An AI-Powered Real-Time Driver Monitoring and Safety Alert System

Driver distraction, fatigue, and unsafe practices are leading contributors to road accidents worldwide. This project introduces an AI-based Real-Time Driver Monitoring and Safety Alert System designed to improve road safety by continuously analysing the driver’s behaviour. The system monitors facial expressions, head movements, eye state, and body posture to identify drowsiness, inattention, mobile phone usage, smoking, and improper seatbelt use. It integrates computer vision techniques, eye aspect ratio (EAR), head pose estimation, and YOLO-based object detection to detect risky behaviours with high accuracy in real-time. Upon detecting unsafe actions, the system issues immediate audio-visual alerts to help drivers stay attentive and avoid potential accidents. The solution is tailored for Indian vehicles and traffic conditions, providing an affordable and adaptable option for both personal and commercial vehicles. Its modular design, low-latency processing, and reliable detection contribute to a safer driving experience and reduced accident rates

Authors

Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-11-02
DOI
https://doi.org/10.48175/ijarsct-29613
Citations
1
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
2.12
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article

An AI-Powered Real-Time Driver Monitoring and Safety Alert System

А. В. Малолетов, M. S., Mr. Shubas S R, Prof. Said S.K. et al.
1 citations
International Journal of Advanced Research in Science Communication and Technology
Sleep and Work-Related Fatigue
2.12
article

An AI-Powered Real-Time Driver Monitoring and Safety Alert System

А. В. Малолетов, M. S., Mr. Shubas S R, Prof. Said S.K., Prof. Kolse C.A.
article en
1 citations

Abstract

Driver distraction, fatigue, and unsafe practices are leading contributors to road accidents worldwide. This project introduces an AI-based Real-Time Driver Monitoring and Safety Alert System designed to improve road safety by continuously analysing the driver’s behaviour. The system monitors facial expressions, head movements, eye state, and body posture to identify drowsiness, inattention, mobile phone usage, smoking, and improper seatbelt use. It integrates computer vision techniques, eye aspect ratio (EAR), head pose estimation, and YOLO-based object detection to detect risky behaviours with high accuracy in real-time. Upon detecting unsafe actions, the system issues immediate audio-visual alerts to help drivers stay attentive and avoid potential accidents. The solution is tailored for Indian vehicles and traffic conditions, providing an affordable and adaptable option for both personal and commercial vehicles. Its modular design, low-latency processing, and reliable detection contribute to a safer driving experience and reduced accident rates

International Journal of Advanced Research in Science Communication and Technology
Openalex Percentile: Top 10%
Sleep and Work-Related Fatigue
2.12
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