A Comparability Study on Driver Fatigue Using C#, C++ and Python
Accidents on road are very common
these days. Most of them are caused by driver
fatigueness. Some common causes and symptoms
have been identified. One of the main solution
to detect driver fatigue is by analyzing the facial
features of the drivers. This paper discusses about
the facial features that can be used to detect driver
fatigue. Further examples on existing vehicle
safety technology is also discussed. Primarily, this
work emphasizes on the study of three different
programming languages and its compatibility
which works best to be integrated with the
proposed hardware. Based on the study, the
result is discussed and the suitable programming
language is suggested.
Ji, Q., Zhu, Z., Lan, P., & Zhiwei Zhu Peilin Lan, Q. J. (2004). Real Time Non-intrusive Monitoring and Prediction of Driver Fatigue. IEEE Trans.
Veh.Technol, 53(4), 1052–1068.
Kuamr, N., & Barwar, N. C. (2014). Analysis of Real Time Driver Fatigue Detection Based on Eye and Yawning. International Journal of Computer Science and Information Technologies, 5(6), 7821-7826.
Patrick, Charles (2018). Fatigue, eMedicineHealth.
Denning, Tori (2014, November). The Underestimated Dangers of Driver Fatigue.
National Sleep Foundation (n.d.). Retrieved from
NHTSA. (2015). Drowsy Driving and Automobile
Crashes. National Highway Traffic Safety Administration.
Government of Australia. (2015, September).
Fatigue Road Safety Commission.
Fan, X., Yin, B. C., & Sun, Y. F. (2007). Yawning
detection for monitoring driver fatigue. In
Proceedings of the Sixth International Conference
on Machine Learning and Cybernetics, ICMLC
(Vol. 2, pp. 664–668).
Attention Assist. (2015). Daimler
Response. (n.d.). VW Golf Turan some improvement.
Driver fatigue detection system as standard.
BMW (n.d.) Driving Assistance Package.
Ford (2010), Ford Technology Newsbrief. Driver
Mazda (n.d.), Lane Departure Waning System.
OpenCV. (2014). Cascade Classification.
Hong.K (2015). Object Detection: Face Detection
using Haar Cascade Classifiers
Abdullah, M. H., Raman, K. J., Azman, A.,
Yogarayan, S., Elbendary, H. A. A., Abdullah,
M. F. A., & Ibrahim, S. Z. (2016). Driver Fatigue
Detection (pp. 269–278). Springer Singapore.
Meikeng, Y., Jr, J. K., & Tan, J. (2013). Study:
Women drivers are angrier than men.
Find out root of aggressive driving style,
Government urged. (2013).
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ISSN : 2590-3551, eISSN : 2600-8122
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