Drowsiness Warning System Using Artificial Intelligence
Nowadays, driving support systems, such as car
navigation systems, are getting common, and they support drivers in
several aspects. It is important for driving support systems to detect
status of driver's consciousness. Particularly, detecting driver's
drowsiness could prevent drivers from collisions caused by drowsy
driving. In this paper, we discuss the various artificial detection
methods for detecting driver's drowsiness processing technique. This
system is based on facial images analysis for warning the driver of
drowsiness or in attention to prevent traffic accidents.
[1] T. Hamada, T. Ito, K. Adachi, T. Nakano, and S. Yamamoto
(2003),"Detecting method for Driver-s drowsiness applicable to
Individual Features" IEEE proc. Intelligent Transportation Systems, vol.
2, pp.1405-1410.
[2] L. Barr, H. Howrach, S. Popkin and R. J. Carroll (2009) " A review and
evaluation of emerging driver fatigue detection, measures and
technologies", A Report of US department of transportation, Washington
DC, USA.
[3] M. Eriksson and N.P. Papanikolopoulos, (1997), "Eye-tracking for
detection of driver fatigue", IEEE proc. Intelligent Transport System,
Boston, MA, pp. 314-319.
[4] A. Eskandarian, and A. Mortazavi (2007), "Evaluation of a smart
algorithm for commercial vehicle driver drowsiness detection", IEEE
Intelligent Vehicles Symposium (IV'07), Istanbul, Turkey, pp. 553-559.
[5] H. Gu, Y. Zhang, and Qiang Ji, (2005), "Task oriented facial behaviour
recognition with selective sensing," Elsevier Journal of Computer Vision
Image Understate, vol. 100, no.3, pp. 385-415.
[6] KimHon ,Chung(2005),"Electroencephalogram -raphic study of
drowsiness in simulated driving with sleep deprivation", International
Journal of Industrial Ergonomics., vol. 35, no. 4, pp. 307-320.
[7] K. Harimast (2002)"Human Maehinc. Intedae in an Intelligent vehicle"
SAU. vol.56. no.2, pp.4-7.
[8] M. Suzuki, N. Yamamoto, O. Yamamoto, T. Nakano, and S. Yamamoto
(2006) "Measurement of Driver's Consciousness by Image Processing-
A Method for Presuming Driver's Drowsiness by Eye-Blinks coping
with Individual Differences" IEEE International Conference on Systems,
Man, and Cybernetics, Taipei, Taiwan. vol. 2, pp. 2891-2896.
[9] Paul Stephen Rau (2005), "Drowsy drivers detection and warning
system for commercial vehicle drivers: Field proportional test design,
analysis, and progress", Proc. - 19th International Technical Conference
on the Enhanced Safety of Vehicles, Washington, D.C.,
[10] Perez, Claudio A. et al., (2001). "Face and Eye Tracking Algorithm
Based on Digital Image Processing", IEEE System, Man and
Cybernetics 2001 Conference, vol. 2, pp1178-1188.
[11] P. P. Caffier, U. Erdmann, and P. Ullsperger, (2003) "Experimental
evaluation of eye-blink parameters as a Drowsiness measure", Eur.
Journal of Applied Physiology, vol.89, no.3-4, pp.319-325.
[12] S. Singh. and N. P. Fapanikolopaulas (1999), "Monitoring Driver
Fatigue Using Facial Analysis Technologies", IEEE International
conference on the Intelligent Transportation Systems. pp.316-318.
[1] T. Hamada, T. Ito, K. Adachi, T. Nakano, and S. Yamamoto
(2003),"Detecting method for Driver-s drowsiness applicable to
Individual Features" IEEE proc. Intelligent Transportation Systems, vol.
2, pp.1405-1410.
[2] L. Barr, H. Howrach, S. Popkin and R. J. Carroll (2009) " A review and
evaluation of emerging driver fatigue detection, measures and
technologies", A Report of US department of transportation, Washington
DC, USA.
[3] M. Eriksson and N.P. Papanikolopoulos, (1997), "Eye-tracking for
detection of driver fatigue", IEEE proc. Intelligent Transport System,
Boston, MA, pp. 314-319.
[4] A. Eskandarian, and A. Mortazavi (2007), "Evaluation of a smart
algorithm for commercial vehicle driver drowsiness detection", IEEE
Intelligent Vehicles Symposium (IV'07), Istanbul, Turkey, pp. 553-559.
[5] H. Gu, Y. Zhang, and Qiang Ji, (2005), "Task oriented facial behaviour
recognition with selective sensing," Elsevier Journal of Computer Vision
Image Understate, vol. 100, no.3, pp. 385-415.
[6] KimHon ,Chung(2005),"Electroencephalogram -raphic study of
drowsiness in simulated driving with sleep deprivation", International
Journal of Industrial Ergonomics., vol. 35, no. 4, pp. 307-320.
[7] K. Harimast (2002)"Human Maehinc. Intedae in an Intelligent vehicle"
SAU. vol.56. no.2, pp.4-7.
[8] M. Suzuki, N. Yamamoto, O. Yamamoto, T. Nakano, and S. Yamamoto
(2006) "Measurement of Driver's Consciousness by Image Processing-
A Method for Presuming Driver's Drowsiness by Eye-Blinks coping
with Individual Differences" IEEE International Conference on Systems,
Man, and Cybernetics, Taipei, Taiwan. vol. 2, pp. 2891-2896.
[9] Paul Stephen Rau (2005), "Drowsy drivers detection and warning
system for commercial vehicle drivers: Field proportional test design,
analysis, and progress", Proc. - 19th International Technical Conference
on the Enhanced Safety of Vehicles, Washington, D.C.,
[10] Perez, Claudio A. et al., (2001). "Face and Eye Tracking Algorithm
Based on Digital Image Processing", IEEE System, Man and
Cybernetics 2001 Conference, vol. 2, pp1178-1188.
[11] P. P. Caffier, U. Erdmann, and P. Ullsperger, (2003) "Experimental
evaluation of eye-blink parameters as a Drowsiness measure", Eur.
Journal of Applied Physiology, vol.89, no.3-4, pp.319-325.
[12] S. Singh. and N. P. Fapanikolopaulas (1999), "Monitoring Driver
Fatigue Using Facial Analysis Technologies", IEEE International
conference on the Intelligent Transportation Systems. pp.316-318.
@article{"International Journal of Business, Human and Social Sciences:62065", author = "Nidhi Sharma and V. K. Banga", title = "Drowsiness Warning System Using Artificial Intelligence", abstract = "Nowadays, driving support systems, such as car
navigation systems, are getting common, and they support drivers in
several aspects. It is important for driving support systems to detect
status of driver's consciousness. Particularly, detecting driver's
drowsiness could prevent drivers from collisions caused by drowsy
driving. In this paper, we discuss the various artificial detection
methods for detecting driver's drowsiness processing technique. This
system is based on facial images analysis for warning the driver of
drowsiness or in attention to prevent traffic accidents.", keywords = "Neuro-Fuzzy Model, Halstead Model, Walston-FelixModel, Bailey-Basili Model, Doty Model, GA Based Model, GeneticAlgorithm.", volume = "4", number = "7", pages = "1823-3", }
