We are witnessing exponential growth of urban areas and the emergence of mega-cities. The MegaSense project investigates massive-scale pollution and environmental sensing enhanced by advanced data analytics and AI techniques. The MegaSense concept is coordinated by the University of Helsinki and applies world class scientific expertise in Atmospheric Science, Computer Science and GeoInformatics.
Our mission is to use machine learning techniques for the calibration of a high number of low-quality and low-cost sensors with a small number of highly accurate measurement stations.
The project addresses the global challenge pertaining to pollution modelling and prediction, while considering the limitations of the state of the art: low density of measurement stations and lack of high-resolution spatial-temporal data.
Nine out of ten people around the world breathe highly polluted air.
Recent estimates indicate that by 2030 the global population of major cities with 10 million or more inhabitants is growing from 3.2 billion to close to 5 billion. Air pollution is a global challenge that resulted in the death of nearly 7 million people in 2012 according to the World Health Organization.
This hyper densification results in denser energy consumption, more waste, and more traffic congestion. This development can adversely affect air quality and increase the pollution levels of cities. By air pollution we mean the introduction of harmful chemicals into the atmosphere.
The recent study by the Global Burden of Disease (GBD) project reported that 5.5 million people worldwide are dying prematurely each year as a result of air pollution.