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ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore artificial intelligence data-driven Internet of Things systems, sustainable Industry 4.0 wireless networks, and digitized mass production in cyber-physical smart manufacturing. Using and replicating data from BDO, Capgemini, the Economist Intelligence Unit, Forrester, Management Events, and McKinsey, we performed analyses and made estimates regarding autonomous networked manufacturing machines in industrial enterprises. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: cyber-physical; smart manufacturing; sustainability; Industry 4.0; big data

How to cite: Wade, K., and Vochozka, M. (2021). “Artificial Intelligence Data-driven Internet of Things Systems, Sustainable Industry 4.0 Wireless Networks, and Digitized Mass Production in Cyber-Physical Smart Manufacturing,” Journal of Self-Governance and Management Economics 9(3): 48–60. doi: 10.22381/jsme9320214.

Received 16 March 2021 • Received in revised form 10 September 2021
Accepted 12 September 2021 • Available online 18 September 2021

Karen Wade
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Center for Cognitive Technology-driven
Automation at CLI, Ottawa, Canada
(corresponding author)
Marek Vochozka
This email address is being protected from spambots. You need JavaScript enabled to view it.
The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceské Budejovice, Czech Republic

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