• Vaibhavi Pralhad Doijad
• Amruta Bhagavan Kale
• Sanika Sarjerao Patil
• Sandesh Dipak Kadam
• Mrs.R.R.Gaur

Currently, the most important contributing cause to a traffic collision is a sleepy driver. The goal of the study is to develop a practical method of warning drivers when they are getting weary. Consequently, a reliable mechanism must be created to prevent mishaps. In this planned research, we focus on a drowsy 1alert system that has created using a technique in which the VSP is assessed by an inborn reflex construct using an Eye ratio (EAR) and geometrical attentional distance. Additionally, a face landmark algorithmic programme is applied for accurate eye detection. program is additionally used as correct eye detection. In order to prevent a serious accident, the module alerts the driver and admin person when the driver is showing signs of being asleep.

Image Processing, Deep Neural Network, Drowsy Detection, EAR, MAR

"Driver Drowsiness Detection System Using Deep Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.j723-j728, June-2023, Available :http://www.jetir.org/papers/JETIR2306985.pdf

"Driver Drowsiness Detection System Using Deep Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppj723-j728, June-2023, Available at : http://www.jetir.org/papers/JETIR2306985.pdf