Machine Learning Coffee Seminar: Sasu Tarkoma, University of Helsinki "MegaSense: Scalable Air Pollution Sensing in Megacities"
MegaSense: Scalable Air Pollution Sensing in Megacities
Professor of Computer Science
Head of Department
Department of Computer Science
University of Helsinki
This talk gives an overview of the MegaSense research program that is a collaboration between Computer Science, Atmospheric Sciences and Geosciences at the University of Helsinki. The research program designs and deploys an air pollution monitoring system for realizing low-cost, near real-time and high resolution spatio-temporal air pollution maps of urban areas. MegaSense involves a novel hierarchy of multi-vendor distributed air quality sensors, in which more accurate sensors calibrate lower cost sensors. Current low-cost air quality sensors suffer from measurement drift and they have low accuracy. We address this significant open problem for dense urban areas by developing a calibration scheme based on machine learning that detects and automatically corrects drift. MegaSense integrates with the 5G cellular network and leverages mobile edge computing for sensor management and distributed pollution map creation.