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ABSTRACT. Employing recent research results covering smart sustainable city governance and management, and building our argument by drawing on data collected from CompTIA, Deloitte, DNV GL, ICMA, KPMG, PTI, RICS, and SCC, we performed analyses and made estimates regarding data-driven Internet of Things systems and machine learning-based analytics. Structural equation modeling was used to analyze the collected data.

Keywords: COVID-19; smart sustainable city; big data; Internet of Things

How to cite: Scott, R., Poliak, M., Vrbka, J., and Nica, E. (2020). “COVID-19 Response and Recovery in Smart Sustainable City Governance and Management: Data-driven Internet of Things Systems and Machine Learning-based Analytics,” Geopolitics, History, and International Relations 12(2): 16–22. doi:10.22381/GHIR12220202

Received 18 July 2020 • Received in revised form 23 October 2020
Accepted 25 October 2020 • Available online 27 October 2020

Roger Scott
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Center for Artificial Intelligence Data-driven
Internet of Things Systems at AAER, London, England
(corresponding author)
Milos Poliak
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Faculty of Operation and Economics
of Transport and Communications,
Department of Road and Urban Transport,
University of Zilina, Zilina, Slovak Republic
Jaromir Vrbka
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The Institute of Technology and Business in Ceske Budejovice,
The School of Expertness and Valuation, Czech Republic
Elvira Nica
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Faculty of Administration and Public Management,
The Bucharest University of Economic Studies, Romania

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