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Driver Fatigue Monitoring Using EEG Signal and Gas Seepage Detection

R. Sharmila1 , Gnanavel G.2 , Sharmila R.3

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-4 , Page no. 229-332, Apr-2014

Online published on Apr 30, 2014

Copyright © R. Sharmila, Gnanavel G., Sharmila R. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: R. Sharmila, Gnanavel G., Sharmila R., “Driver Fatigue Monitoring Using EEG Signal and Gas Seepage Detection,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.229-332, 2014.

MLA Style Citation: R. Sharmila, Gnanavel G., Sharmila R. "Driver Fatigue Monitoring Using EEG Signal and Gas Seepage Detection." International Journal of Computer Sciences and Engineering 2.4 (2014): 229-332.

APA Style Citation: R. Sharmila, Gnanavel G., Sharmila R., (2014). Driver Fatigue Monitoring Using EEG Signal and Gas Seepage Detection. International Journal of Computer Sciences and Engineering, 2(4), 229-332.

BibTex Style Citation:
@article{Sharmila_2014,
author = {R. Sharmila, Gnanavel G., Sharmila R.},
title = {Driver Fatigue Monitoring Using EEG Signal and Gas Seepage Detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2014},
volume = {2},
Issue = {4},
month = {4},
year = {2014},
issn = {2347-2693},
pages = {229-332},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=145},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=145
TI - Driver Fatigue Monitoring Using EEG Signal and Gas Seepage Detection
T2 - International Journal of Computer Sciences and Engineering
AU - R. Sharmila, Gnanavel G., Sharmila R.
PY - 2014
DA - 2014/04/30
PB - IJCSE, Indore, INDIA
SP - 229-332
IS - 4
VL - 2
SN - 2347-2693
ER -

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Abstract

Statistically about 50percent of road accident is due to the driver drowsiness. In this paper, we describe a real time online protocol that controls the vehicle depends on the driver fatigue level. A direct technique is to analyse the EEG (Electroencephalography) signal. An electrode is placed in driver scalp and acquired the EEG signal of driver at every moment, for feature extraction the FFT (Fast Fourier Transform) is used. Then, the feature extracted EEG signal is given to the microcontroller. It can detect the various threshold level of the driver fatigue, then compare and depends upon the driver fatigue level it can control the speed of the vehicle at certain limit. The gas sensor is used to detect the ac gas leakage ,depend on the sensing signal the microcontroller open a car window automatically, in order to reduce the Freon ac gas it mixed with the co2 gas.

Key-Words / Index Term

EEG, EOG, EMG, ECG, FFT, System Architecture

References

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