A blockchain-enabled machine learning mask detection method for prevention of pandemic diseases | VAWKUM Transactions on Computer Sciences 2023

Author(s)

Anwar Ali Sathio Department of CS& IT, Benazir Bhutto Shaheed University,Karachi,Sindh,Pakistan

Dr. Shafique Ahmed Awan Department of CS& IT, Benazir Bhutto Shaheed University,Karachi,Sindh,Pakistan

Ali Orangzeb Panhwar Department of CS, Shaheed Zulfiqar Ali Bhutto Institute of Science& Technologies(SZABIST) Gharo,Sindh,Pakistan

Ali Muhammad Aamir Department of CS& IT, Benazir Bhutto Shaheed University,Karachi,Sindh,Pakistan

Ariz Muhammad Brohi Department of CS& IT, Benazir Bhutto Shaheed University,Karachi,Sindh,Pakistan

Asadullah Burdi Institute of Mathematics and Computer Science (IMCS), University of Sindh Jamshoro,Sindh,Pakistan

Abstract

During the COVID-19 pandemic, finding efective methods to prevent the spread of infectious diseases has become critical. One important measure for reducing the transmission of airborne viruses is wearing face masks but enforcing mask-wearing regulations can be difficult in many settings. Real-time and accurate monitoring of mask usage is needed to address this challenge. To do so, we propose a method for mask detection using a Convolutional Neural Network (CNN) and Blockchain Technology. Our system involves training a CNN model on a Dataset of images of people with and without masks and then deploying it on IoT-enabled devices for real-time monitoring. The use of Blockchain Technology ensures the security and privacy of the data and enables the efficient sharing of resources among network participants. Our proposed system achieved 99 percent accuracy through CNN training and was transformed into a Blockchain-enabled network mechanism with QR validation of every node for authentication. This approach can potentially be an efective tool for promoting compliance with maskwearing regulations and reducing the risk of infection. We present a framework for implementing this technique and discuss its potential benefits and challenges.

Publication Details

Page(s) 165-183

DOI DOI not available

Published Journal: VAWKUM Transactions on Computer Sciences, Volume: 11, Issue: 1, Year: 2023

Keywords

COVID19 Machine learning Covid19 method face Mask Detection Blockchain

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