• Preetesh K S
• Manojkumar Mallesh Sagar
• Vishal Hallur
• Goutham
• Smitha.M

Driver fatigue is a leading global cause of road accidents, with serious injuries and fatalities often as a result. In order to improve road safety, this project suggests an Automatic Braking System coupled with Drowsiness Detection. The system continuously checks for the driver's alertness based on real-time video analysis and facial features, including eye blink rate, duration of eyelid closure, and head position. Sophisticated computer vision methods, in association with machine learning principles, are utilized to correctly identify indicators of drowsiness. If it identifies drowsy action, the system issues a warning signal to the driver. In case the driver does not respond in a pre-specified period of time, the system automatically engages the braking system of the vehicle in order to avoid the possible accident. This smart safety solution is specifically valuable for truck drivers who work long hours on the road and can significantly cut the risk of collision from driving while tired. The application displays a realistic and effective way to incorporate human behavior monitoring into motor vehicle control systems to advance intelligent and safe transport.

AUTOMATIC BRAKING USING DROWSINESS DETECTION SYSTEM

"AUTOMATIC BRAKING USING DROWSINESS DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.565-569, July-2025, Available :http://www.jetir.org/papers/JETIRGX06109.pdf

"AUTOMATIC BRAKING USING DROWSINESS DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp565-569, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06109.pdf