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This study introduces a blockchain-based model to enhance the integrity and accuracy of industrial internet of things (IIoT) data. The new method processes IIoT data independently, improving operational efficiency and strategic decision-making for industrial sites.

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Area of Science:

  • Industrial Internet of Things (IIoT)
  • Blockchain Technology
  • Data Integrity

Background:

  • Industrial sites generate vast data via IIoT devices, often processed using AI.
  • Current autonomous and real-time data processing methods are expensive and inefficient.
  • A need exists for a cost-effective and reliable data processing method for industrial data.

Purpose of the Study:

  • To propose a blockchain-based Industrial Internet of Things (IIoT) information reinforcement model.
  • To ensure the integrity of IIoT data generated at industrial locations.
  • To enhance the accuracy and efficiency of industrial data processing.

Main Methods:

  • Processing IIoT data into a blockchain independently at the endpoint.
  • Optimizing information linkage by reflecting data based on attribute value frequency.
  • Dynamically aggregating related IIoT data through hierarchical subnets.

Main Results:

  • Reduced time for validating IIoT data integrity by integrating sensors directly with the blockchain.
  • Eliminated the need for extra functions in the manufacturing process.
  • Improved IIoT information accuracy by 2.5% to 3% on average.

Conclusions:

  • The proposed blockchain-based model reliably ensures IIoT data integrity.
  • The model enhances operational efficiency and strategic decision-making in industrial settings.
  • Facilitates information sharing and system connectivity between industrial locations.