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@article{155330,
        author = {G. R. Rao and Shubham Jain and Sarthak Soni and Anjali Parmar},
        title = {STATISTICAL ANALYSIS OF DETERIORATION OF AIR QUALITY IN THE PANDEMIC ERA},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {612-618},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155330},
        abstract = {Predicting air best is a complicated undertaking because of the dynamic nature, volatility, and high variability in time and area of pollutants and particulates. at the same time, being capable of version, are expecting, and screen air first-class is becoming increasingly more relevant, especially in urban areas, due to the discovered essential impact of air pollution on citizens’ healt hand the environment.
Managing air pollution is one of the principal environmental demanding situations in a smart city environment. actual-time tracking of pollutants statistics enables the metropolitans to investigate the cutting-edge site visitors state of affairs of the metropolis and take their selections as a consequence.
Existing research has used specific machine learning equipment for pollutants prediction; however, comparative evaluation of these techniques is regularly required to have a better understanding in their processing time for more than one dataset. Our task analysis is supposed to forecast pollutant and particulate stages and to predict the air quality index (AQI).},
        keywords = {Air Quality, Jupyter Notebook, Deterioration, Analysis},
        month = {},
        }