An Approach for Environment Vitiation Analysis and Prediction Using Data Mining and Business Intelligence

  • Shubhangi TirpudeEmail author
  • Aarti Karandikar
  • Rashmi Welekar
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 165)


This paper focuses on an intuitive and effective way of giving data analysis and predictions based on the quality of various environmental factors for India. The problem with the existing solutions/system is that no complete dataset is available which gives a complete and thorough analysis of all the environmental factors such as air, water, tree cover, and forest cover. We have collected authentic data from various government sources and performed operations on the combined datasets. We have performed ETL on the various raw datasets and then imported all the transformed datasets into the PowerBI database and created multiple dashboards which gave data analysis based on all the different factors. For predictions and forecasting we have used RStudio, K-means clustering, and ARIMA model. The dashboards support Natural Language Processing and the user can input their query in the form of a sentence and will get the required results. We have implemented vitiation analysis for air quality, water quality, forest cover, and tree cover in India and the system is ready to be scaled to give analysis for different countries of the world.


Environment quality Data analysis Business intelligence Air quality Water quality Tree cover Forest cover Predictions NLP Forecasting K-means clustering ARIMA Natural language processing 


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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Shri Ramdeobaba College of Engineering and ManagementNagpurIndia

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