Fine-grained air quality exposure modeling and forecasting using machine learning.
Implementing Organization
IIT Gandhinagar ,Gujarat & IIT Delhi
Principal Investigator
PI: Dr. Nipun Batra
Computer Science and Engineering, Indian Institute of Technology GandhinagarPalaj, Gandhinagar - 382055, Gujarat
nipun.batra@iitgn.ac.in
CO-Principal Investigator
Dr. Udit Bhatia
Discipline of Civil Engineering, Indian Institute of Technology GandhinagarPalaj, Gandhinagar - 382055, Gujarat, Dr. SagnikDey, Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, HauzKhas, New Delhi-110016 , Dr. RijurekhaSen, Indian Institute of Technology Delhi, HauzKhas, New Delhi-110016
riju@cse.iitd.ac.in,sagnik@cas.iitd.ac.in
Project Overview
Development of novel machine learning algorithms for leveraging various grades of air quality sensors (with different noise assumptions) and accurately inferring a spatially fine-grained air quality map of a megacity is attempted. Implementation of novel fusion techniques to leverage multi-modal data from sources including, but not limited to: satellite retrievals, traffic data, high-resolution (spatial and temporal) meteorological data, population density, geophysical variables (e.g. distance to road, land use pattern, non-vehicle point sources, etc. Implementation of data-driven air quality forecasting models leveraging various meteorological data, and advances in machine learning
IIT Gandhinagar ,Gujarat & IIT Delhi
nipun.batra@iitgn.ac.in
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