Inspiration
A study estimates that crop residue burning released 149.24 million tonnes of carbon dioxide (CO2), over 9 million tonnes of carbon monoxide (CO), 0.25 million tonnes of oxides of sulphur (SOX), 1.28 million tonnes of particulate matter and 0.07 million tonnes of black carbon. These directly contribute to environmental pollution mainly air pollution Mainly in Punjab farmers have burnt paddy stubble over one lakh hectares in just eight days as per the data collected by the Punjab Pollution Control Board (PPCB) through satellite. So far in this season, the state has recorded farm fires over a total 2.11 lakh hectares area till October .The crop burning in Punjab has been increasing for 218% every year. Hence, we came to conclusion by integrating ML in predicting air pollutant and to control environmental pollution
What it does
It predicts the pollution caused in Delhi and analyse the pollutant. It says the burning of paddy fields in Punjab and Haryana. And to reduce the pollution the vegetation waste are collected by the Agriculture waste Buyer.
How we built it
We have used Python as our main programming language. Libraries used: Numpy, pandas,matplotlib & sklearn. Platform Used: Jupyter Noteboook & IBM Z. We rummaged for an accurate dataset in order to build a predicting model.
What we learned
We are completely new to machine learning and data science so the whole project is very helpful and interesting to learn.
What's next for BINARY BRAINS TEAM-110
The project gives only the analysis of the Delhi pollution, the next step will be building web app from this model.
Log in or sign up for Devpost to join the conversation.