International Journal of Research Studies in Educational Technology
Divine Word College of San Jose Special Issue
Volume 8, Issue Number 2
Available Online: 15 July 2024
Author/s:
Kline, George Harrison B.*
Divine Word College of San Jose, Philippines (georgekline07@gmail.com)
Bolivar, Francis Ivan B.
Nacar, Caeyla Nhina T.
Domingo, Azilanna Dann D.
Baldonado, Ariane Gwyneth G.
Sunga, Ashlhey Micaella S.
Bautista, Josephine N.
Limos-Galay, Jenny A.
Abstract:
This applied experimental research focuses on developing a drowsiness and alcohol detection system using Arduino Uno technology. This device is intended for integration into glasses to be used by drivers to enhance road safety by combining infrared sensors for detecting drowsiness based on the duration of the user’s blink, an MQ3 module for detecting alcohol in the breath, and an SMS system for emergency contact, all included in a single device. Descriptive statistical methods evaluate the effectiveness of the drowsiness detection system in terms of accuracy and eye structure, and the alcohol detection system is evaluated in terms of consistency and sensitivity regarding the amount of alcohol present in the user’s breath. For the drowsiness detection system, accuracy is assessed by its ability to detect eyelid closure for more than three seconds using an infrared sensor, with consistent recorded performance regardless of eye structure. Concerning the alcohol detection system, consistency is evaluated over 30 tests, with slightly varying success rates depending on alcohol consumption levels (10 mL, 20 mL, and 30 mL), demonstrating good accuracy across all trials. Statistical analyses, including t-tests and ANOVA, reveal no significant differences in efficacy based on eye structure or the amount of alcohol. The researchers recommend improving the sensitivity of the Drowsiness Detection System, addressing errors in the Alcohol Detection System by further calibrating the sensitivity of the module, integrating a NEO-6M GPS module for more detailed location information, and improving the design of the product by using lighter variants of the parts used.
Keywords: applied experimental research, IR sensor, MQ3 module, GSM module, alcohol detection, drowsiness detection
DOI: https://doi.org/10.5861/ijrset.2024.8010
Cite this article:
Kline, G. H. B., Bolivar, F. I. B., Nacar, C. N. T., Domingo, A. D. D., Baldonado, A. G. G., Sunga, A. M. S., Bautista, J. N., & Limos-Galay, J. A. (2024). Drowsiness and alcohol detection system using Arduino Uno. International Journal of Research Studies in Educational Technology, 8(2), 45-52. https://doi.org/10.5861/ijrset.2024.8010
* Corresponding Author