VedPDubey / Pollution-and-the-Pandemic

Full stack machine learning project, with data visualization and analysis of the air quality of India, the effect of the pandemic on pollution, and performing Time Series Forecasting on the data using Facebook Prophet to predict future values of the AQI. Interactive and engaging website designed and the model and backend deployed on a local host using Flask.

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Pollution and the Pandemic - Team Underdogs

Introduction:

On 23rd March 2020 the government of India under Prime Minister Narendra Modi ordered a nationwide lockdown for 21 days, limiting movement of the entire 1.38 billion or 138 crore population of India as a preventive measure against the COVID-19 pandemic in India. And that is pretty much how - for us, the Indian denizens - a life in the pandemic was about to begin.

Almost immediately after the lockdown was initiated, citizens started noticing that the environment in particular the air quality seemed to have improved noticeably. So much so, that if you recall - the scenic Dauladhar mountain range in Himachal Pradesh was visible from its neighbouring states - which otherwise would have been covered with dense smog.

The objective behind our project is to give an insight into just how much of an impact this pandemic has had on the long standing issue of hazardous air pollution. Not only that but we have worked on the data in order to create a Time Series Forecasting model using Facebook Prophet so that this situation and whatever we’ve experienced before it helps us in preparing for the future.

To summarise the project great emphasis has been made on how much the pandemic has been responsible for affecting the pollution, through interactive graphs and elements which will grasp the interest and pique the curiosity of the user.

Presentation Link:

Link to our Project Powerpoint

Technology Stack:

  1. Python 3.7
  2. Google Colab
  3. Time Series Forecasting (Machine Learning) using FB Prophet
  4. Data Visualisation using pyplot and seaborn
  5. Flask
  6. HTML
  7. CSS & JavaScript
  8. Heroku (to be used)

Contributors:

Team Name: Underdogs

Made at:

About

Full stack machine learning project, with data visualization and analysis of the air quality of India, the effect of the pandemic on pollution, and performing Time Series Forecasting on the data using Facebook Prophet to predict future values of the AQI. Interactive and engaging website designed and the model and backend deployed on a local host using Flask.


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Language:HTML 72.0%Language:Jupyter Notebook 24.2%Language:JavaScript 3.2%Language:CSS 0.5%Language:Python 0.1%