Applying Intelligent Reflector Surfaces for Detecting Violent Expiratory Aerosol Cloud using Terahertz Signals
Harun \v{S}iljak, Michael Taynnan Barros, Nathan D'Arcy, Daniel Perez, Martins, Nicola Marchetti, Sasitharan Balasubramaniam

TL;DR
This paper proposes using Intelligent Reflector Surfaces emitting terahertz signals to detect respiratory aerosol clouds, extending IRS capabilities for environmental monitoring and public health applications.
Contribution
It introduces a novel approach of leveraging IRS infrastructure with terahertz signals for airborne aerosol detection, combining communication and environmental sensing.
Findings
Simulation results show promising detection accuracy.
Path optimization improves aerosol cloud localization.
Potential for integrating health monitoring into existing telecom infrastructure.
Abstract
The recent COVID-19 pandemic has driven researchers from different spectrum to develop novel solutions that can improve detection and understanding of SARS-CoV-2 virus. In this article we propose the use of Intelligent Reflector Surface (IRS) emitting terahertz signals to detect airborne respiratory aerosol cloud that are secreted from people. Our proposed approach makes use of future IRS infrastructure to extend beyond communication functionality by adding environmental scanning for aerosol clouds. Simulations have also been conducted to analyze the accuracy of aerosol cloud detection based on a signal scanning and path optimization algorithm. Utilizing IRS for detecting respiratory aerosol cloud can lead to new added value of telecommunication infrastructures for sensor monitoring data that can be used for public health.
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