Using MindWave Mobile2 sensor to Detect the Driver's Drowsiness

Authors

  • Tariq A. Alkaar Electrical and Electronic Engineering Department, Faculty of Engineering, Sabratha University, Sabratha, Libya
  • Abdulhamed Abdusslam Essed Electrical and Electronic Engineering Department, Faculty of Engineering, Sabratha University, Sabratha, Libya
  • Sokina Ibrahim Knan Electrical and Computer Engineering Department, School of Applied Science and Engineering, Libyan Academy, Tripoli, Libya

Keywords:

EEG, Drowsiness, Arduino UNO, MindWave Mobile 2

Abstract

One of the primary factors contributing to traffic accidents is sleepiness, which is brought on by exhaustion or overwork, then lowers the activity of brain neurons in the nervous system. Therefore, it is necessary to develop methods to detect drowsiness. There are several methods for detecting drowsiness, including eye closure detection and driving pattern-based detection. This research uses an Electroencephalography EEG by MindWave Mobile 2 sensor to measure brain waves in order to detect drowsiness. The sensor provides information about electrical signals to the brain, then sent to the Arduino UNO board via Bluetooth HC-05 and, when a person falls asleep, activates an alarm. The point at which a person feels drowsy can be identified after experimenting with this gadget in a number of activities, sleep, and sleepiness scenarios.

Dimensions

Published

2024-06-24

How to Cite

Tariq A. Alkaar, Abdulhamed Abdusslam Essed, & Sokina Ibrahim Knan. (2024). Using MindWave Mobile2 sensor to Detect the Driver’s Drowsiness. African Journal of Advanced Pure and Applied Sciences (AJAPAS), 3(2), 199–207. Retrieved from https://aaasjournals.com/index.php/ajapas/article/view/860

Issue

Volume 3, Issue 2, April-June 2024

Section

Articles
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