Aeye: Real-time age, gender and emotion detection in browser

This paper presents Aeye, a lightweight, browser-based application capable of real-time detection of human age, gender and emotional state using artificial intelligence. Unlike many existing AI systems, Aeye performs all computation on the client side, preserving user privacy and enabling full offline functionality. The application utilizes face-api.js and Tiny Face Detector models, achieving fast and efficient performance even on low-resource devices. Its modular design supports dynamic interface controls and responsive operation across platforms. The scientific contribution lies in the integration of asynchronous model loading, real-time GPU-accelerated inference using TensorFlow.js, and deployment as a progressive web app (PWA). These innovations make Aeye suitable for educational, experimental, and field use cases where connectivity and infrastructure are limited. The paper outlines the system architecture, implementation, and evaluation results, and discusses potential extensions such as multi-face detection and integration with emotion-driven user interfaces.