Real-Time Drowsiness Detection and Accident Prevention for Drivers

Authors

  • Vijayakumar
  • Masood Alam
  • Pavithra S. K.
  • G. D. Naidu
  • R. Poomurugan

Keywords:

Accidents, Arduino Uno 328P, Buzzer, Global Positioning System (GPS), Global System for Mobile Communications (GSM), Real-time drowsiness detection

Abstract

In modern times, the demands of busy schedules make it challenging always to stay alert. Imagine a scenario where a person, exhausted from the day's challenges, is driving from one place to another. The person's feet are on the pedal, and their hands are on the wheel. Still, gradually, they become sleepy due to tiredness that causes their eyelids to close and their eyesight to blur-driving. At the same time, intoxicated can have dangerous repercussions, such as collisions and possibly fatalities. This situation is alarmingly common, highlighting the importance of addressing this problem. This paper presents a "Real-Time Drowsiness Detection and Accident Prevention System for Drivers." This device warns drivers when they nod off while operating a vehicle, averting collisions and maybe saving lives. Late-night drivers and long-distance travellers will find it very helpful. When the driver feels sleepy and falls asleep, an eye blink sensor detects this, triggering a buzzer to emit intermittent beeps and causing the vehicle's speed to decrease gradually. An accelerometer recognizes severe accidents by receiving signals. A vibration sensor picks up the signal during an accident or rollover and relays it to a controller. Via the microcontroller, the GSM module notifies the driver's close contact of an alert. The location is then traced using GPS, and necessary actions are taken after confirming the location. If no severe injuries are detected during the accident, unnecessary delays for the rescue team are avoided. This system detects accidents through speed control and message notifications, ensuring timely intervention and enhancing overall safety.

Published

2024-08-05

How to Cite

Vijayakumar, Masood Alam, Pavithra S. K., G. D. Naidu, & R. Poomurugan. (2024). Real-Time Drowsiness Detection and Accident Prevention for Drivers. Recent Trends in Semiconductor and Sensor Technology, 27–38. Retrieved from https://matjournals.net/engineering/index.php/RTSST/article/view/779