Internet of things sensing networks, deep learning-enabled smart process planning, and big data-driven innovation in cyber-physical system-based manufacturing

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Internet of things sensing networks, deep learning-enabled smart process planning, and big data-driven innovation in cyber-physical system-based manufacturing. / Connolly-Barker, Melissa; Gregova, Elena; Dengov, Victor V.; Podhorska, Ivana.

In: Economics, Management, and Financial Markets, Vol. 15, No. 2, 06.2020, p. 23-29.

Research output: Contribution to journal › Article › peer-review

BibTeX

@article{93d7eaab0fff47b895431fe468541feb,

title = "Internet of things sensing networks, deep learning-enabled smart process planning, and big data-driven innovation in cyber-physical system-based manufacturing",

abstract = "Based on an in-depth survey of the literature, the purpose of the paper is to explore cyber-physical system-based manufacturing. Using and replicating data from Capgemini, CompTIA, EY, Microsoft, PAC, and PwC, we performed analyses and made estimates regarding the relationship between Internet of Things sensing networks, deep learning-enabled smart process planning, and big data-driven inno-vation. Data were analyzed using structural equation modeling.",

keywords = "Big data, Cyber-physical system-based manufacturing, Internet of Things",

author = "Melissa Connolly-Barker and Elena Gregova and Dengov, {Victor V.} and Ivana Podhorska",

year = "2020",

month = jun,

doi = "10.22381/EMFM15220203",

language = "English",

volume = "15",

pages = "23--29",

journal = "Economics, Management, and Financial Markets",

issn = "1842-3191",

publisher = "Addleton Academic Publishers",

number = "2",

}

RIS

TY - JOUR

T1 - Internet of things sensing networks, deep learning-enabled smart process planning, and big data-driven innovation in cyber-physical system-based manufacturing

AU - Connolly-Barker, Melissa

AU - Gregova, Elena

AU - Dengov, Victor V.

AU - Podhorska, Ivana

PY - 2020/6

Y1 - 2020/6

N2 - Based on an in-depth survey of the literature, the purpose of the paper is to explore cyber-physical system-based manufacturing. Using and replicating data from Capgemini, CompTIA, EY, Microsoft, PAC, and PwC, we performed analyses and made estimates regarding the relationship between Internet of Things sensing networks, deep learning-enabled smart process planning, and big data-driven inno-vation. Data were analyzed using structural equation modeling.

AB - Based on an in-depth survey of the literature, the purpose of the paper is to explore cyber-physical system-based manufacturing. Using and replicating data from Capgemini, CompTIA, EY, Microsoft, PAC, and PwC, we performed analyses and made estimates regarding the relationship between Internet of Things sensing networks, deep learning-enabled smart process planning, and big data-driven inno-vation. Data were analyzed using structural equation modeling.

KW - Big data

KW - Cyber-physical system-based manufacturing

KW - Internet of Things

UR - http://www.scopus.com/inward/record.url?scp=85087372543&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/3b86ee38-f507-38ab-88c0-74a9310bdb87/

U2 - 10.22381/EMFM15220203

DO - 10.22381/EMFM15220203

M3 - Article

AN - SCOPUS:85087372543

VL - 15

SP - 23

EP - 29

JO - Economics, Management, and Financial Markets

JF - Economics, Management, and Financial Markets

SN - 1842-3191

IS - 2

ER -

ID: 60618876