  With the rapid development of economy in China over the past decade, air
pollution has become an increasingly serious problem in major cities and caused
grave public health concerns in China. Recently, a number of studies have dealt
with air quality and air pollution. Among them, some attempt to predict and
monitor the air quality from different sources of information, ranging from
deployed physical sensors to social media. These methods are either too
expensive or unreliable, prompting us to search for a novel and effective way
to sense the air quality. In this study, we propose to employ the state of the
art in computer vision techniques to analyze photos that can be easily acquired
from online social media. Next, we establish the correlation between the haze
level computed directly from photos with the official PM 2.5 record of the
taken city at the taken time. Our experiments based on both synthetic and real
photos have shown the promise of this image-based approach to estimating and
monitoring air pollution.
