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Mathematics of Planet EarthThe Internet of Things and Machine Learning, Solutions for Urban Infrastructure Management

Mathematics of Planet Earth: The Internet of Things and Machine Learning, Solutions for Urban... [Urban infrastructure management requires the ability to reason about a large-scale complex system: What is the state of the system? How can it be compactly represented and quantified? How is the system likely to evolve? Reasoning calls for predictive modeling, feedback, optimization, and control. With an understanding of the system state and its likely evolution, how should resources be allocated or policies changed to produce a better outcome? By leveraging data from the Internet of Things, it becomes feasible to perform online estimation, optimization, and control of such systems to help our cities function better. This involves taking traditional applications of mathematical sciences into a large-scale, online, and adaptive setting. We focus in this chapter on two particular applications that are important to effectively manage a city: transportation and municipal water services.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Mathematics of Planet EarthThe Internet of Things and Machine Learning, Solutions for Urban Infrastructure Management

Part of the Mathematics of Planet Earth Book Series (volume 5)
Editors: Kaper, Hans G.; Roberts, Fred S.
Mathematics of Planet Earth — Nov 2, 2019

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References (131)

Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2019
ISBN
978-3-030-22043-3
Pages
337 –368
DOI
10.1007/978-3-030-22044-0_13
Publisher site
See Chapter on Publisher Site

Abstract

[Urban infrastructure management requires the ability to reason about a large-scale complex system: What is the state of the system? How can it be compactly represented and quantified? How is the system likely to evolve? Reasoning calls for predictive modeling, feedback, optimization, and control. With an understanding of the system state and its likely evolution, how should resources be allocated or policies changed to produce a better outcome? By leveraging data from the Internet of Things, it becomes feasible to perform online estimation, optimization, and control of such systems to help our cities function better. This involves taking traditional applications of mathematical sciences into a large-scale, online, and adaptive setting. We focus in this chapter on two particular applications that are important to effectively manage a city: transportation and municipal water services.]

Published: Nov 2, 2019

Keywords: Algorithms; Control; Data; Estimation; Internet of Things; Machine learning; Prediction; Smart city; Urban computing

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