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1715171 Vol 9 · Issue 9 Download Paper

DriveGuard: Eye Blink Sensor Based Automatic Braking System with Hazard Warning

Gokul Krishnan U Akash S Vivek Remanan Thomas Kurien

Subject area: Science,Engineering and Technology  ·  Area of research: Computer Vision, IoT

DOI: 10.64388/IREV9I9-1715171

Abstract

Road accidents caused by driver fatigue and drowsiness are a major concern, especially during long-distance and night-time driving. Loss of alertness due to sleep can lead to delayed reaction times and severe accidents. To address this problem, this project presents an Eye Blink Sensor Based Automatic Braking System, designed to continuously monitor the driver’s eye movements and take preventive action when drowsiness is detected. The proposed system uses an IR eye blink sensor to sense eye closure patterns. An Arduino microcontroller processes the sensor input and determines the driver’s alertness level. If normal eye movement is detected, the system remains in a safe state. When prolonged eye closure is sensed, the system generates warning alerts using a buzzer and visual indicators. If the drowsy condition persists, the system automatically activates the braking mechanism to slow down or stop the vehicle, thereby preventing potential accidents. An LCD display is used to provide real- time status messages such as normal condition, sleep detection, and sleep confirmation. The system is simple, cost-effective, and reliable, making it suitable for implementation in real-time vehicle safety applications. This project demonstrates an efficient approach to enhancing road safety by reducing accidents caused by driver fatigue and inattentiveness.

References

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[2] Fariya Osmani and Pawan Wawage “Vision Trans- former For Eye State Analysis”, (2024) IEEE — DOI:10.1109/ICISAA62385.2024.10829106.

[3] Munna Naser and Taj Rashid ”Machine Vision Based System with Speed Control”, (2025) IEEE—DOI: 10.1109/ICCE63647.2025.10929942.

[4] Mohamed Hedi Baccour et al.”Camera Based Eye Blink Detection Algorithm”, 2023.

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[6] Ajay Mittal ”Head Movement Based Detection Review”, 2023.

[7] Chanakya Borgohain et al. ”Driver Drowsiness And Adaptive Breaking System”, (2025) IEEE—DOI: 10.1109/GCON65540.2025.11173295.

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[10] World Health Organization, “Global Road Safety Report 2023,” WHO, Geneva, Switzerland.

How to cite this paper

Gokul Krishnan U, Akash S, Vivek Remanan, Thomas Kurien "DriveGuard: Eye Blink Sensor Based Automatic Braking System with Hazard Warning" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 1908-1913 https://doi.org/10.64388/IREV9I9-1715171
Gokul Krishnan U, Akash S, Vivek Remanan, Thomas Kurien "DriveGuard: Eye Blink Sensor Based Automatic Braking System with Hazard Warning" Iconic Research And Engineering Journals, vol. 9, no. 9, Mar. 2026, doi: https://doi.org/10.64388/IREV9I9-1715171
Gokul Krishnan U, Akash S, Vivek Remanan, Thomas Kurien (2026). DriveGuard: Eye Blink Sensor Based Automatic Braking System with Hazard Warning. Iconic Research And Engineering Journals, 9(9). doi: https://doi.org/10.64388/IREV9I9-1715171
Gokul Krishnan U, Akash S, Vivek Remanan, Thomas Kurien "DriveGuard: Eye Blink Sensor Based Automatic Braking System with Hazard Warning" Iconic Research And Engineering Journals, vol. 9, no. 9, Mar. 2026. Crossref, https://doi.org/10.64388/IREV9I9-1715171
@article{1715171,
      author = {Gokul Krishnan U, Akash S, Vivek Remanan, Thomas Kurien},
      title = {DriveGuard: Eye Blink Sensor Based Automatic Braking System with Hazard Warning},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {1908-1913},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715171.pdf},
      abstract = {Road accidents caused by driver fatigue and drowsiness are a major concern, especially during long-distance and night-time driving. Loss of alertness due to sleep can lead to delayed reaction times and severe accidents. To address this problem, this project presents an Eye Blink Sensor Based Automatic Braking System, designed to continuously monitor the driver’s eye movements and take preventive action when drowsiness is detected. The proposed system uses an IR eye blink sensor to sense eye closure patterns. An Arduino microcontroller processes the sensor input and determines the driver’s alertness level. If normal eye movement is detected, the system remains in a safe state. When prolonged eye closure is sensed, the system generates warning alerts using a buzzer and visual indicators. If the drowsy condition persists, the system automatically activates the braking mechanism to slow down or stop the vehicle, thereby preventing potential accidents. An LCD display is used to provide real- time status messages such as normal condition, sleep detection, and sleep confirmation. The system is simple, cost-effective, and reliable, making it suitable for implementation in real-time vehicle safety applications. This project demonstrates an efficient approach to enhancing road safety by reducing accidents caused by driver fatigue and inattentiveness.},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715171}
  }