Air pollution analysis using big data technology: towards a better world

  • Authors

    • Siva Krishna kvs
    • Saikumar Pulluri
    • Kamalakannan J
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.15532
  • Air Pollution, Big Data, Classifiers, Decision Tree, Logistic Regression, Naïve Byes, Pollutants, Random Forest.

  • Abstract

    Big data is generally perceived as being one of the most intense drivers to advance profitability, Enhance effectiveness, furthermore, bolsters advancement. It is quite anticipated which would analyze big data and transform big data into big values. To find the answer of the fascinat-ing question whether there are characteristic connections between the two inclinations of big data and green challenges, a study has exam-ined the issues on greening the entire life cycle of big data frameworks. As the data which is captured from different sensors is huge, to analysis that data and find patterns to predict the future data, we need big data technology which can handle that huge amount of data in a better way. In this paper, we have used different classifiers to analysis the results based on available data in the spark framework using the Python and Scala programming languages. We showed a comparative study between python and Scala technology based on classifiers. For this research data set of Andhra-Pradesh and Tamilnadu (states in India) are utilized to show the analysis of air pollution with the help of big data concept. We compared the classifiers on based on time and accuracy. Generally random forest gives good results but in our case deci-sion tree and logistic regression have given high accuracy.

     

  • References

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  • How to Cite

    Krishna kvs, S., Pulluri, S., & J, K. (2018). Air pollution analysis using big data technology: towards a better world. International Journal of Engineering & Technology, 7(2.33), 919-923. https://doi.org/10.14419/ijet.v7i2.33.15532

    Received date: 2018-07-13

    Accepted date: 2018-07-13

    Published date: 2018-06-08