Development of Noncontact Train Driver Monitoring System with Bio Signal Processing 


Vol. 43,  No. 12, pp. 2136-2144, Dec.  2018
10.7840/kics.2018.43.12.2136


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  Abstract

To detect extraordinary condition by monitoring consistently the car driver or the train driver can contribute to improve the operational safety. A system that can monitor the driver by receiving a bio-signal with non-contact method such that without using a sensor attached to the driver was developed. And the proess and result of the development is dscribed in this paper. The system detects the driver’s status by recognizing the bionic signal such that the gaze angle and heart beat rate of the driver which are highly related with drowsiness. Various measurement data is used to machine learning for the first stage learning and the learned machine can detect the drowsiness and the gaze angle with decision and classification algorithm. Multi-class classification algorithm was adapted to detect various gaze angle. Besides, coutinuity condition was applied to reduce wrong recognition. Test result represents the decision accuracy over 90% and this show that this monitoringsystem can be applied to the real system.

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  Cite this article

[IEEE Style]

H. Chun, J. Kim, G. Kim, J. Lee, "Development of Noncontact Train Driver Monitoring System with Bio Signal Processing," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 12, pp. 2136-2144, 2018. DOI: 10.7840/kics.2018.43.12.2136.

[ACM Style]

Hye-yeun Chun, Jungtai Kim, Gil-dong Kim, and Jaeho Lee. 2018. Development of Noncontact Train Driver Monitoring System with Bio Signal Processing. The Journal of Korean Institute of Communications and Information Sciences, 43, 12, (2018), 2136-2144. DOI: 10.7840/kics.2018.43.12.2136.

[KICS Style]

Hye-yeun Chun, Jungtai Kim, Gil-dong Kim, Jaeho Lee, "Development of Noncontact Train Driver Monitoring System with Bio Signal Processing," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 12, pp. 2136-2144, 12. 2018. (https://doi.org/10.7840/kics.2018.43.12.2136)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880