Pratik Mahadik,
Jagdish Baraskar,
Pritam Pawar,
Adesh Telange,
Nayana Jadhav,
- B.E Scholar, Vishwaniketan’s Institute of Management Entrepreneurship , Engineering Technology (ViMEET), Mumbai University, Khalapur Maharashtra, India
- B.E Scholar, Vishwaniketan’s Institute of Management Entrepreneurship , Engineering Technology (ViMEET), Mumbai University, Khalapur Maharashtra, India
- B.E Scholar, Vishwaniketan’s Institute of Management Entrepreneurship , Engineering Technology (ViMEET), Mumbai University, Khalapur Maharashtra, India
- B.E Scholar, Vishwaniketan’s Institute of Management Entrepreneurship , Engineering Technology (ViMEET), Mumbai University, Khalapur Maharashtra, India
- Professor, Vishwaniketan’s Institute of Management Entrepreneurship , Engineering Technology (ViMEET), Mumbai University, Khalapur Maharashtra, India
Abstract
Autonomous braking systems and driver observation are two important developments in car safety technology that are intended to reduce accidents brought on by tired drivers. An eye blink sensor has been incorporated in the device. The sensors recognize an eye blink automatically once the driver starts the engine. This gadget displays the sensor’s output so that it may be compared to the Arduino. The eye blink sensor gets a signal from the transmission module, causing the buzzer to automatically vibrate, the LED to illuminate, and the car to automatically stop when the value hits the predetermined level.Driver Observation and automatic braking system are technologies designed to make driving safer by addressing the issue of driver fatigue. These systems identify when a motorist is becoming sleepy using a variety of sensors and gadgets.. For example, wearable devices like eye blink sensor and sensors to watch for signs like eye closure, blinking patterns. These systems notify the driver to take a break or wake up by means of sounds, vibrations, or visual alerts when they notice indications of drowsiness. Due to drivers’ fatigue while operating a vehicle, there has been a marked rise in traffic accidents, many of which are fatal. When a driver falls asleep, he loses control and causes an accident.This occurs when a driver is unable to maintain control of their car while traveling at a fast speed on the road. A model that can stop these kinds of mishaps can be produced by this project. This immediate feedback helps prevent accidents that could happen if a driver falls asleep at the wheel Together, these technologies greatly reduce the risk of accidents caused by driver fatigue, making roads safer for everyone. This aims to create a framework to keep the car safe and secure through critical activity.They ensure drivers stay alert and help prevent crashes by taking over certain driving tasks when necessaryThis project can produce a model that can stop these kinds of mishaps. We presented a very straightforward and affordable solution that addresses this problem in order to stop this.
Keywords: Eye blink sensor, Ultrasonic sensor, relays, Arduino, DC motor.
References
[1] Ueno H., Kanda, M. and Tsukino, M. “Development of Drowsiness Detection System”, IEEE Vehicle Navigation and Information Systems Conference Proceedings,(1994), ppA1-3,15-20. [2] Ishaq Azhar Mohammed, “ARTIFICIAL INTELLIGENCE: THE KEY TO SELFDRIVING IDENTITY GOVERNANCE”, International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.4, Issue 4, pp.664-667, November 2016,Available at :http://www.ijcrt.org/papers/IJCRT113 [3] Adamson S, Enright S. Alcohol Gas Detector “Breathalyzer. [4] Wierwille WW. Overview of research on driver drowsiness definition and driver drowsiness detection. InProceedings: International Technical Conference on the Enhanced Safety of Vehicles 1995 (Vol. 1995, pp. 462-468). National Highway Traffic Safety Administration. [5] Doudou M, Bouabdallah A, Berge-Cherfaoui V. Driver drowsiness measurement technologies: Current research, market solutions, and challenges. International Journal of Intelligent Transportation Systems Research. 2020 May;18:297-319. [6] Hemamalini M, Muhilan P. Accident prevention using eye blink sensor. Asia Pacific Journal of Research, year. 2017:84-6. [7] Prabha C, Sunitha R, Anitha R. Automatic vehicle accident detection and messaging system using GSM and GPS modem. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. 2014 Jul 20;3(7):10723-7. [8] Sahayadhas A, Sundaraj K, Murugappan M. Detecting driver drowsiness based on sensors: a review. Sensors. 2012 Dec 7;12(12):16937-53. [9] Dasgupta A, George A, Happy SL, Routray A. A vision-based system for monitoring the loss of attention in automotive drivers. IEEE Transactions on Intelligent Transportation Systems. 2013 Jul 22;14(4):1825-38. [10] Drowsy Driver Sleeping Device and Driver Alert System, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 [6] X. Xie, R. Sudhakar and H. Zhuang, -Real Time Eye Feature Tracking from a Video Image Sequence Using Kalman Filter, IIIEEE Transactions on Systems, Man, and Cybernetics, Vol. 25, No.12, pp. 1568-1577, 1995. [11] Wright J, Yang AY, Ganesh A, Sastry SS, Ma Y. Robust face recognition via sparse representation. IEEE transactions on pattern analysis and machine intelligence. 2008 Apr 3;31(2):210-27.
Journal of Microcontroller Engineering and Applications
Volume | |
Received | May 7, 2024 |
Accepted | May 18, 2024 |
Published | August 14, 2024 |