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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42254
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The increase in customer preferences towards mainly be spoke fashion leads to the need of applications that would allow customers to easily design and order clothes online. However, as many existing platforms have shown, it is difficult to incorporate design tools that are easy to use, real time previews which are important and recommendations that consider the user preferences appropriately. To fill these voids, this paper presents the âCustom Clothing Design and Ordering Platform with Generative AIâ. Being equipped with sophisticated machine learning and generative AI features, the platform provides users with an innovative environment that allows them creating designs suitable for their needs. These are such as AI-generated design proposals, live visualisations, and an intelligent recommendation system for fabrics and patterns chosen by the user as well as trend prediction. The platform taps into generative AI to improve design and colour choices with design features that support individual body fit and product size. Moreover, sentiment analysis is incorporated in order to analyse the reception of the users and the further design advice. By simplifying the ordering process, and providing some techniques for demand forecasting, it makes the process effective to both the customers and manufacturers. Through the application of an artificial intelligence mechanism, this revolutionary technology alters the customer experience to create a new model for personalized clothing production for independent fashion designers and businesses.
KEYWORDS
Publication Date
3/10/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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