Driver Fatigue Detection Using Deep Learning Algorithm

Authors

  • H. R. Manjesh Student, Department of Electronics and Communication Engineering, East West Institute of Technology, Bangalore, India
  • B. S. Pavan Kumar Student, Department of Electronics and Communication Engineering, East West Institute of Technology, Bangalore, India
  • G. Vinay Student, Department of Electronics and Communication Engineering, East West Institute of Technology, Bangalore, India
  • N. Vinay Student, Department of Electronics and Communication Engineering, East West Institute of Technology, Bangalore, India
  • M. Anand Professor, Department of Electronics and Communication Engineering, East West Institute of Technology, Bangalore, India

Keywords:

Machine Learning, road safety, Open CV, image processing, Dlib library, Raspberry Pi, WiFi module

Abstract

Recently, machine gaining expertise of strategies have been used to predict a driver's circumstance in order to grant records that will decorate road safety. A driver's circumstance can be estimated through a driver's facial expressions and riding behaviors. Recent developments in video processing the usage of laptop computer analyzing have enabled snap shots acquired from cam-eras to be analyzed with immoderate accuracy. In this proposed system, an approach for extracting certain factors of the eyes and the mouth using Open CV and Dlib library. It offers an alarm when drowsiness and accident occur. An alert will be acquired to the licensed person through the WiFi module linked to the raspberry-pi, the automobile will be stopped.

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Published

30-05-2022

Issue

Vol. 5 No. 5 (2022)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
H. R. Manjesh, B. S. P. Kumar, G. Vinay, N. Vinay, and M. Anand, “Driver Fatigue Detection Using Deep Learning Algorithm”, IJRESM, vol. 5, no. 5, pp. 216–219, May 2022, Accessed: Oct. 30, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/2098