Smart Alarm Driver Assistance as an Early Warning of Drowsiness Drivers Based on Raspberry pi 4 Model B
DOI:
https://doi.org/10.18196/jet.v9i1.25036Keywords:
Drowsinnes Drivers, Raspberry Pi 4 Model B, Eye Aspect Ratio (EAR)Abstract
A decrease in the level of awareness due to drowsiness while driving a motorized vehicle can increase the risk of traffic accidents. Smart Alarm Driver Assistance is a computing system development based on one board Raspberry Pi 4 model B. Digital image processing is intended to automatically recognize signs of drowsiness and provide warnings as early as possible. It is hoped that this research will reduce the number of road accidents caused by drowsy drivers. Raspberry pi is integrated with Raspberry pi camera noir v2 8MP for real-time eye monitoring, audio speaker and I2C OLED 128x64 as a warning output. Shape Predictor_68_Facial landmark model is used to detect Eye Aspect Ratio (EAR) as a parameter of driver drowsiness. The results of the test obtained an average response time of 0.82 seconds for the audio speaker to turn on and the average time the 128x64 OLED I2C lights up 0.90 seconds. This research can prove that the Raspberry Pi 4 model B can be implemented for drowsiness detection and warning. In the future, the protoype can be developed in terms of software and proper tool design.
References
N. R. Adão Martins, S. Annaheim, C. M. Spengler, and R. M. Rossi, “Fatigue Monitoring Through Wearables: A State-of-the-Art Review,” Frontiers in Physiology, vol. 12, no. December, 2021, doi: 10.3389/fphys.2021.790292.
L. Y. Joe, N. N. P. Wang, K. K. Y. Celine, G. L. K. Regan, E. Hanafi, and H. A. Illias, “IoT-Based Smart Driver Monitoring System With Emergency Response Mechanism,” in 2023 Innovations in Power and Advanced Computing Technologies (i-PACT), 2023, pp. 1–6. doi: 10.1109/i-PACT58649.2023.10434713.
R. Aprianto, A. Rokhim, A. Basuki, and S. Sugiyarto, “Pengaruh Karakteristik Pengemudi Dan Pemanfaatan Rest Area Terhadap Kelelahan Pengemudi Studi Kasus Ruas Jalan Tol Pejagan - Solo,” Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety), vol. 8, no. 1, pp. 92–103, 2021, doi: 10.46447/ktj.v8i1.310.
B. Borah and S. Mukherjee, “D-Alarm: An Efficient Driver Drowsiness Detection and Alarming System,” in 2023 6th International Conference on Advances in Science and Technology (ICAST), 2023, pp. 203–208. doi: 10.1109/ICAST59062.2023.10454968.
M. Srivastava, S. A. Idrisi, and T. Gupta, “Driver Drowsiness Detection System with OpenCV & Keras,” in 2021 International Conference on Simulation, Automation & Smart Manufacturing (SASM), 2021, pp. 1–6. doi: 10.1109/SASM51857.2021.9841195.
I. Sulistiyowati, A. R. Sugiarto, and J. Jamaaluddin, “Smart Laboratory Based on Internet of Things in the Faculty of Electrical Engineering, University of Muhammadiyah Sidoarjo,” IOP Conference Series: Materials Science and Engineering, vol. 874, no. 1, 2020, doi: 10.1088/1757-899X/874/1/012007.
S. D. Ayuni, S. Syahrorini, and J. Jamaaluddin, “Lapindo Embankment Security Monitoring System Based on IoT,” Elinvo (Electronics, Informatics, and Vocational Education), vol. 6, no. 1, pp. 40–48, 2021, doi: 10.21831/elinvo.v6i1.40429.
A. Wisaksono and C. A. Ragil, “Design and Development of Parking Motor Parking Information System at Muhammadiyah University, Sidoarjo,” IOP Conference Series: Materials Science and Engineering, vol. 874, no. 1, 2020, doi: 10.1088/1757-899X/874/1/012015.
J. Jamaaluddin, D. Hadidjaja, and H. Arif, “Smoke detection system using MQ2 sensor and Arduino microcontroller: Effective and efficient solution for promoting healthy environments,” AIP Conference Proceedings, vol. 3167, no. 1, p. 40024, Jul. 2024, doi: 10.1063/5.0219708.
S. Sharma et al., “Eye state detection for use in advanced driver assistance systems,” in 2018 International Conference on Recent Trends in Advance Computing (ICRTAC), 2018, pp. 155–161. doi: 10.1109/ICRTAC.2018.8679348.
E. Wood et al., “3D Face Reconstruction with Dense Landmarks BT - Computer Vision – ECCV 2022,” S. Avidan, G. Brostow, M. Cissé, G. M. Farinella, and T. Hassner, Eds., Cham: Springer Nature Switzerland, 2022, pp. 160–177.
J. W. Jolles, “Broad-scale applications of the Raspberry Pi: A review and guide for biologists,” Methods in Ecology and Evolution, vol. 12, no. 9, pp. 1562–1579, 2021, doi: 10.1111/2041-210X.13652.
W. Raslan et al., “Smart Vehicle Safety: AI-Driven Driver Assistance and V2X Communications,” in 2024 International Telecommunications Conference (ITC-Egypt), 2024, pp. 787–792. doi: 10.1109/ITC-Egypt61547.2024.10620463.
K. Adi, C. E. Widodo, A. P. Widodo, and H. N. Aristia, “Monitoring system of drowsiness and lost focused driver using raspberry pi,” Iranian Journal of Public Health, vol. 49, no. 9, pp. 1675–1682, 2020, doi: 10.18502/ijph.v49i9.4084.
N. Kamarudin et al., “Implementation of haar cascade classifier and eye aspect ratio for driver drowsiness detection using raspberry Pi,” Universal Journal of Electrical and Electronic Engineering, vol. 6, no. 5, pp. 67–75, 2019, doi: 10.13189/ujeee.2019.061609.
N. T. Singh, Saurav, N. Pathak, A. Raizada, and S. Shukla, “Real-time Driver Drowsiness Detection System using Cascaded ConvNet Framework,” in 2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS), 2023, pp. 828–833. doi: 10.1109/ICSCSS57650.2023.10169434.
M. Wilkinson, M. C. Bell, and J. I. L. Morison, “A Raspberry Pi-based camera system and image processing procedure for low cost and long-term monitoring of forest canopy dynamics,” Methods in Ecology and Evolution, vol. 12, no. 7, pp. 1316–1322, 2021, doi: 10.1111/2041-210X.13610.
P. K. V Shekar, P. R. Sanil, S. S. Shetty, S. U, and M. Badiger, “Smart Driver Warning and Alert System using Visual Features,” in 2023 7th International Conference on Trends in Electronics and Informatics (ICOEI), 2023, pp. 1603–1607. doi: 10.1109/ICOEI56765.2023.10125651.
B. Sudharsan, S. P. Kumar, and R. Dhakshinamurthy, “AI vision: Smart speaker design and implementation with object detection custom skill and advanced voice interaction capability,” Proceedings of the 11th International Conference on Advanced Computing, ICoAC 2019, no. February, pp. 97–102, 2019, doi: 10.1109/ICoAC48765.2019.247125.
A. Ibbett and Y. Al-Saggaf, “A Distributed Sensor Network (DSN) Employing a Raspberry Pi 3 Model B Microprocessor and a Custom-Designed and Factory-Manufactured Multi-Purpose Printed Circuit Board for Future Sensing Projects †,” Engineering Proceedings, vol. 58, no. 1, 2024, doi: 10.3390/ecsa-10-16187.
Raspberry Pi Ltd, “Raspberry Pi 4 Model B Datasheet,” Raspberry Pi, no. March, p. 12, 2024.
S. Suwarno and K. Kevin, “Analysis of Face Recognition Algorithm: Dlib and OpenCV,” Journal of Informatics and Telecommunication Engineering, vol. 4, no. 1, pp. 173–184, 2020, doi: 10.31289/jite.v4i1.3865.
F. H. Saad et al., “Facial and mandibular landmark tracking with habitual head posture estimation using linear and fiducial markers,” Healthcare Technology Letters, vol. 11, no. 1, pp. 21–30, Feb. 2024, doi: https://doi.org/10.1049/htl2.12076.
C. Dewi, R. C. Chen, X. Jiang, and H. Yu, “Adjusting eye aspect ratio for strong eye blink detection based on facial landmarks,” PeerJ Computer Science, vol. 8, no. 2020, pp. 1–21, 2022, doi: 10.7717/peerj-cs.943.
C. Dewi, R. C. Chen, C. W. Chang, S. H. Wu, X. Jiang, and H. Yu, “Eye Aspect Ratio for Real-Time Drowsiness Detection to Improve Driver Safety,” Electronics (Switzerland), vol. 11, no. 19, 2022, doi: 10.3390/electronics11193183.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Journal of Electrical Technology UMY

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Journal of Electrical Technology UMY. Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Authors should sign Copyright Transfer Agreement when they have approved the final proofs sent by the journal prior the publication. JET UMY strives to ensure that no errors occur in the articles that have been published, both data errors and statements in the article.
JET UMY keep the rights to articles that have been published. Authors are permitted to disseminate published article by sharing the link of JET UMY website. Authors are allowed to use their works for any purposes deemed necessary without written permission from JET UMY with an acknowledgement of initial publication in this journal.
License
All articles published in JET UMY are licensed under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA) license. You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.