An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system

The Industrial Internet of Things (IIoT) was developed based on the technology and applications of the Internet of Things (IoT) in an industrial environment. As it is a sub-set of the IoT, it requires higher levels of safety and security. While increased productivity, better management and high oper...

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Main Author: Abdullah Ali Salamai
Format: Article
Language:English
Published: University of New Mexico 2023-05-01
Series:Neutrosophic Sets and Systems
Subjects:
Online Access:http://fs.unm.edu/NSS/RiskManagementIIoT13.pdf
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author Abdullah Ali Salamai
author_facet Abdullah Ali Salamai
author_sort Abdullah Ali Salamai
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description The Industrial Internet of Things (IIoT) was developed based on the technology and applications of the Internet of Things (IoT) in an industrial environment. As it is a sub-set of the IoT, it requires higher levels of safety and security. While increased productivity, better management and high operational efficiency are its main goals, they involve managing many risks, such as conflicting criteria and uncertain information, that need to be assessed and ranked. Therefore, in this paper, the Multi-criteria Decision-making (MCDM) method is used to deal with these criteria and a neutrosophic environment to overcome the uncertainty. Also, the Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches are proposed. The former is used to obtain the weights of the criteria and the latter to rank the management of risk in the IIOT system. Numerical examples are provided and a sensitivity analysis conducted to test the reliability of this model.
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spelling doaj.art-530853f0cf50417298379446f448af942023-05-17T13:35:59ZengUniversity of New MexicoNeutrosophic Sets and Systems2331-60552331-608X2023-05-015521623110.5281/zenodo.7832743An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) systemAbdullah Ali SalamaiThe Industrial Internet of Things (IIoT) was developed based on the technology and applications of the Internet of Things (IoT) in an industrial environment. As it is a sub-set of the IoT, it requires higher levels of safety and security. While increased productivity, better management and high operational efficiency are its main goals, they involve managing many risks, such as conflicting criteria and uncertain information, that need to be assessed and ranked. Therefore, in this paper, the Multi-criteria Decision-making (MCDM) method is used to deal with these criteria and a neutrosophic environment to overcome the uncertainty. Also, the Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches are proposed. The former is used to obtain the weights of the criteria and the latter to rank the management of risk in the IIOT system. Numerical examples are provided and a sensitivity analysis conducted to test the reliability of this model. http://fs.unm.edu/NSS/RiskManagementIIoT13.pdfiiotiotneutrosophic setstopsis
spellingShingle Abdullah Ali Salamai
An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system
Neutrosophic Sets and Systems
iiot
iot
neutrosophic sets
topsis
title An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system
title_full An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system
title_fullStr An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system
title_full_unstemmed An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system
title_short An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system
title_sort integrated model for ranking risk management in industrial internet of things iiot system
topic iiot
iot
neutrosophic sets
topsis
url http://fs.unm.edu/NSS/RiskManagementIIoT13.pdf
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