IoT-based Smart Drowsiness Detection and Alert System

Authors

  • Abubakar . Student, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan.
  • Samra Shaheen Student, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan.
  • Hareem Hayee Student, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan.
  • Rimsha Sarwar Teaching Assistant, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan.
  • Sawera Shehzadi Teaching Assistant, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan.
  • Amna Tariq Teaching Assistant, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan.
  • Muhammad Hamza Zulfiqar Lecturer, Department of Biomedical Engineering, Narowal Campus, University of Engineering and Technology, Lahore 54890, Pakistan

DOI:

https://doi.org/10.37591/jomea.v10i2.7629

Keywords:

Drowsiness, IOT, microcontroller, accidents, drivers

Abstract

Drowsiness detection systems are necessary in the current era, as drowsy driving contributes to about 20% of all traffic accidents. Approximately 50,000 people have accidents due to drowsy driving annually. Because driving when tired is dangerous, new strategies must be devised to mitigate the impact. Our system is a microcontroller-based system for protecting drivers from unsafe driving based on the physiological parameter of eye blinking. The proposed system detects the sleepy state of the driver using an IR sensor and delivers a WhatsApp message to the emergency contacts provided by the driver. The system is portable and can accurately detect whether the driver is dizzy. The physiological parameter-based system can be used to prevent many accidents.

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Published

2024-03-11

Issue

Vol. 10 No. 2 (2023)

Section

Research Articles