Addressing the COVID-19 Crisis by Harnessing Internet of Things Sensors and Machine Learning Algorithms in Data-driven Smart Sustainable Cities
Unknown authors
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 © 2020, Addleton Academic Publishers All rights reserved
Topics & Concepts
Coronavirus disease 2019 (COVID-19)Internet of ThingsThe Internet2019-20 coronavirus outbreakExploratory researchMachine learningComputer scienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)AlgorithmSustainable developmentStructural equation modelingArtificial intelligenceData sciencePolitical scienceSociologyComputer securityWorld Wide WebSocial scienceMedicineVirologyInfectious disease (medical specialty)OutbreakDiseasePathologyLawSmart Cities and TechnologiesHuman Mobility and Location-Based Analysis