Live Monitoring of the Driver Facial Expression using Image Processing and Based on the Drowsiness
Abstract
The significant
causes of road accidents are occurred due to Drowsiness and Fatigue of drivers.
We aim to reduce the number of accidents due to driver Drowsiness hence will
increase transportation safety. This System will Live Monitor the Driver Facial
Expression using Image Processing and Based on the Drowsiness or frequent
Yawning it will Notify the driver to take a break and if driver do not take a break,
then it will generate an Alert Signal such as Turning on the Music Player,
Turning on Vibration Motor of Driver Seat and turning on Hazard lights which
will indicate other drivers that this driver is feeling drowsy. The entire
system is implemented using Raspberry-Pi.
Country : India
1 Dr. Archek Praveen Kumar
HOD & Professor, Department of Electronics and Communication Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
Rahman, M. Sirshar, A. Khan” Real
Time Drowsiness Detection Using Eye Blink Monitoring” 2015 National Software
Engineering Conference (NSEC 2015).
Facial Features Monitoring for Real
Time Drowsiness Detection by Manu B.N, 2016 12th International Conference on
Innovations in Information Technology (IIT)
https://ieeexplore.ieee.org/document/7880030
IOT Based Real-Time Drowsy Driving
Detection System for the Prevention of Road Accidents by Fabian Parsia George,
Md. Yousuf-Hossian https://ieeexplore.ieee.org/abstract/document/8550026
Rezaee Khosro et al., "Real-time
intelligent alarm system of driver fatigue based on video sequences",
Robotics and Mechatronics (ICRoM) 2013 First RSI/ISM International Conference
on, 2013.
Tawari Ashish, Kuo Hao Chen and Mohan
Manubhai Trivedi, where is the driver looking: Analysis of head eye and iris
for robust gaze zone estimation", Intelligent Transportation Systems
(ITSC) 2014 IEEE 17th International Conference on, 2014.
Eskandarian, A. and A. Mortazavi,
"Evaluation of a smart algorithm for commercial vehicle driver drowsiness
detection" in Intelligent Vehicles Symposium, 2007 IEEE. 2007. IEEE
Kunika Chhaganbhai Patel, Shafiullah
Atiullah Khan, Vijaykumar Nandkumar Patil, “Real-Time Driver Drowsiness
Detection System Based on Visual Information”, International Journal of
Engineering Science and Computing, March 2018.
Quang N., NguyenLe T. Anh ThoToi Vo
VanHui YuNguyen DucThang, “Visual Based Drowsiness Detection Using Facial
Features”, 6th International Conference on the Development of Biomedical
Engineering in Vietnam (BME6) pp 723-727, BME 2017.
