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Relation between variables in Dataset.ipynb

#Analysis of Air quality and correlation visualization with different environment factors

Open Data Hackathon project

The air we breathe may contains many impurities. These impurities include both particulate matters as well as different microorganisms. The particulate matters are composed of different size particles such as PM 2.5, PM 10, amd PMc(s). These particles get suspended in the air and on exposure, cause different types of health problems that become a tremendous health concern in a developing country like Nepal.

In our work, we have tried to plot the correlation between different parameters in the environment with the concentration of the particulate matter in the air. Though the available dataset of Pokhara did not contain the parameters that we are looking after, such as the humidity, rainfall, air temperature and wind speed, we worked on the past data from different sites and combined the data to make a more complete dataset.

Then the correlation between the different parameters were observed. We aimed to use the weather forecast for the next day as well as the trend of PM 2.5 concentration in the atmosphere to make helpful predictions about the concentration of PM 2.5 particulate matter for the next day.

We need a quite large dataset to make accurate predictions about the levels of PM 2.5. However, we tried incorporating a prediction engine into the system with little success. At the end, we created a infographic with content awaring people about the effects of particulate matter and the ways to be safe.

This project was undertaken by:

  1. Dr. Laxmi Prasad Khatiwada
  2. Sandesh Bhusal
  3. Pujan Thapa
  4. Radhika Bhandari
  5. Sanishya Shrestha
  6. Sanju Sah

Here are some glimpses from the project:

Finding Correlation between parameters

Heatmap in real time map


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