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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Air Quality Prediction Through Regression Model

[Full Text]

 

AUTHOR(S)

A.Aarthi, P.Gayathri, N.R.Gomathi , S.Kalaiselvi , Dr.V.Gomathi

 

KEYWORDS

Air pollution, health, Carbon monoxide, time-series data, Regression analysis

 

ABSTRACT

Examining and protecting air quality in this world has become one of the essential activities for every human in many industrial and urban areas today. The meteorological and traffic factors, burning of fossil fuels, and industrial parameters play significant roles in air pollution. With this increasing air pollution, we need to implement models that will record information about concentrations of air pollutants. The deposition of these harmful gases in the air is affecting the quality of people's lives by altering their health, especially in urban areas. In this paper, regression techniques are used to predict the concentration of Carbon monoxide in the environment. Carbon monoxide causes headaches, dizziness, vomiting, nausea, and heart diseases. The dataset is downloaded and imported to the project. It contains data on average hourly responses of major air pollutants for nearly one year. This dataset is used to predict the amount of Carbon monoxide based on other parameters using regression analysis. It creates awareness among people about the air quality degradation, and it's health effects. Support environmentalists and government to frame air quality standards and regulations based on issues of toxic and pathogenic air exposure and health-related hazards for human welfare.

 

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