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Addressing the COVID-19 Crisis by Harnessing Internet of Things Sensors and Machine Learning Algorithms in Data-driven Smart Sustainable Cities

Addressing the COVID-19 Crisis by Harnessing Internet of Things Sensors and Machine Learning... This paper analyzes the outcomes of an exploratory review of the current research on data-driven smart sustainable cities. The data used for this study was obtained and replicated from previous research conducted by Capgemini, ICMA, KPMG, UNESCAP, UNHSP, SCC, The University of Adelaide, and The World Bank. We performed analyses and made estimates regarding Internet of Things sensors and machine learning algorithms. Data collected from 5,200 respondents are tested against the research model by using structural equation modeling. Keywords: COVID-19; Internet of Things; big data; smart sustainable city; algorithm http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Geopolitics, History, and International Relations Addleton Academic Publishers

Addressing the COVID-19 Crisis by Harnessing Internet of Things Sensors and Machine Learning Algorithms in Data-driven Smart Sustainable Cities

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1948-9145
eISSN
2374-4383
Publisher site
See Article on Publisher Site

Abstract

This paper analyzes the outcomes of an exploratory review of the current research on data-driven smart sustainable cities. The data used for this study was obtained and replicated from previous research conducted by Capgemini, ICMA, KPMG, UNESCAP, UNHSP, SCC, The University of Adelaide, and The World Bank. We performed analyses and made estimates regarding Internet of Things sensors and machine learning algorithms. Data collected from 5,200 respondents are tested against the research model by using structural equation modeling. Keywords: COVID-19; Internet of Things; big data; smart sustainable city; algorithm

Journal

Geopolitics, History, and International RelationsAddleton Academic Publishers

Published: Jan 1, 2019

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