A NEW INTELLIGENT DRIVER VIGILANCE SYSTEM DESIGN USING TILT SENSORS

Ali Zuhair Ghazi Zahid; Karrar Shakir Muttair; Oras Ahmed Shareef; Abbas Ali Diwan; Hazeem Baqir Taher; Raed Hameed Chyad Alfilh; Ahmed Mahmood Farhan; Mahmood Farhan Mosleh; Faiz Arith

doi:10.30572/2018/KJE/160103

Authors

Ali Zuhair Ghazi Zahid Nanotechnology and Advanced Materials Research Unit, Faculty of Engineering, University of Kufa, Najaf, Iraq
Karrar Shakir Muttair Nanotechnology and Advanced Materials Research Unit, Faculty of Engineering, University of Kufa, Najaf, Iraq
Oras Ahmed Shareef Department of Computer Engineering Techniques, Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq
Abbas Ali Diwan Nanotechnology and Advanced Materials Research Unit, Faculty of Engineering, University of Kufa, Najaf, Iraq
Hazeem Baqir Taher Department of Computer Science, College of Education for Pure Sciences, Thi-Qar University, Thi-Qar, Iraq
Raed Hameed Chyad Alfilh Department of Refrigeration and Air Conditioning Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq
Ahmed Mahmood Farhan Department of Medical Instrumentation Engineering, Engineering Technical College, Al-bayan University, Baghdad, Iraq
Mahmood Farhan Mosleh Department of Computer Engineering Techniques, Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq
Faiz Arith Faculty of Electronics and Computer Technology and Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Durian Tunggal, Malaysia

DOI:

https://doi.org/10.30572/2018/KJE/160103

Keywords:

Raspberry Pi, Tilt Sensor, Tilt Detection Techniques, NHTSA, USB Web Camera, Mini Piezo Buzzer, SD Card, Angles Tilt Algorithms, Driver Vigilance System

Abstract

A significant number of causes for people killed by automobile accidents on both public and interior roads are the driver's failure to pay attention to the roadway, as well as other factors such as tiredness, sleep during driving, using the phone, or even the driver being intoxicated, etc. This work aims to identify sleepy status, pinpoint the onset of sleep, and alert the driver when their level of alertness drops below a level that does not improve productivity or the vehicle's overall safety protocols to prevent drowsiness-related crashes. In this article, we present a new method for implementing drowsiness detection inexpensively, using a Raspberry Pi as a central processor board that connects all practical measurement components. In addition, the proposed method includes the following activities: tracking the driver's head vibration while driving using tilt sensors. Moreover, a camera was mounted in front of the driver to take photos and record videos of the driver's health. As a result, the results were entirely satisfactory, and if the driver was operating the vehicle while fatigued, the response was 95% reliable and fast.