COVID-19 Response and Recovery in Smart Sustainable City Governance and Management: Data-driven Internet of Things Systems and Machine Learning-based Analytics

Q1 Arts and Humanities

Geopolitics, History, and International Relations Pub Date : 2020-01-01 DOI:10.22381/ghir12220202

R. Scott, M. Poliak, J. Vrbka, E. Nica

引用次数: 22

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 © 2020, Addleton Academic Publishers All rights reserved

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可持续智慧城市治理和管理中的COVID-19应对和恢复:数据驱动的物联网系统和基于机器学习的分析

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geopolitics, History, and International Relations Arts and Humanities-History

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期刊介绍： Geopolitics, History, and International Relations publishes mainly original empirical research and review articles focusing on hot emerging topics, e.g. digital diplomacy, online political participation, data activism, fake social media news, algorithmic governance, computational politics, Internet terrorism, autonomous weapons systems, virtual history, innovative data-driven smart urban ecosystems, etc. This journal considers only manuscripts having a high integrative value in the current Scopus- and Web of Science-indexed literature.