Environmental Data Analytics

Environmental Data Analytics

Research on Environmental Data Analytics

Objective: To provide an integrated, in depth applied approach to data analysis and linear statistical models in environmental science research.

Emphasis on graphical methods for visualizing data and the results of statistical models. Statistical techniques to enable better-informed decision-making as our climate changes.

With the rise of environmental issues, many are beginning to see solving these issues as a spectator sport. A sport in which humanity relies on policy makers, scientists, and others to make changes for them. Our progress to halt climate change is not a result of growth, but actually regression. It is the result of our growing inability to exist at peace with nature rather than in constant conflict.

Most environmental data involve a large degree of complexity and uncertainty. Environmental Data Analysis is created to provide modern quantitative tools and techniques designed specifically to meet the needs of environmental sciences and related fields. While an explosion in data science research has fuelled enormous advances in areas as diverse as eCommerce and marketing, smart cities, logistics and transport, health and wellbeing, these tools have yet to be fully deployed in one of the most pressing problems facing humanity, that of mitigating and adapting to global change.
The research project would focus on developing a new approach to data science and environmental challenges in the niche environmental science areas like Waste Management, Water Management and Air quality monitoring. Analysis of environmental data would provide a perspective to solve future environmental issues. Scaling down a new approach for the progression of environmental data analysis. This would further help in the deployment of statistical techniques and data models to enable decision making on the real environmental issues and the prevention of the same.

 

 

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