International Journal of Advanced Research in Computer and Communication Engineering

Abstract: In today’s fast-paced digital world, individuals face increasing challenges in managing their personal wardrobes efficiently. Despite owning a variety of clothing, many struggle with repetitive outfit choices, underutilization of their wardrobe, and daily decision fatigue. DrobeDex is an AI-powered smart wardrobe and outfit planner Progressive Web Application (PWA) designed to address these challenges by combining user-centric design with intelligent automation. The application allows users to digitize their clothing collections through image uploads, which are then auto-tagged using a custom ResNet50 model. Users can create, manage, and log daily outfits using a drag-and drop interface. DrobeDex is built using React.js to ensure cross platform compatibility and smooth performance on modern web browsers. It employs efficient client-side image preprocessing and integrates a custom ResNet50 model for auto-tagging alongside Generative AI for personalized outfit recommendations. The project follows an Agile development methodology, enabling iterative improvement based on user feedback and real-world testing. Index Terms—AI-powered wardrobe, outfit planning, deep learning, React Native, sustainability, personalized recommendations.

Keywords: AI-powered wardrobe, outfit planning, deep learning, sustainability, personalized recommendations.

Downloads: | DOI: 10.17148/IJARCCE.2025.1412106