Abstract :

Road Accidents Caused By Fatigue And Delayed Emergency Response Continue To Be Global Safety Problems. In Order To Increase Road Safety, This Study Presents A Real-time Driver Drowsiness And Accident Warning System That Makes Use Of Computer Vision And Sensor-based Monitoring. The Driver S Face Is Captured By A Dashboard-mounted Camera, And Yawning And Blinking Are Signs Of Fatigue. A Pretrained Algorithm Collects Facial Landmark Points And Calculates The Eye Aspect Ratio (EAR) And Mouth Aspect Ratio (MAR) To Identify Prolonged Eye Closure And Excessive Yawning. Instant Auditory Indications For Fatigue Are Sent To Drivers. Additionally, An Accelerometer-based Module Monitors Sudden Crashes Or Unusual Vehicle Motions To Identify Collisions. Following An Accident, The System Instantly Notifies Emergency Contacts Via IoT Of The Vehicle S Location. The Proposed Technology Is Feasible In Intelligent Transportation Systems Because To Its Affordable, Non-invasive, Real-time Preventative Drowsiness Detection And Prompt Post-accident Response.

Published:

20-4-1-2026

Issue:

Vol. 26 No. 4-1 (2026)

Page Nos:

621-626

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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