Accident Analysis and Prevention Using Advanced Drivers Assistance Systems

Authors

  • Parthibaraj A  Assistant Professor, Department of Electronics and Communication Engineering, K. Ramakrishnan college of Technology, Samayapuram, Trichy, Tamil Nadu, India
  • R. Agalya  Student, Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Samayapuram, Trichy, Tamil Nadu, India
  • P. Bhagirathy  Student, Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Samayapuram, Trichy, Tamil Nadu, India
  • A. Ashley Shivanika  Student, Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Samayapuram, Trichy, Tamil Nadu, India
  • P. Deepa  Student, Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Samayapuram, Trichy, Tamil Nadu, India

Keywords:

MQ3 sensor, ultrasonic sensor , GPS, GSM, Aurdino.

Abstract

This paper proposes a new approach to detect as well as prevent car accident using inbuilt sensors. A recent survey shows that the rate of vehicle accidents is widely increasing, due to rash driving like over speeding, not following traffic rules etc. The application can make use of a sensor to sense alcohol using alcohol detector (mq3) connected to arduino. Vehicle accidents are one of the leading cause for death rate.This system deals with the optimum solution to these problems.The ultrasonic sensor is used to detect the objects in front of car which avoids dangerous accidents. Aurdino based vehicle anti-theft system using GPS,GSM and accelerometer.The GPS tracks the position of the stolen vehicle and gives the information via GSM.

References

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International Journal of Scientific Research in Science and Technology

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Published

2021-04-10

Issue

Volume 9, Issue 1, March-April-2021

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Parthibaraj A, R. Agalya, P. Bhagirathy, A. Ashley Shivanika, P. Deepa, " Accident Analysis and Prevention Using Advanced Drivers Assistance Systems, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 9, Issue 1, pp.1054-1059, March-April-2021.