Blockchain-based Digital Twins: Research Trends, Issues, and Future Challenges
Sabah Suhail, Rasheed Hussain, Raja Jurdak, Alma Oracevic, Khaled, Salah, Raimundas Matulevi\v{c}ius, and Choong Seon Hong

TL;DR
This paper reviews the integration of blockchain technology with Digital Twins in industrial settings, emphasizing trustworthiness, data integrity, and AI-driven insights, while discussing current challenges and future research directions.
Contribution
It provides a comprehensive survey of blockchain-based Digital Twins, highlighting their benefits, current research trends, and proposing a framework for trustworthy implementation.
Findings
Blockchain enhances data trustworthiness in Digital Twins.
AI plays a crucial role in analyzing blockchain-enabled Digital Twins.
Identifies key challenges and future research directions for blockchain-based Digital Twins.
Abstract
Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of trustworthy data. For the physical data to be trustworthy, it needs to be cross-validated through multiple sensor sources with overlapping fields of view. Cross-validated data can then be stored on the blockchain, to maintain its integrity and trustworthiness. Once trustworthy data is recorded on the blockchain, product lifecycle events can be fed into data-driven systems for process monitoring, diagnostics, and optimized control. In this regard, Digital Twins (DTs) can be leveraged to draw intelligent conclusions from data by identifying the faults and recommending precautionary measures ahead of critical events. Empowering DTs with blockchain in…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Digital Transformation in Industry · IoT and Edge/Fog Computing
