by C.-H. Chen-Ritzo
and F. Parr
During the last 50 years, population growth, along with
increasingly affluent societies, has resulted in a greater demand for
our limited physical infrastructures and natural resources than ever
before. In addition, the risks of climate change have heightened the
need for more sophisticated ways of controlling carbon emissions.
Today, numerous streams of data are being collected from sensors
that monitor the environment. When used in conjunction with
computational models, these streams can be important sources of
data for understanding physical phenomena and human behavior.
In this paper, we present a vision of a pervasively instrumented
world in which these streams of real-world data are combined with
mathematical models to improve the ability to manage the
consumption of increasingly scarce resources. Such an
instrumented world requires a class of information technology
systems that combine very large numbers of sensors and actuators
with computing platforms for capturing and analyzing such data
streams. We provide details on the characteristics, requirements,
and possible applications of such platforms and the key roles that
they will play in addressing various societal challenges.