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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.
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