Earth, Atmosphere & Environment Sciences
Title : | “Fine-grained air quality exposure modeling and forecasting using machine learning”. |
Area of research : | Earth, Atmosphere & Environment Sciences |
Focus area : | Atmospheric Science |
Principal Investigator : | PI: Dr. Nipun Batra, Computer Science and Engineering, Indian Institute of Technology GandhinagarPalaj, Gandhinagar - 382055, Gujarat |
Timeline Start Year : | 2023 |
Details
Executive Summary : | 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 |
Co-PI: | 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 |
Total Budget (INR): | 61,40,960 |
Organizations involved