Blockchain-empowered digital twins collaboration: Smart transportation use case
Author | Sahal, Radhya |
Author | Alsamhi, Saeed H. |
Author | Brown, Kenneth N. |
Author | O’shea, Donna |
Author | McCarthy, Conor |
Author | Guizani, Mohsen |
Available date | 2022-10-30T10:46:21Z |
Publication Date | 2021-09-01 |
Publication Name | Machines |
Identifier | http://dx.doi.org/10.3390/machines9090193 |
Citation | Sahal, R., Alsamhi, S. H., Brown, K. N., O’Shea, D., McCarthy, C., & Guizani, M. (2021). Blockchain-empowered digital twins collaboration: smart transportation use case. Machines, 9(9), 193. |
Abstract | Digital twins (DTs) is a promising technology in the revolution of the industry and essential for Industry 4.0. DTs play a vital role in improving distributed manufacturing, providing up-to-date operational data representation of physical assets, supporting decision-making, and avoiding the potential risks in distributed manufacturing systems. Furthermore, DTs need to collaborate within distributed manufacturing systems to predict the risks and reach consensus-based decision-making. However, DTs collaboration suffers from single failure due to attack and connection in a centralized manner, data interoperability, authentication, and scalability. To overcome the above challenges, we have discussed the major high-level requirements for the DTs collaboration. Then, we have proposed a conceptual framework to fulfill the DTs collaboration requirements by using the combination of blockchain, predictive analysis techniques, and DTs technologies. The proposed framework aims to empower more intelligence DTs based on blockchain technology. In particular, we propose a concrete ledger-based collaborative DTs framework that focuses on real-time operational data analytics and distributed consensus algorithms. Furthermore, we describe how the conceptual framework can be applied using smart transportation system use cases, i.e., smart logistics and railway predictive maintenance. Finally, we highlighted the future direction to guide interested researchers in this interesting area. |
Language | en |
Publisher | MDPI |
Subject | Blockchain Data analysis Digital twins Industry 4.0 Logistics Railway Smart manufacturing Transportation |
Type | Article |
Issue Number | 9 |
Volume Number | 9 |
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Computer Science & Engineering [2284 items ]