The objective of this project is to first collect and analyze the complex environmental data through various state-of-the-art time series techniques. Based on this outcome, machine learning (ML) methods are going to be utilized to capture the dynamic trends of a large number of environmental parameters including particulate matter and pollutants that cause long-term health hazards.
While developing such ML based models, intelligent formulations would be placed so that models do not get over-fitted with the data used to make them more robust. To identify the most significant features, ML based sensitivity analysis will be performed to enable a decision maker to find the most crucial environmental parameters to control.
Timeline and Budget
- Year 1: 6.9 Lakhs
- Year 2: 6.9 Lakhs
- Year 3: 6.9 Lakhs
Proposer: Dr. Kishalay Mitra, Professor & Head, Department of Chemical Engineering