VISIONGUARD: AN AI-DRIVEN REAL-TIME DRIVER ATTENTION AND DISTRACTION MONITORING SYSTEM USING DEEP LEARNING
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Driver distraction and drowsiness have emerged as leading contributors to road accidents, posing severe threats to public safety and transportation systems worldwide. Traditional monitoring approaches rely on manual supervision or intrusive physiological sensors, which are impractical for continuous, long-term deployment. This paper presents VisionGuard—an AI-driven, non-intrusive, real-time Driver Attention and Distraction Monitoring System built upon deep learning techniques. A real-time in-cabin camera continuously captures the driver's facial features and head movements for behavioral analysis. The system employs the YOLO (You Only Look Once) object detection algorithm for fast and accurate real-time detection of distraction indicators including gaze deviation, head orientation, eye movement, and improper visual focus. Drowsiness is assessed through PERCLOS (Percentage of Eye Closure) and Mouth Aspect Ratio (MAR) metrics. Upon detecting distraction or fatigue, the system generates immediate audio and visual alerts to restore driver attention. Experimental evaluation demonstrates that the proposed framework achieves robust detection performance across diverse lighting and driving conditions without requiring wearable sensors, making it a practical and scalable solution for intelligent transportation safety systems.
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H, I., S, I. N., K, A. A. & N, K. (2026). Visionguard: an AI-Driven Real-Time Driver Attention and Distraction Monitoring System using Deep Learning. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.452
H, Ismail, et al.. "Visionguard: an AI-Driven Real-Time Driver Attention and Distraction Monitoring System using Deep Learning." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.452.
H, Ismail,Imran S,Arafath K, and Kishanthan N. "Visionguard: an AI-Driven Real-Time Driver Attention and Distraction Monitoring System using Deep Learning." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.452.
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