Abstract

Objective: One of the main objectives of this research is the creation of a smart system capable of dealing with the vaccine supply chain (VSC) problems while properly addressing the issues related to maintaining vaccine quality, providing accurate demand forecasting, and building stakeholder trust. These issues have been illustrated as a result of the COVID-19 pandemic.

Method: Essentially, the system that was put forward in this research efficiently brings together blockchain, the Internet of Things (IoT), and machine learning for VSC management to work well. Transparency and traceability are assured by blockchain, IoT allows for real-time monitoring, and machine learning facilitates the same through data analysis.

Outcomes: The use of blockchain for tracking combined with the IoT sensors for temperature control is the integrated system that provides for vaccine quality and safety. The machine learning models for vaccine demand prediction led to less than 3% average annual error for flu vaccine demand forecasting.

Innovation: This is the first piece of research to create a single VSC management system that blends blockchain, IoT, and machine learning. The three technologies, when working together, have a combined effect that is much larger than the sum of their individual effects and thus, lead to overcoming the main VSC challenges, particularly those that have been intensified by the COVID-19 pandemic. This system is capable of being a model that can bring about improvements in supply chain management.

Shweta Shweta

Affiliation

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Development of a smart Vaccine Supply Ecosystem Powered and experimented by hyper tuned models