Skip to main content
Log in

A Smart Drowsiness Detection System for Accident Prevention

  • Short Communication
  • Published:
National Academy Science Letters Aims and scope Submit manuscript

Abstract

Driver’s drowsiness is one of the main reasons for road accidents which lead to several fatalities every year. Statistics highlights the necessity of a drowsiness detection system that could possibly alert the co-passengers and driver before an accident would occur. Some automobile manufacturers have implemented drowsiness detection systems in their cars that work based on the vehicle movement, angle of steering wheel and other factors, but these parameters may not be reliable while detecting drowsiness of a driver. Few research papers have published on determining the drowsiness of a driver using electroencephalogram (EEG) sensor technology that detects the brain waves and determines if the person drowsy based on the obtained data. EEG is an optimum way of measuring the active state of a person in real time. In this work, we are adopting this technology along with an eye blink detection to detect the drowsiness and alert the driver.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. Yang JH, Mao ZH, Tijerina L, Pilutti T, Coughlin JF, Feron E (2009) Detection of driver fatigue caused by sleep deprivation. IEEE Trans Syst Man Cybern A Syst Hum 39(4):694–705

    Article  Google Scholar 

  2. Jap BT, Lal S, Fischer P, Bekiaris E (2009) Using EEG spectral components to assess algorithms for detecting fatigue. Expert Syst Appl 36:2352–2359

    Article  Google Scholar 

  3. Ned Hermann: What is the function of the various brainwaves?. https://www.scientificamerican.com/article/what-is-the-function-of-t-1997-12-22/

  4. Li G, Chung W-Y (2015) A context-aware EEG headset system for early detection of driver drowsiness. Sensors 15(8):20873–20893

    Article  ADS  Google Scholar 

  5. Kartsch V, Benatti S, Rossi D, Benini L (2017) A wearable EEG-based drowsiness detection system with blink duration and alpha waves analysis. In: 8th International IEEE EMBS conference on neural engineering, Shanghai, China, May 25–28

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. G. Sangeetha.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kondapaneni, A., Hemanth, C., Sangeetha, R.G. et al. A Smart Drowsiness Detection System for Accident Prevention. Natl. Acad. Sci. Lett. 44, 317–320 (2021). https://doi.org/10.1007/s40009-020-01000-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40009-020-01000-3

Keywords

Navigation