Trustworthy Digital Twins in the Industrial Internet of Things with Blockchain

Sabah Suhail, Rasheed Hussain, Raja Jurdak, Choong Seon Hong

Research output: Contribution to journalArticle (Academic Journal)peer-review

98 Citations (Scopus)

Abstract

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 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.

Original languageEnglish
JournalIEEE Internet Computing
Early online date18 Feb 2021
DOIs
Publication statusE-pub ahead of print - 18 Feb 2021

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Blockchain
  • Data models
  • Data security and trust
  • Digital twin
  • Digital Twins (DTs)
  • Distributed databases
  • Industrial Internet of Things
  • Industrial Internet of Things (IIoT)
  • Industries
  • Monitoring
  • Sensors

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