A Secure and Scalable Blockchain Framework for Data Sharing and Cost Distribution in Railway Condition Monitoring
Advancements in sensor technologies, remote verification systems, and high-speed data transmission networks have made remote condition monitoring (RCM) systems an essential component of the Internet of Things (IoT), revolutionizing the management and maintenance of railway infrastructure. Despite their potential, the railway industry has struggled to fully capitalize on the extensive datasets generated by RCM systems, which remain isolated within siloed platforms, limiting their broader utility and interdisciplinary applications. Recognizing this challenge, the Rail Safety and Standards Board (RSSB) initiated the T1010 research program in 2013 to promote collaboration among stakeholders and encourage data sharing within the UK rail sector. Building upon the foundational insights of the T1010 program, this study presents a blockchain-based framework incorporating smart contracts (SC) to automate, secure, and enhance agreements for sharing RCM data. The framework aims to foster innovation in collaborative business practices and create a decentralized marketplace for RCM data by replacing traditional paper-based contracts with auditable, tamper-proof smart contracts. The proposed solution offers a secure, transparent, and equitable platform for data exchange, enabling fair cost distribution among participants while eliminating reliance on a trusted third party (TTP). The developed system has been rigorously evaluated through comprehensive testing to assess its performance, focusing on key metrics such as throughput, latency, and reliability. Simulations and controlled experiments were conducted to mimic the operational environment of the railway industry, ensuring the system’s ability to handle large-scale data exchange and complex transactions in a timely and secure manner. The findings provide strong evidence of the system’s readiness for deployment in real-world scenarios and its transformative potential to revolutionize data-sharing practices, drive innovation, and enhance collaborative opportunities within the railway industry.
Authors
- John M. Easton (ORCID: https://orcid.org/0000-0001-8745-6753)
- Rahma A. Alzahrani (ORCID: https://orcid.org/0000-0003-0913-514X)
Institutions
- Imam Abdulrahman Bin Faisal University (SA)
- University of Birmingham (GB)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3603413
- Primary Topic
- Vehicle License Plate Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00