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September 23, 2025PeerJ Computer Science5 citationsOpen Access

Security and privacy for Binance-based integrated blockchain for blood supply chain management systems

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CRCh. RupaSGSai Varshitha. GDDD Divya

Key Points

  • The proposed system achieved 99.5% accuracy in predicting blood availability, ensuring timely access for users.
  • Utilizing Binance blockchain technology lowers transaction fees and enhances the scalability of blood transactions.
  • The AdaBoost algorithm facilitates predictions regarding the nearest blood bank and donor, improving resource allocation.
  • Smart contracts enable secure and immutable transactions while providing transparency without third-party involvement.

Abstract

The world faces a severe blood shortage, with a gap of 1.95 million units, highlighting the need for efficient blood allocation and management systems. Traditional cloud and blockchain approaches have been explored for blood bank management but faced implementation challenges. This study proposes designing and developing a decentralized Binance blockchain-based application framework to ensure transparency and security. It uses the AdaBoost algorithm to predict the availability of the nearest blood bank and blood donor. Supply chain management provides transparency without the intervention of third parties thereby preventing blood crimes. Metamask is incorporated for crypto transactions in the Binance Smart Chain test network (BSC). BSC stands out for its low transaction fees and high scalability, enabling swift transaction processing at a fraction of the cost compared to Ethereum. The smart contracts are deployed using hardhat configuration enabling BscScan as an Application Programming Interface (API) gateway to record transactions within the decentralized application (dApp). The proposed system achieved an accuracy of 99.5%, demonstrating the robustness of the AdaBoost model in predicting blood availability. The integration of blockchain technology ensures transparency, immutability, and secure traceability of blood transactions across the network.

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Cite This Study

Rupa et al. (2025) studied this question.

synapsesocial.com/papers/68d4757f31b076d99fa6cda0https://doi.org/10.7717/peerj-cs.3123
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