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ABSTRACT. We draw on a substantial body of theoretical and empirical research on industrial big data analytics for Cognitive Internet of Things, and to explore this, we inspected, used, and replicated survey data from BCG, CIO, EY, Gartner, PwC, and Statista, performing analyses and making estimates regarding how Industry 4.0 is delivering revenue, cost and efficiency gains (%) and top technologies being considered in-line with organizations’ strategic plan (%). Structural equation modeling was used to analyze the data and test the proposed conceptual model.

Keywords: industrial big data analytics; Cognitive Internet of Things

How to cite: Graessley, Scott, Petr Suler, Tomas Kliestik, and Eva Kicova (2019). “Industrial Big Data Analytics for Cognitive Internet of Things: Wireless Sensor Networks, Smart Computing Algorithms, and Machine Learning Techniques,” Analysis and Metaphysics 18: 23–29. doi:10.22381/AM1820193

Received 29 March 2019 • Received in revised form 26 August 2019
Accepted 28 August 2019 • Available online 15 December 2019

Scott Graessley
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The Cognitive Automation Research Unit,
New Haven, CT, USA
Petr Suler
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The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceske Budejovice, Czech Republic
Tomas Kliestik
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
Eva Kicova
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic

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