A Decentralized Architecture for Industrial Data Interoperability Using Blockchain and IPFS
Bibliographic record
Abstract
Industry 5.0 demands real-time, secure, and decentralized interoperability between heterogeneous industrial systems. Existing frameworks, primarily developed for healthcare, lack the scalability and performance required for collaborative industrial environments. This paper proposes a hybrid architecture integrating the Corda permissioned blockchain with IPFS to enable traceable, content-addressed, and policy-based data exchange among autonomous actors. The system includes a modular integration layer supporting protocols like OPC UA, MQTT, and REST, and leverages specialized CorDapps for registry, access control, and auditability. Evaluated under realistic scenarios with 50,000 transactions and 2.7 GB of data, our framework outperforms centralized ESB systems, achieving a 40% reduction in data retrieval time, 99.8% availability under 30% node failure, and 37,543.4 TPS with 18.2 ms average latency, validated via Corda RPC and IPFS API logs. These results confirm the framework’s suitability for secure, resilient, and scalable data interoperability in Industry 5.0.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".