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A Blockchain and AI Based Vaccination Tracking Framework for Coronavirus (COVID-19) Epidemics.

Authors :
Pradhan, Nihar Ranjan
Mahule, Rajesh
Wamuyu, Patrick Kanyi
Rathore, Pradeep Kumar
Singh, Akhilendra Pratap
Source :
IETE Journal of Research. Nov2023, Vol. 69 Issue 11, p7803-7815. 13p.
Publication Year :
2023

Abstract

The Coronavirus disease, i.e. (COVID-19) pandemic outbreaks has inevitably lead to a corresponding movement restrictive measure by the members of both central and state government leadership. The current limitation of healthcare systems cannot predict the COVID-19 outbreaks and vaccination drive. The need of the hour is to use Blockchain Technology for the construction of immutable ledger. In this paper a Blockchain and Artificial Intelligence (AI) enabled COVID-19 vaccine tracking system has been proposed. The proposed system is designed using the Ethereum Virtual Machine (EVM), decentralized storage by Inter Planetary File System (IPFS) and implemented using Truffle and Ganache Tool. The smart contract interaction among the entities is developed with Drizzle and the front-end using ReactJS. The performance of the proposed framework has been presented with Keccack 256 transaction hash, the total number of transactions, gas consumed by each contract. Additionally the performance parameters such as latency, throughput, traffic in, out, CPU, and memory utilization of the blockchain framework are also calculated. The artificial neural network (ANN) has been used to classify the vaccination group. Such an attempt is a worthwhile addition to the state of the art as evident from the results presented herein. The proposed framework provides a way for vaccinated members of the community to be tracked and indexed so as to avail the benefits, for example, less restrictive movements nationally, internationally, or simply in their own respective communities. This paper leverages the advantages of Blockchain Technology to obtain a reliable and accurate way to facilitate the entire tracking process. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03772063
Volume :
69
Issue :
11
Database :
Academic Search Index
Journal :
IETE Journal of Research
Publication Type :
Academic Journal
Accession number :
175825223
Full Text :
https://doi.org/10.1080/03772063.2022.2058630