Issue |
E3S Web Conf.
Volume 564, 2024
International Conference on Power Generation and Renewable Energy Sources (ICPGRES-2024)
|
|
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Article Number | 07005 | |
Number of page(s) | 5 | |
Section | Signal Processing | |
DOI | https://doi.org/10.1051/e3sconf/202456407005 | |
Published online | 06 September 2024 |
Blockchain-Based Solution for Mitigating Overproduction and Underproduction of Medical Supplies
1 M-Tech in CSE, School of CSE, REVA University, Bangalore, India
2 Associate Professor, School of CSE, REVA University, Bangalore, India
Overproduction and underconsumption of medical goods have led to billions of dollars in losses over the past decade. The lack of accountability, transparency, traceability, auditing, assessment, security, and trust in the current healthcare supply chain system typically causes these issues. It is crucial to prevent unnecessary waste and ensure equitable distribution of medical supplies. In this paper, we propose a blockchain-based approach that ensures the accountability and dedication of all participants to prevent excess waste. We introduce five phases for accurate and fair waste assessment: production, delivery, consumption, commitment, and registration. We developed four smart contracts that automatically record all activities on an immutable ledger, ensuring data provenance, transparency, security, and accountability. To address the issue of massive data storage, we use off-chain decentralized storage. We detail five methods and thoroughly explain each step of the proposed solution, including testing, validation, and full implementation. To ensure our smart contracts are secure and free from vulnerabilities, we perform security analyses. The code for the smart contracts is available to the public on GitHub..
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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