Designclo: A Smart Recommender System for Personalized Clothing

Abstract: The clothing industry is undergoing a significant transformation driven by the integration of Artificial Intelligence (AI) and emerging digital technologies. Traditional manual processes in clothing design are often time-consuming and restrictive, prompting the development of innovative solutions that enhance creativity and efficiency. To address this gap, the proponents introduce DesignClo, a mobile-based application that leverages a smart recommender system to deliver personalized clothing designs. The system integrates AI-Powered Design suggestions and a wide variety of motifs, enabling users to refine ideas and access trend-driven insights. Complemented by three-dimensional (3D) visualization technology, the platform allows users to preview their creations through life-like mockups, bridging the gap between concept and reality. Built using Tauri and Rust, and developed under the Agile Methodology, the application ensures adaptability, performance, and user-centered design. This inclusivity underscores the application’s broader societal value, offering opportunities for aspiring designers, professionals, and customers regardless of technological limitations. DesignClo uniquely features a virtual try-on so that the user will be able to observe their personalized clothing piece on how it would like when worn. This feature not only allow users to be able to visualize their design in a real-life setting, but it also enables them sync their own customization tailored to their preferences. Overall, DesignClo represents a breakthrough in personalized clothing production, serving as both a creative tool and an industry-aligned platform for clothing and printing businesses. By merging AI-driven recommendations, intuitive design customization, and offline usability, the system provides a sustainable and future-ready approach to enhancing user participation and shaping the evolution of the clothing industry.

Agile Methodology, Artificial Intelligence, Recommender System, Rust, Tauri, Three-Dimensional Technology, Virtual Try-On

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