Advertisement

Sleep Detection and Alert System for Automobiles

  • T. BabuEmail author
  • S. Ashwin
  • Mukul Naidu
  • C. Muthukumaaran
  • C. Ravi Raghavan
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

Driver sleep detection is a car safety technology which helps to prevent accidents when the driver gets drowsy. Various studies have suggested that around 20% of road accidents are fatigue related. A sleep alarm is used in a vehicle for detecting the condition indicative of the onset of sleepiness of a driver and for alerting the driver. An eye blink sensor is used to keep track of the driver’s eyelid motion. If the predefined safety conditions are not met, then the driver is alerted by producing an alarming sound from the inbuilt car speakers primarily. Secondly, a vibrating device is incorporated within the driver’s seat which activates when the conditions are not satisfied. Taking into account of the worst case scenario, that is, if the driver does not respond to any of these alarms then, using the proximity sensors, the obstacles around the vehicle is detected, and the brakes are automatically applied gradually.

Keywords

Sleep detection Eye blink Drowsy Driver Eyelid 

References

  1. 1.
    Kusuma Kumari BM (2014) A real time driver drowsiness detection system. Int J Comput Appl 32–34Google Scholar
  2. 2.
    Choudhary P, Sharma R, Singh G, Das S (2016) A survey paper on drowsiness detection & alarm system for drivers. Int Res J Eng Technol 1433–1437Google Scholar
  3. 3.
    Bhavya B, Alice Josephine R (2013) Intel-eye: an innovative system for accident detection (a two–way approach in eye gaze analysis). Int J Comput Commun Eng 2(2):189–193Google Scholar
  4. 4.
    Sontakke KM (2015) Efficient driver fatigue detection and alerting system. Int J Sci Res Publ 5(7):1–4Google Scholar
  5. 5.
    Bergasa LM (2006) Real time system for monitoring driver vigilance, IEEE Trans Intell Transp Syst 7(1):63–77CrossRefGoogle Scholar
  6. 6.
    Ghimire D, Jeong S, Yoon S, Park S, Choi J (2015) Real-time sleepiness detection for driver state monitoring system. Adv Sci Technol Lett 120:1–8Google Scholar
  7. 7.
    Victoreia G, Yazhini D, Parameswari G, Gurumoorthi E, Vijayabarathy G (2014) Driver fatigue monitoring system using eye closure. Int J Mod Eng Res 4(11):26–31Google Scholar
  8. 8.
    Fuletra JD, Bosamiya D (2014) A survey on drier’s drowsiness detection techniques. Int J Recent Innov Trends Comput Commun 1(11):816–819Google Scholar
  9. 9.
    Garg EMVEA (2012) Detection and security system for drowsy driver by using artificial neural network techniques. Int J Appl Sci Adv Technol 1(1):39–43Google Scholar
  10. 10.
    Saini R, Saini V (2014) Driver drowsiness detection system and techniques: a review. Int J Comput Sci Inf Technol 5(3):4245–4249Google Scholar
  11. 11.
    Jayanthi D, Bommy M (2012) Vision-based real-time driver fatigue detection system for efficient vehicle control. Int J Eng Adv Technol 2(1):238–242Google Scholar
  12. 12.
    Malla AM, Davidson PR, Bones PJ, Green R, Jones RD (2010) Automated video based measurement of eye closure for detecting behavioural microsleepGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • T. Babu
    • 1
    Email author
  • S. Ashwin
    • 1
  • Mukul Naidu
    • 1
  • C. Muthukumaaran
    • 1
  • C. Ravi Raghavan
    • 1
  1. 1.Department of Mechanical EngineeringSri Sai Ram Engineering CollegeChennaiIndia

Personalised recommendations