AI Based Driver Drowsiness Driver Alert System for Next Generation

Authors

  • R. Shashikiran Department of Electronics and Communiations Engineering, Nagarjuna College of Engineering and Technology, Bangalore, India
  • Yamuna Shivakumar Department of Electronics and Communiations Engineering, Nagarjuna College of Engineering and Technology, Bangalore, India
  • Rajeshwari Hattikatagi Department of Electronics and Communiations Engineering, Nagarjuna College of Engineering and Technology, Bangalore, India
  • Palleti Jaswanthi Department of Electronics and Communiations Engineering, Nagarjuna College of Engineering and Technology, Bangalore, India
  • Yassam charitha Department of Electronics and Communiations Engineering, Nagarjuna College of Engineering and Technology, Bangalore, India

Keywords:

Camera, raspberry pi 3, monitor, alarm, relay

Abstract

Driver drowsiness detection is designed mainly to keep the driver awake while driving to avoid the accident due to sleepiness. The alert signal is generated from embedded device to awake driver from sleepy state. The Pi along with Raspbian camera is used to calculate the drowsiness of the driver in real time. The purpose of this paper way to devise a way to alert drowsy drivers in act of driving. One of the causes of car accident comes from drowsiness of the driver. Therefore, this study attempted to address the issues by creating an experiment in order to calculate the level of drowsiness .A requirement for this paper was the utilization of a Raspberry Pi camera and Raspberry Pi 3 module, which were able to calculate the level of drowsiness in drivers. The frequency of head tilting and blinking of the eyes was used to determine whether or not a driver felt drowsy. With an evaluation on ten volunteers, the accuracy of face and eye detection was up to 99.59 percent.

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Published

2021-06-08

How to Cite

[1]
R. . Shashikiran, Y. Shivakumar, R. Hattikatagi, P. Jaswanthi, and Y. charitha, “AI Based Driver Drowsiness Driver Alert System for Next Generation”, IJRAMT, vol. 2, no. 6, pp. 32–35, Jun. 2021.

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Articles