Authors:
Md. Ashraf Shubana khan,vagdevi,Vasudha,santoshilaxmi,DOI NO:
https://doi.org/10.26782/jmcms.2019.08.00034Keywords:
Raspberry Pi,Open Cv,Camera,python IDLE,Abstract
This venture manages the immediate method for estimating driver weakness is estimating the condition of the driver for example sluggishness. So it is imperative to recognize the laziness of the driver to spare life and property. This undertaking is pointed towards building up a model of tiredness identification framework. This framework is a constant framework which catches picture consistently and measures the condition of the eye as indicated by the predetermined calculation and gives cautioning whenever required. . For executing this framework a few OpenCv libraries are utilized including Haar-course. The whole framework is actualized utilizing Raspberry-Pi.Refference:
I. Akira Kuramori, Noritaka Koguchi, “Evaluation of Effects of Drivability on
Driver Workload by Using Electromyogram,”
2004.
III. Erez Dagan, Ofer Mano, Gideon P. Stein, et al, “Forward Collision Warning
with a Single Camera,” Proc. Intelligent Vehicles Symposium, pp. 37- 42, 2004.
IV. L.M. Bergasa, J. Nuevo, M.A. Sotalo, and M. Vazquez, “Real-time system for
monitoring driver vigilance,” Proc. IEEE Intelligent Vehicle Symposium, pp. 78-
83, 2004.
V. Lal, S. K. L., Craig, et al,“Development of an Algorithm for an EEG-based
Driver Fatigue Countermeasure,” Journal of Safety Research, vol. 34, pp. 321-
328, 2003.
VI. Luis M. Bergasa, Jesús Nuevo, “Real- Time System for Monitoring Driver
Vigilance,” IEEE Trans. Intelligent Transportation Systems, vol. 7, no. 1, pp.
63-77, 2006.
VII. Nikolaos P, “Vision-based Detection of Driver Fatigue,” Proc. IEEE
Internetional Conference on Intelligent Transportation, 2000.
VIII. Qiong Wang, Jingyu Yang, Mingwu Ren, and Yujie Zheng, “Driver Fatigue
Detection: A Survey,” Proc. Of the 6th World Congress on Intelligent Control
and Automation, pp. 8587- 8591, 2006.
IX. Royal D, “Volume I – Findings report; national survey on distracted and driving
attitudes and behaviours, 2002,” The Gallup Organization, Washington, D.C.,
Tech. Rep., DOT HS 809 566, 2003.
X. Wen-Bing Horng, Chih-Yuan Chen, Yi Chang, et al, “Driver Fatigue Detection
Based on Eye Tracking and Dynamic Template Matching,” Proc. of the 2004
IEEE International Conference on Networking, Sensing & Control, pp. 7-12,
2004
XI. Yoshihiro Takei, and Yoshimi Furukawa, “Estimate of driver’s fatigue through
steering motion,” Proc. IEEE International Conference on Systems, Man and
Cybernetics, vol. 2, pp. 1765-1770, 2005.