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

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Smart Trends in Computing and Communications

Abstract

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.

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Correspondence to Shubhangi Tirpude .

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Tirpude, S., Karandikar, A., Welekar, R. (2020). An Approach for Environment Vitiation Analysis and Prediction Using Data Mining and Business Intelligence. In: Zhang, YD., Mandal, J., So-In, C., Thakur, N. (eds) Smart Trends in Computing and Communications. Smart Innovation, Systems and Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-15-0077-0_34

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