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Trustworthy digital twinning data platform for power infrastructure construction projects using blockchain and semantic web

Autor(en):
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Frontiers in Built Environment, , v. 10
DOI: 10.3389/fbuil.2024.1440513
Abstrakt:

Power infrastructure projects are characterized by complex supply chain structures and numerous stakeholders, presenting significant challenges in maintaining data integrity and ensuring seamless integration of project information. Previous Digital Twins (DTs) and Building Information Modeling (BIM) collaboration methods lack robust mechanisms for data traceability and immutable storage, leading to potential risks such as data loss or tampering. Furthermore, existing project information exchange and data management methods do not adequately integrate diverse data types, such as project documentation, onsite environment monitoring IoT sensor readings and CAD/BIM-based design information. This research introduces a novel DT data platform prototype, utilizing Blockchain and Semantic Web technologies, to establish a trustworthy DT data environment for power infrastructure projects. This system collects heterogeneous data, including manual inputs and IoT-generated data, and processes them into RDF format on dedicated devices. The integrated data is then stored on a Permissioned Blockchain, ensuring traceability and immutability. The framework incorporates Distributed File Systems to enhance storage efficiency and features a semantic gateway that transforms heterogeneous data into RDF graphs, fostering interoperability and the potential for automated data linkage. The efficacy of this prototype was demonstrated through a case study, testing data consistency and showcasing prototype queries enhanced by Semantic Web, thus substantiating the platform’s capacity to support multidisciplinary project management.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.3389/fbuil.2024.1440513.
  • Über diese
    Datenseite
  • Reference-ID
    10812641
  • Veröffentlicht am:
    17.01.2025
  • Geändert am:
    17.01.2025
 
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