Authors :
Radhika M.Patil; Dr. H. T. Dinde; Sonali. K. Powar
Volume/Issue :
Volume 5 - 2020, Issue 8 - August
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/2Z8eKlQ
DOI :
10.38124/IJISRT20AUG683
Abstract :
Day by day the air pollution becomes serious
concern in India as well as in overall world. Proper or
accurate prediction or forecast of Air Quality or the
concentration level of other Ambient air pollutants such
as Sulfur Dioxide, Nitrogen Dioxide, Carbon Monoxide,
Particulate Matter having diameter less than 10µ,
Particulate Matter having diameter less than 2.5µ,
Ozone, etc. is very important because impact of these
factors on human health becomes severe. This literature
review focuses on the various techniques used for
prediction or modelling of Air Quality Index (AQI) and
forecasting of future concentration levels of pollutants
that may cause the air pollution so that governing bodies
can take the actions to reduce the pollution.
Keywords :
AQI, air pollutants, Linear Regression, Prediction, Artificial Neural Network
Day by day the air pollution becomes serious
concern in India as well as in overall world. Proper or
accurate prediction or forecast of Air Quality or the
concentration level of other Ambient air pollutants such
as Sulfur Dioxide, Nitrogen Dioxide, Carbon Monoxide,
Particulate Matter having diameter less than 10µ,
Particulate Matter having diameter less than 2.5µ,
Ozone, etc. is very important because impact of these
factors on human health becomes severe. This literature
review focuses on the various techniques used for
prediction or modelling of Air Quality Index (AQI) and
forecasting of future concentration levels of pollutants
that may cause the air pollution so that governing bodies
can take the actions to reduce the pollution.
Keywords :
AQI, air pollutants, Linear Regression, Prediction, Artificial Neural Network
