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ABSTRACT. Despite the relevance of smart Industrial Internet of Things devices, services, and applications, only limited research has been conducted on this topic. Using and replicating data from BCG, BDO, BI Intelligence, DAA, IDC, IoT Analytics GmbH, McKinsey, PwC, Statista, and Zebra Technologies, we performed analyses and made estimates regarding disruptive technologies that will enable digitization of the manufacturing sector (%), retailers planning to invest in artificial intelligence and Internet of Things technologies by 2021 (%), and advanced technologies manufacturers are planning to use (%). The results of a study based on data collected from 4,500 respondents provide support for our research model. Using the structural equation modeling and employing the probability sampling technique, we gathered and analyzed data through a self-administrated questionnaire.

Keywords: sensing and sensory data; predictive analytics; cognitive computing

How to cite: Bourke, Eilis, Maria Kovacova, Jana Kliestikova, and Zuzana Rowland (2019). “Smart Industrial Internet of Things Devices, Services, and Applications: Ubiquitous Sensing and Sensory Data, Predictive Analytics Algorithms, and Cognitive Computing Technologies,” Analysis and Metaphysics 18: 50–56. doi:10.22381/AM1820197

Received 12 May 2019 • Received in revised form 20 October 2019
Accepted 23 October 2019 • Available online 5 December 2019

Eilis Bourke
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The Cognitive Artificial Intelligence
Systems Laboratory, Cambridge, UK
Maria Kovacova
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
Jana Kliestikova
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
Zuzana Rowland
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The Institute of Technology and Business in Ceske Budejovice,
The School of Expertness and Valuation, Czech Republic

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