TITLE:
“Smart” Surveillance of Dusty Behavior: Illuminating the Relationship between Particulate Matter and the Atmosphere
AUTHORS:
Shelley Choi
KEYWORDS:
Atmosphere, Particulate Matter, Weather Forecast, Artificial Intelligence, Deep Learning
JOURNAL NAME:
Computational Water, Energy, and Environmental Engineering,
Vol.7 No.3,
July
20,
2018
ABSTRACT: Although large amounts of research have been completed to find the relationship between
particulate matter and climate change, they have still proven
to be inadequate. Efforts to lay the foundations for understanding atmospheric chemical
reactions have been repeatedly foiled by both the
size and complexity of the task, which require more than the effort of a
handful of researchers. Since the development of advanced physical models for
dust behavior is projected to take years, what if
laypeople could dramatically expedite this process by using their mobile devices as measurement tools? With relatively
little effort by many individuals, previously unknown information about the
earth’s atmosphere may at last become accessible thanks to recent advances in
artificial intelligence. However, there are potential obstacles. Even if all
technical problems are resolved, viable plans for battling particulate matter
pollution will likely need to be accompanied by environmental policies. While
technological breakthroughs give reason to hope for a brighter future, the
resolution of global issues requires both grassroots changes and global
efforts.