evaluation through a workshop involving undergraduate, master’s, and doctoral students and researchers in fashion design and textile engineering in Portugal. The data were collected using a questionnaire that combined quantitative and qualitative questions, designed to assess the receptiveness to, challenges of, and opportunities arising from gamification in the teaching of circular design. The findings indicate that participants responded positively to the tool, recognising its value as both a pedagogical resource and a professional instrument for promoting sustainability and circularity in the textile and clothing industry. Ultimately, gamification catalyses training students, designers, and industry professionals to address the challenges of circularity, fostering new perspectives on circular design in professional practice. Full article

Artificial intelligence (AI)-powered online shopping is profoundly reshaping the way in which consumers engage with sustainable clothing. However, the relationships between digital multisensory cues and perceived quality with sustainable consumption intention still need to be explored. Based on the Stimulus–Organism–Response (S-O-R) framework, the present study explores the relationships of digital multisensory cues and perceived quality with consumers’ flow experience, pleasure, and responses (e.g., engagement, loyalty, and sustainable consumption intention) in the context of AI-powered online shopping using a cross-sectional, scenario-based, assisted recall survey. A total of 571 valid responses were retained for analysis. Partial least squares structural equation modelling (PLS-SEM) was adopted for data analysis. The findings indicate that digital multisensory cues showed a positive relationship with pleasure, whereas perceived quality was positively associated with both flow experience and pleasure. Flow experience was positively linked to pleasure, which was further associated with engagement and sustainable consumption intention. Statistically significant indirect effects on sustainable consumption intention through pleasure were observed for flow experience, digital multisensory cues, and perceived quality. The results of this study offer practical implications for retailers seeking to design emotionally engaging AI-powered shopping experiences that may support sustainable consumption intention. Full article

Environmental sustainability of natural and synthetic fibers used in textiles and composites depends on their impacts throughout production, use, and end-of-life (EoL) stages. Natural fibers are renewable and biodegradable but may require substantial water and agricultural inputs, whereas synthetic fibers contribute to fossil resource depletion, microplastic pollution, and persistent waste generation. Natural fibers are often regarded as more sustainable alternatives to synthetic fiber; however, evidence from a life cycle assessment (LCA) reveals a more nuanced reality. As demand for fiber-based materials increases across textile and composite applications, a deeper understanding of the environmental implications of both natural and synthetic options becomes essential. This review compares these fiber categories from a life cycle perspective, examining carbon footprint, energy demands, resource consumption, and EoL pathways. Natural fibers such as cotton, flax, jute, hemp, sisal, banana, coir, and emerging plant-based alternatives offer advantages including biodegradability and carbon sequestration during cultivation. Nevertheless, agricultural practices and subsequent industrial processing require substantial land, water, and chemical inputs. Synthetic fibers, predominantly derived from fossil resources, provide a long service life and consistent performance but are associated with high greenhouse gas (GHG) emissions, dependence on non-renewable feedstocks, microplastic pollution, and broader environmental impacts. By presenting a comprehensive life cycle-based comparison, this review identifies the conditions under which each fiber type may offer environmental benefits, supporting informed material selection for sustainable development. Full article

Generative artificial intelligence (GenAI) is reshaping fashion design by expanding creative possibilities and accelerating innovation. For independent designer brands, which rely on originality, distinctive aesthetics, and creative identity, GenAI offers opportunities to sustain innovation while raising concerns about authenticity and consumer trust. However, consumer responses toward AI-generated clothing (AGC) among AGC-interested young Chinese consumers remain underexplored. This study explores factors influencing their attitudes and purchase intention toward AGC. Drawing on a TPB–TCV-based integrated framework, this study develops an integrated model incorporating consumption value dimensions, perceived effort of the brand in design (PEBD), generative quality (GQ), and AI creativity (AIC). Based on 568 valid questionnaires, PLS-SEM was employed, with multi-group analysis as a supplementary analysis. The results show that attitude plays a key mediating role in explaining purchase intention. Specifically, PEBD and subjective norm significantly predict purchase intention, while PEBD also indirectly influences purchase intention through attitude. Emotional, epistemic, and social values, PEBD, GQ, and AIC significantly contribute to attitude formation, whereas only PEBD and subjective norm demonstrate significant direct effects on purchase intention. These findings provide managerial insights for independent designer brands seeking to apply GenAI while considering consumer perceptions of creativity, originality, and value in shaping AGC purchase intention. Full article

The increasing environmental impact of the textile industry has heightened interest in sustainable consumption practices, particularly second-hand clothing consumption. However, instruments assessing attitudes toward second-hand clothing remain limited. This study aimed to develop a scale to assess university students’ perceptions, sustainability orientations, values, and attitudes toward second-hand clothing consumption and to provide evidence of its psychometric properties. An initial pool of 45 items was generated through a literature review and focus group interviews with students from 14 universities representing different geographical regions of Türkiye. Exploratory Factor Analysis (EFA) was conducted using data from 244 university students. After removing nine items, a 36-item, eight-factor structure accounted for 66.43% of the total variance. The factors were labeled Saving, Fashion, Social Interaction, Spiritual Well-Being, Brand Orientation, Sustainability, Trust, and Nostalgia. Confirmatory Factor Analysis (CFA) performed on an independent sample supported the proposed structure and demonstrated an acceptable model fit (χ²/df = 2.16; CFI = 0.854; TLI = 0.838; RMSEA = 0.069; SRMR = 0.074). Cronbach’s alpha coefficients ranged from 0.712 to 0.913. Overall, the findings indicate that the proposed scale demonstrates acceptable psychometric properties and has the potential to assess university students’ attitudes toward second-hand clothing consumption in future research. Full article

This study investigates the impact of environmental factors, financial conditions, and trade-related policy on Thailand’s textile and clothing exports under the ASEAN–China Free Trade Agreement (ACFTA) and the WTO’s Agreement on Textiles and Clothing (ATC), focusing on export performance and trade creation between 1990 and 2024, using strong panel data across 31 countries from 11 ASEAN–China member countries and 20 non-member countries. This study has been guided by Porter’s competitive advantage theory and the gravity trade framework. The analysis was conducted using STATA 18 to analyze the fixed-effects regression alongside a robust Poisson Pseudo-Maximum Likelihood (PPML) estimation. The results indicate that (1) improvements in environmental, trade, and financial conditions are associated with higher export performance, (2) the results do not support trade creation under ACFTA, with the estimated ACFTA coefficient being negatively associated with export volume, and (3) the post-ATC effect is not consistently supported across model specifications and is not statistically significant in the combined specification. The findings suggest that export performance is jointly influenced by these dimensions rather than by trade liberalization and the post-ATC agreement alone. We recommend that policymakers support firms in managing the transition costs associated with green production, strengthen international trade cooperation, and maintain macroeconomic stability to enhance the long-term export performance of Thailand’s textile and clothing industry. These findings provide evidence that environmental sustainability and macro-financial conditions remain important determinants of export performance under changing global trade conditions. Future research may incorporate additional variables, broader datasets, and alternative econometric approaches to further validate the robustness of the findings. Full article

Thermal comfort shapes occupant health, well-being, and productivity and influences the sustainability and energy efficiency of the built environment. The Predicted Mean Vote (PMV) is the most widely used thermal comfort index, yet four of its six input parameters—globe temperature, clothing insulation, metabolic rate, and air velocity—require specialized, costly equipment or occupant self-reporting, which has long limited its practical large-scale application. This study introduces a machine learning (ML) framework aimed at estimating these four parameters using indoor and outdoor air temperature and relative humidity as its only sensor inputs, complemented by readily available contextual information and individual activity profiles. It exploits the climatic coupling of globe temperature and air velocity to the indoor–outdoor environment and the temperature- and activity-driven behavioral patterns that govern clothing insulation and metabolic rate. The proposed framework achieved strong predictive performance, explaining 85% of the variance in actual PMV values (R² = 0.85), with a near-zero mean residual (−0.041) and a residual standard deviation of 0.286. Approximately 91% of absolute errors fell below 0.5 PMV units—a deviation unlikely to shift the assigned thermal comfort category. Mapped to thermal comfort categories, predictions reached 80% accuracy, with a macro-averaged precision of 0.81 and recall of 0.80, exhibiting the highest performance for neutral and warm conditions while performing less accurately for cool discomfort. These results suggest that standard temperature and humidity sensors, combined with basic contextual information and individual activity profiles, could support reliable PMV-based thermal comfort assessment, advancing scalable, sensor-light comfort monitoring for energy-efficient, sustainable buildings. Full article

The safety of non-food products is embedded in the United Nations 2030 Agenda for Sustainable Development and the European Union (EU) framework, supporting health protection, responsible production and consumption, and market surveillance. The EU Rapid Alert System for dangerous non-food products, known as Safety Gate (formerly RAPEX), was established in 2005 to facilitate the exchange of information on products posing risks within the internal market. The aim of this study was to present the interdependencies reported in the Safety Gate system/RAPEX in 2005–2025, considering: product category, type of risk, country of origin, notifying country and year, as well as measures taken. The VOSviewer 1.6.20 and Statistica 13.3 were used. The results highlighted the following problems: toys from China with chemical, choking and injury risks; electrical appliances also from China with electric shock hazards; motor vehicles from Germany with injury risks; cosmetics from Italy with chemical and microbiological risks; and clothing from Turkey with suffocation risks. Reporting is expected to continue under existing regulatory frameworks, although changing the name of the system from RAPEX to “Safety Gate” may reduce its recognition. The findings highlight the need for targeted enforcement, improved risk profiling by product category and origin, and ongoing monitoring of emerging safety risks. Full article

The fashion industry generates a major environmental impact, requiring integrated sustainable approaches. This study integrates six thematic axes—sustainability, modular design, natural materials, eco-friendly dyeing, multidimensional comfort and consumer perception, and radial composition—into an integrative framework for sustainable design. The mixed-methods methodology comprises four stages: (I) a quantitative stage (questionnaire, n = 150); (II) an experimental stage (testing of comfort characteristics of linen fabrics according to ISO standards, and indigo dyeing through three techniques: uniform, tie-dye, and shibori); (III) a digital design stage in CLO3D and physical fabrication of the prototype; (IV) a prototype testing and validation stage (panel, n = 20). The prototype provides functional adaptability through 8 design configurations, versatility through reversibility, and aesthetic diversity through the radial composition, yielding 16 distinct wearing modes within a single product. Panel evaluation confirms high prototype acceptance (M = 4.81–4.95), and physical interaction with the prototype significantly increases purchase intention compared with conceptual evaluation (M_pre = 3.54; M_post = 4.60; d = 2.04; p < 0.001). The contribution validates a framework that integrates six dimensions of sustainable fashion into a coherent clothing design model, demonstrating design’s role as a practical instrument in the sustainability transition, with applied implications for designers and researchers. Full article

Shopping mobility accounts for a significant share of total travel, while the growth of e-commerce is reshaping consumer purchasing behaviour and retail dynamics. Comprehending how territorial and sociodemographic factors shape the choice between physical and digital retail channels is therefore a key issue for transport planning and sustainable urban mobility. In this context, it is important to understand how accessibility to different classes of retailers is configured and how it can impact purchasing choices. Through a discrete choice analysis, this study examines the sociodemographic and territorial determinants of purchasing behaviour, focusing on the clothing market. Four purchase alternatives are considered: medium-sized and small urban retail stores, shopping malls, online purchasing, and no purchase. This multi-alternative framework enables the direct estimation of substitution patterns not only between physical and digital retail, but also between distinct forms of physical retail. Data were collected through a survey conducted in Southern Italy, providing empirical evidence from a territorial setting that is structurally underrepresented in the existing literature. A multinomial logit model and a two-level hierarchical logit model incorporating pedestrian accessibility—measured as walking time from residence to the nearest clothing store—alongside sociodemographic and territorial attributes were calibrated to analyse alternative choice behaviour. The calibrated models show interesting results, highlighting the role of pedestrian accessibility in the choice of clothing stores in city centres. Age, income, and territorial variables further differentiate channel preferences across population segments. The findings offer relevant implications for policymakers, governance managers, urban planners, and researchers concerned with retail location, sustainable accessibility, and consumer behaviour. These insights are highly valuable for developing planning that addresses the United Nations 2030 Agenda, particularly Sustainable Development Goal 11. Full article

The study of sobriety in fashion can be understood as a form of spiritual exercise within a Christian ecological framework. This article argues that sobriety, understood as a virtue that shapes desire and moderates consumption, offers a theological response to the environmental and social consequences of contemporary fashion. Drawing on biblical sources, patristic and medieval theology, and early modern reflections, it traces the evolution of sobriety from a principle of bodily moderation to a broader philosophy of life. Through a theological analysis of fashion consumption, the article shows how sobriety can function as an ethical and spiritual practice capable of resisting hyperconsumerism and fostering ecological responsibility. The shift from modesty to sobriety thus provides a renewed framework for linking Christian virtue ethics, fashion consumption, and care for the planet. Full article