Trustworthy digital twins in the industrial internet of things with blockchain
Open accessAbstract
Industrial processes rely on sensory data for critical decision-making processes. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the trustworthiness of data. To this end, we envision a blockchain-based framework for the Industrial Internet of Things (IIoT) to address the issues of data management and security. Once the data collected from trustworthy sources are recorded in the blockchain, product lifecycle events can be fed into data-driven systems for process monitoring, diagnostics, and optimized control. In this regard, we leverage digital twins (DTs) that can draw intelligent conclusions from the data by identifying the faults and recommending precautionary measures ahead of critical events. Furthermore, we discuss the integration of DTs and blockchain to target key challenges of disparate data repositories, untrustworthy data dissemination, and fault diagnosis. Finally, we identify outstanding challenges faced by the IIoT and future research directions while leveraging blockchain and DTs.
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Accurately modeling DTs is an ongoing and unresolved concern due to variability, vagueness, and uncertainty in physical space.
“However, the challenge lies in accurately modeling DTs, given the variability, vagueness, and uncertainty inherent in physical space, making it an ongoing and unresolved concern [126].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [126]
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Cites
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“However, the challenge lies in accurately modeling DTs, given the variability, vagueness, and uncertainty inherent in physical space, making it an ongoing and unresolved concern [126].”
- Authors
- Suhail, S., Hussain, R., Jurdak, R., & Hong, C. S.
- Affiliations
- Vienna University of Economics and Business (AT)
- University of Bristol (GB)
- Queensland University of Technology (AU)
- Kyung Hee University (KR)
- Venue
- IEEE Internet Computing
- Published
- 2022-05-01
- Volume
- 26
- Issue
- 3
- Pages
- 58-67
- ISSN
- 1089-7801 (ISSN-L)
- 1941-0131
- OpenAlex
- W3094110753
- Cited by
- 154
- References
- 13
- Citations by year
- 2026: 11 · 2025: 28 · 2024: 31 · 2023: 39 · 2022: 33 · 2021: 12
- FWCI
- 26.00
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE Internet Computing (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by-nc)
- Bristol Research (University of Bristol) (submittedVersion)
- Explore Bristol Research (submittedVersion)
- WU Research (submittedVersion)
- arXiv (Cornell University)
- Funders
- Korea government MSIT (IITP-2020-2015-0-00742, No.2019-0-01287)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, Industrial Internet of Things, blockchain, data trustworthiness, data security, data management, process monitoring, fault diagnosis, predictive maintenance, data-driven control
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