Real-Time AIoT-Based Fatigue Detection System for Enhancing Worker Well-Being and Learning Efficiency

In today's fast-paced work environments, fatigue among workers can decrease productivity and health. To address this, we developed a real-time fatigue detection system using Artificial Intelligence of Things (AIoT). It integrates sensors—including cameras, simulated physiological sensors, environmental monitors, and logs—to assess workers' cognitive and physical states. Key indicators such as eye aspect ratio (EAR), head pose, and behaviors are extracted. A weighted fusion algorithm combines these to generate a fatigue score, triggering alerts when thresholds are exceeded. This non-intrusive system enables timely interventions, promoting well-being and productivity. Achieving 86% accuracy, it effectively monitors fatigue via vision, physiological, and behavioral data, offering personalized feedback. Ultimately, this AIoT solution shows great promise for improving worker health and efficiency.