kumoh national institute of technology
Networked Systems Lab.

Simeon Okechukwu Ajakwe, Igboanusi Ikechi Saviour, Love Allen Chijioke Ahakonye, Dong-Seong Kim, Jae-Min Lee, ITCM: IT Convergence Model for Real-Time Ubiquitous Vaccination Verification and Authentication, Computer Networks (Pr)
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Date : 2021-09-16
Views : 216

This paper proposed an IT-convergence solution that
fuses Blockchain and Artificial Intelligence model to distinguish
between vaccinated and non-vaccinated individuals in real-time
scenarios and initiate strict and appropriate compliance directives; denial or access to certain places. The proposed system
design is a fusion of facial recognition, mask wearing detection
technology using Yolov5 deep learning model, network-based
vaccination record management application, biometric featurebased vaccination status validation, and compliance enforcement
in real-time. Blockchain technology was introduced at backend to ensure data trust. To test system performance, various
datasets were used for detection, recognition, and prediction.
The system achieved 99.5% accurate detection and 100% realtime authentications with minimal computational complexities
while maintaining data trust through secured network. This
innovation guarantee real-time and seamless monitoring of vaccination progress and curtailment of COVID-19 spread through
compliance enforcement.