STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Microcontroller Engineering and Applications

IoT-based Smart Drowsiness Detection and Alert System

  1. Abubakar .
  2. Samra Shaheen
  3. Hareem Hayee
  4. Rimsha Sarwar
  5. Sawera Shehzadi
  6. Amna Tariq
  7. Muhammad Hamza Zulfiqar

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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