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An Evaluation of the Air Quality in the Neighborhoods Surrounding the KMML Industrial Area in Chavara using Machine Learning Techniques

  • Authors
    Johnson S.Corresponding
    Perumalsamy D.
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  • gnest_06120_in press.pdf
  • Paper ID
    gnest_06120
  • Paper status
    In press
  • Date paper submitted
  • Date paper accepted
  • Date paper online
DOI
https://doi.org/10.55555/gnj.06120
Graphical abstract
Abstract

The nuclear power plants are another kind of power sources. Throughout the summer as well as winter of 2010 through 2022, researchers analyzed data from residential neighborhoods bordering the Chavara manufacturing industry in the Kollam region of southern India. The research set out to compare the quality of the air in the industrial area with that of the surrounding residential areas, along with the concentrations of several airborne pollutants (SO2, NO2, RPM, Free Cl2, and TSPM). To forecast a value close to the true value, a combination of artificial intelligence techniques is utilized. The optimum method for making accurate predictions of the relevant Air Quality indicators is then determined by comparing various metrics of error across the different approaches. The next statement presents the analysis's ultimate.

Keywords
Air Quality Evaluation Machine learning techniques Industry 4.0 and Chavara Kerala
Cite this article
Johnson, S. and Perumalsamy, D. (2024) “An Evaluation of the Air Quality in the Neighborhoods Surrounding the KMML Industrial Area in Chavara using Machine Learning Techniques”, Global NEST Journal [Preprint]. Available at: https://doi.org/10.55555/gnj.06120.
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  • gnest_06120_in press.pdf