Road Condition Monitoring with Grading System

Authors

  • Saurabh Jadhav
  • Saurabh Zingade
  • Tanvesh Takawale

DOI:

https://doi.org/10.46243/jst.2020.v5.i5.pp64-69

Keywords:

Machine Learning, Road Conditions, Impact Analysis

Abstract

India has the highest number of two-wheeler riders in the entire world. As Indians think that twowheelers are more convenient a lot of people use them for their daily activities. Delivery boys for a lot of companies also prefer to use a two-wheeler as it is more economically convenient. Along with this, people also use twowheelers for rushing to the workplace avoiding a lot of traffic. The majority of these people can be classified as young adults. A lot of people complain about back issues due to the bad road conditions that they face while travelling every day. Our system uses the sensor consisting of the accelerometer and the gyroscope to analyze the condition of the road and classify how bad the current condition of the road actually is. The system will not only classify the road as good or bad but also provide a rating to the road based on how severe the condition of the road actually is. The sensors will be calibrated according to a particular vehicle which will be beneficial for the rider. The system will also provide the best option of the road from travelling from point A to point B provided if there are multiple options available and the analysis of all the options has been done previously. Keywords: Machine Learning; Road Conditions; Impact Analysis ________________________________________________________

Downloads

Published

2024-05-02

How to Cite

Saurabh Jadhav, Saurabh Zingade, & Tanvesh Takawale. (2024). Road Condition Monitoring with Grading System. Journal of Science & Technology (JST), 5(5), 64–69. https://doi.org/10.46243/jst.2020.v5.i5.pp64-69