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

    102 Citations (Scopus)
    2 Downloads (Pure)

    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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