Trustworthy Digital Twins in the Industrial Internet of Things with Blockchain

TL;DR

This paper proposes a blockchain-based framework for the Industrial Internet of Things that enhances data trustworthiness and integrates Digital Twins for improved process monitoring, diagnostics, and fault prevention.

Contribution

It introduces a novel integration of blockchain and Digital Twins to address data security, trust, and fault diagnosis in IIoT environments.

Findings

Blockchain ensures data integrity and security in IIoT.

Digital Twins enable predictive diagnostics and process optimization.

Framework addresses data fragmentation and untrustworthy data dissemination.

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.