TRAFFIC MANAGEMENT USING BIG DATA ANALYTIC TOOL

Authors

  • Saranya Krishna   ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
  • Sharanya K S   ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
  • Shwetha K S   ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
  • Dr. Jitendranath Mungara  ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India

Keywords:

Big Data, data mining, PYTHON

Abstract

The analysis of the large-scale data of transportation and accidents has many potentials and it can give very useful insights from the hidden relationship of data. Accidents datasets are used to find main causes of traffic accidents which mainly causes traffic causality and congestion. The vehicular causality dataset used to study human behavior effect on causing traffic accidents. This paper uses nine attributes and two classification algorithm to analyze and predict the possibilities of traffic accidents in python coding environment. Python has a large and comprehensive standard library . pandas is a software library written for the PYTHON programming language for data manipulation and analysis. The random forest algorithm and naïve Bayes algorithm predicts the possibilities of outcomes being a sign of any accident. Checking for the accurate results from algorithms rules and policies are made which is submitted to practioners and decision makers for further road safety measures

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-06-30

Issue

Volume 2, Issue 3, May-June-2017

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

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

How to Cite

[1]
Saranya Krishna , Sharanya K S , Shwetha K S , Dr. Jitendranath Mungara, " TRAFFIC MANAGEMENT USING BIG DATA ANALYTIC TOOL, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.777-781, May-June-2017.