NICA, Elvira and Vojtěch STEHEL. Internet of Things Sensing Networks, Artificial Intelligence-based Decision-Making Algorithms, and Real-Time Process Monitoring in Sustainable Industry 4.0. Journal of Self-Governance and Management Economics. New York, USA: Addleton Academic Publishers, 2021, vol. 9, No 3, p. 35-47. ISSN 2329-4175.
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Basic information
Original name Internet of Things Sensing Networks, Artificial Intelligence-based Decision-Making Algorithms, and Real-Time Process Monitoring in Sustainable Industry 4.0
Authors NICA, Elvira (guarantor) and Vojtěch STEHEL (203 Czech Republic, belonging to the institution).
Edition Journal of Self-Governance and Management Economics, New York, USA, Addleton Academic Publishers, 2021, 2329-4175.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10200 1.2 Computer and information sciences
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/75081431:_____/21:00002171
Organization unit Institute of Technology and Business in České Budějovice
Keywords in English sustainability; Industry 4.0; Internet of Things; sensing network; big data
Tags BPL_FIP_2, RIV21, SCOPUS
Changed by Changed by: Mgr. Nikola Petříková, učo 28324. Changed: 21/4/2022 07:16.
Abstract
This article presents an empirical study carried out to evaluate and analyze Internet of Things sensing networks, artificial intelligence-based decision making algorithms, and real-time process monitoring in sustainable Industry 4.0. Building our argument by drawing on data collected from Algorithmia, BCG, Deloitte, the Economist Intelligence Unit, Management Events, McKinsey, Ovum, PwC, and Techconsult, we performed analyses and made estimates regarding inter connected data processing in smart manufacturing and business analytics. Data collected from 6,200 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
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