Digital Wardrobe Organizer: A Smart AI-Based Solution for Personal Wardrobe Management

In modern daily life, individuals face a significant cognitive burden from an accumulation of minor decisions, a phenomenon known as decision fatigue. The recurring, mundane task of selecting an outfit is a primary contributor to this mental overload, leading to stress, anxiety, and inefficient use of cognitive resources. This paper presents the design and development of the “Digital Wardrobe Organizer,” a smart mobile application engineered to mitigate this cognitive load. The proposed system leverages a cross-platform Flutter-based front-end, providing a fluid user interface for both Android and iOS. The backend is powered by Firebase, utilizing its Backend-as-a-Service (BaaS) model for scalable user authentication, cloud storage, and a real-time NoSQL database. The core intelligence of the system resides in an on-device TensorFlow Lite (TFLite) object recognition model, which automates the wardrobe digitization process by identifying and tagging garment attributes. This populated inventory is then used by a context-aware recommendation engine. The engine employs a content-based filtering algorithm, enhanced by real-time data from external weather APIs, to suggest appropriate and stylistically coherent outfits. The expected outcomes of this project are a significant reduction in users’ daily decision fatigue and the promotion of sustainable fashion practices by maximizing the utilization of their existing wardrobe.