Artificial Intelligence (AI) and Machine Learning (ML) have been increasingly affecting the fashion industry with real-time capabilities for personalized clothing. Despite fashion ultimately being just self-expression, identity & culture, many considerations, like differences in body shapes, tastes, requirements for the occasion, and continuously evolving trends, complicate the decision-making on what to wear. While personalization systems are more beneficial than one-size-fits-all, many systems still limit their capability for personalization through apps that do not focus on user preference and that are less accurate. This study shows the rapid evolution of a cross-platform mobile application for fashion recommendations, that fused content-based and Collaborative filtering with machine learning techniques to deliver personalized fashion recommendations. The app simplifies the choices about outfitting, reduces the time browsing for clothing, builds user confidence, and provides several options suitable to various user preferences. Firebase and Supabase offer database management and authentication security, while Machine Learning is leveraged to analyze the strong relationships between user and product data in order to provide a recommendation based on user preferences. The development utilized Agile methodologies, incorporating iterative tasks and adjustments guided by user feedback to improve functionality, usability, and precision. Result demonstrates that the application reduces time and browsing in finding outfits and increase user confidence through reliable, and timely suggestions suited to the situation. Moreover, the system showcased inclusivity by putting various styles and real-time trends, thus enabling merchants to connect with a wider audience. In summary, the findings shows that an AI-mobile based fashion recommendation system provides a more user-friendly, personalized, and various clothing selection method. The suggested solution promotes digital fashion technologies by focusing on individuality, diversity, and usability, thereby improving the role of AI in daily self-expression.
Boquiron et al. (Tue,) studied this question.