• Komal Gawali Bharati Vidyapeeth College of Engineering for Women, Pune.
  • Lohar Kirti Bharati Vidyapeeth College of Engineering for Women, Pune.
  • Vanshiv Aishwaraya Bharati Vidyapeeth College of Engineering for Women, Pune.
  • Sonawane Aishwaraya Bharati Vidyapeeth College of Engineering for Women, Pune.
  • Prof. P.D.Kale Bharati Vidyapeeth College of Engineering for Women, Pune.


Fatigue,Thrisholding Drowsiness, Assistance, HaarCascade, Open CV, Blob


Driver fatigue and drowsiness is a main cause of large number of vehicle accidents. Recent report states that 1200 deaths and 76000 injuries caused annually due to drowsiness conditions. Sleepiness is main issue in large number of accidents take placed. Development of a complete system which will help to prevent drowsiness is a major challenge in accident development system. Current technologies used for detecting driver’s fatigue condition uses in physiological signals like heartbeat rate, eye blinking detection and brain activities. But this technique does not have advantages in real world application. Because using electrodes to get signal is very annoying for driver every time and this systems are not cost effective. To overcome all of these problem driver assistance systems is proposed. The purpose of this project is to detect that whether driver is about to fall asleep while driving or not and if driver is in drowsy condition, then give him alert by using alarm or any other device. This will make user alert and will help to prevent accidents during driving.


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K.J. Cho, B. Roy, S. Mascaro, and H.H. Asada,“A Vast DOF Robotic Car Seat Using SMAActuators with a Matrix Drive System, ” Proc. IEEE Robotics and Automation, New Orleans ,L A, USA, Vol.4, 2004, pp.3647-3652.

Ye Sun, Student Member, IEEE, Xiong Yu, Member, IEEE “An Innovative Non-intrusive Driver Assistance System for Vital Signal Monitoring”

Boon-Giin Lee and Wan-Young Chung, Member,IEEE “Driver Alertness Monitoring Using Fusion of Facial Features and Bio-Signals”

J. Faber,“Detection of Different Levels of Vigilance by EEG Pseudo Spectra”, in Neural Network World, 14(3-4), pp. 285-290, 2004.

U.S. NHTSA, “Traffic Safety”, 811172.pdf U.S.CDC, “Mobile Vehicle Safety-Impaired Driving”,http://www.cdc.

Additional Files



How to Cite

Komal Gawali, Lohar Kirti, Vanshiv Aishwaraya, Sonawane Aishwaraya, & Prof. P.D.Kale. (2016). DRIVER FATIGUE DETECTION. International Education and Research Journal (IERJ), 2(3). Retrieved from