Applying Intelligent Reflector Surfaces for Detecting Violent Expiratory Aerosol Cloud using Terahertz Signals

Harun Šiljak, Michael Taynnan Barros, Nathan D'Arcy, Daniel Perez Martins, Nicola Marchetti, Sasitharan Balasubramaniam

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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