An AI-driven smart mirror application for social event-based fashion recommendation and facial skin health analysis

Abstract

The rapid development of Artificial Intelligence (AI) has opened the doors for many innovative applications in everyday use. Among them, a smart mirror is a conventional mirror with integrated features to provide real-time personalized recommendations and health advice. Modern lifestyles often prevent individuals from prioritizing skincare, outfit selection, or day-to-day planning. This paper proposes AI integrated smart mirror system to address these past difficulties. It consists of face verification for user authentication, skin health analysis, social event-based fashion recommendation system, displaying calendar events and weather updates with a proposed hardware device. The skin health analysis module has acne detection feature with localizing acne within “danger triangle” of the face, an important clinical aspect. After evaluating and comparing multiple stateof-the-art models, the most effective models were selected for the application. The system achieves separate performance metrics: 98% accuracy and 24 fps on a Central Processing Unit (CPU) for face verification (MediaPipe & FaceNet), 64% mean Average Precision (mAP) for acne detection (YOLOV8), and 98% mAP for fashion object detection (YOLOV8), demonstrating its suitability for real-time environments. By leveraging these features, the proposed smart mirror system achieves a significant step toward smart computing by seamlessly integrating with digital intelligence.