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ABSTRACT. Employing recent research results covering big data analytics processes in Industrial Internet of Things systems, and building our argument by drawing on data collected from Forbes, McKinsey, PwC, Statista, and World Economic Forum, we performed analyses and made estimates regarding the Internet of Things units installed base by category (2014–2020, in billions of units), spending on Internet of Things worldwide by vertical in 2015 and 2020 (in billions of U.S. dollars), drivers of technological change, industries overall (%), and stages of diffusion of artificial intelligence technologies (%, adoption type). Structural equation modeling was used to analyze the collected data.
JEL codes: E24; J21; J54; J64

Keywords: big data analytics; Industrial Internet of Things; sensing; computing

How to cite: Eysenck, Glenn, Erika Kovalova, Veronika Machova, and Vladimir Konecny (2019). “Big Data Analytics Processes in Industrial Internet of Things Systems: Sensing and Computing Technologies, Machine Learning Techniques, and Autonomous Decision-Making Algorithms,” Journal of Self-Governance and Management Economics 7(4): 28–34. doi:10.22381/JSME7420194

Received 9 July 2019 • Received in revised form 1 December 2019
Accepted 3 December 2019 • Available online 15 December 2019

Glenn Eysenck
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The Cognitive Labor Institute,
New York City, NY, USA
(corresponding author)
Erika Kovalova
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
Veronika Machova
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The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceske Budejovice, Czech Republic
Vladimir Konecny
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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

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