Blockchain-Empowered Digital Twins Collaboration: Smart Transportation Use Case

Machines

卷:9

Mohsen Guizani¹  Donna O’Shea²  Kenneth N. Brown³  Radhya Sahal³  Saeed H. Alsamhi⁴  Conor McCarthy⁵ 

[1] College of Engineering, Qatar University, Doha 2713, Qatar;

[2] Department of Computer Science, Cork Institute of Technology, T12 P928 Cork, Ireland;

[3] SMART 4.0 Fellow, School of Computer Science and Information Technology, University College Cork, T12 E8YV Cork, Ireland;

[4] SMART 4.0 Fellow, Software Research Institute, Athlone Institute of Technology, N37 W089 Athlone, Ireland;

[5] School of Engineering, University of Limerick, V94 T9PX Limerick, Ireland;

关键词: blockchain;    digital twins;    Industry 4.0;    smart manufacturing;    data analysis;    transportation;   

DOI  :  10.3390/machines9090193

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown