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The global vaccine supply chain faces significant challenges, including ensuring vaccine quality, accurate demand forecasting, and fostering trust among stakeholders. Traditional systems struggle with data integrity, real-time monitoring, and efficient inventory management, particularly during crises. To address these issues, an innovative approach integrating blockchain, Internet of Things (IoT), and machine learning is proposed. This study leverages the transparency and immutability of blockchain technology to enhance data integrity and stakeholder trust. IoT devices are employed for real-time monitoring of vaccine conditions, ensuring quality is maintained throughout the supply chain. Advanced machine learning algorithms, specifically convolutional neural networks (CNN) and bidirectional long short-term memory (BiLSTM), are utilized for accurate demand forecasting. These technologies collectively aim to optimize inventory management and distribution processes. The integration of blockchain ensures that all data within the vaccine supply chain is transparent and tamper-proof, significantly improving trust among stakeholders. IoT-enabled real-time monitoring provides continuous oversight of vaccine conditions, preventing quality degradation. Machine learning models, particularly CNN and BiLSTM, enhance demand forecasting accuracy, resulting in more efficient inventory management and equitable distribution. This approach addresses critical inefficiencies and provides robust decision support during crises. The proposed intelligent vaccine supply chain management system, integrating blockchain, IoT, and machine learning, offers a transformative solution to current challenges. By ensuring data integrity, real-time quality monitoring, and precise demand forecasting, this system enhances the efficiency and reliability of vaccine distribution. Ultimately, it promises to mitigate supply chain inefficiencies, ensuring timely and equitable vaccine access, thereby supporting global health, economic stability, and social well-being.

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Blockchain and IoT-Driven Vaccine Supply Chains Promoting Secure and Transference with Machine Learning-Enhanced Demand Forecasting

  • 会议论文

  • 发表日期：

    2026年

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  • Akshay Kumar Karlapati,
  • Ramesh Karnati,
  • K. L. Raghavender Reddy,
  • R. Uma Mageswari

摘要

The global vaccine supply chain faces significant challenges, including ensuring vaccine quality, accurate demand forecasting, and fostering trust among stakeholders. Traditional systems struggle with data integrity, real-time monitoring, and efficient inventory management, particularly during crises. To address these issues, an innovative approach integrating blockchain, Internet of Things (IoT), and machine learning is proposed. This study leverages the transparency and immutability of blockchain technology to enhance data integrity and stakeholder trust. IoT devices are employed for real-time monitoring of vaccine conditions, ensuring quality is maintained throughout the supply chain. Advanced machine learning algorithms, specifically convolutional neural networks (CNN) and bidirectional long short-term memory (BiLSTM), are utilized for accurate demand forecasting. These technologies collectively aim to optimize inventory management and distribution processes. The integration of blockchain ensures that all data within the vaccine supply chain is transparent and tamper-proof, significantly improving trust among stakeholders. IoT-enabled real-time monitoring provides continuous oversight of vaccine conditions, preventing quality degradation. Machine learning models, particularly CNN and BiLSTM, enhance demand forecasting accuracy, resulting in more efficient inventory management and equitable distribution. This approach addresses critical inefficiencies and provides robust decision support during crises. The proposed intelligent vaccine supply chain management system, integrating blockchain, IoT, and machine learning, offers a transformative solution to current challenges. By ensuring data integrity, real-time quality monitoring, and precise demand forecasting, this system enhances the efficiency and reliability of vaccine distribution. Ultimately, it promises to mitigate supply chain inefficiencies, ensuring timely and equitable vaccine access, thereby supporting global health, economic stability, and social well-being.