A Reliable and Efficient Tracking System Based on Deep Learning for Monitoring the Spread of COVID-19 in Closed Areas

Radwa Ahmed Osman,Yasmine N M Saleh,Mazen Nabil Elagamy,Sherine Nagy Saleh

doi:10.3390/ijerph182412941

Abstract

Since 2020, the world is still facing a global economic and health crisis due to the COVID-19 pandemic. One approach to fighting this global crisis is to track COVID-19 cases by wireless technologies, which requires receiving reliable, efficient, and accurate data. Consequently, this article proposes a model based on Lagrange optimization and a distributed deep learning model to assure that all required data for tracking any suspected COVID-19 patient is received efficiently and reliably. Finding the optimum location of the Radio Frequency Identifier (RFID) reader relevant to the base station results in the reliable transmission of data. The proposed deep learning model, developed using the one-dimensional convolutional neural network and a fully connected network, resulted in lower mean absolute squared errors when compared to state-of-the-art regression benchmarks. The proposed model based on Lagrange optimization and deep learning algorithms is evaluated when changing different network parameters, such as requiring signal-to-interference-plus-noise-ratio, reader transmission power, and the required system quality-of-service. The analysis of the obtained results, which indicates the appropriate transmission distance between an RFID reader and a base station, shows the effectiveness and the accuracy of the proposed approach, which leads to an easy and efficient tracking system.

Highlights

There is no doubt that the world has been facing one of its biggest challenges since the World Health Organization (WHO) declared coronavirus disease (COVID-19) as an epidemic in December 2019 [1]
COVID-19 is caused by a coronavirus known as severe acute respiratory syndrome two (SARS-CoV-2), which was first identified in Wuhan, China [1,3,4]
Reader with respect to the base station (BS) to achieve reliable, efficient, and accurate data. It has been shown from the obtained results from analytical and deep learning that the proposed approach can exhibit the best performance under the different channel and environmental conditions

Summary

Introduction

There is no doubt that the world has been facing one of its biggest challenges since the World Health Organization (WHO) declared coronavirus disease (COVID-19) as an epidemic in December 2019 [1] The consequences of this epidemic did not affect only the health domain, and many areas such as the economy, education, and technology [2]. COVID-19 is caused by a coronavirus known as severe acute respiratory syndrome two (SARS-CoV-2), which was first identified in Wuhan, China [1,3,4]. It is not a new disease, but it is the evolution of an older virus known as SARS-CoV that was discovered in.

Methods

Results

Discussion

Conclusion