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

作     者：Siljak, Harun Barros, Michael Taynnan D'Arcy, Nathan Martins, Daniel Perez Marchetti, Nicola Balasubramaniam, Sasitharan 

作者机构：Trinity Coll Dublin SFI CONNECT Res Ctr Dublin D02PN40 Ireland Univ Essex Sch Comp Sci & Elect Engn Colchester CO4 3SQ England South East Technol Univ Walton Inst SFI VistaMilk Res Ctr Waterford X91 P20H Ireland Univ Nebraska Sch Comp Lincoln NE 68583 USA 

出 版 物：《IEEE NETWORK》 (IEEE Network)

年 卷 期：2023年第37卷第5期

页      面：56-63页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Science Foundation Ireland (SFI) Department of Agriculture, Food, and Marine of the Government of Ireland-VistaMilk Research Centre [16/RC/3835] European Regional Development Fund for the CONNECT Research Centre [13/RC/2077_2] 

主　　题：Cloud computing Aerosols Absorption Sensors Wireless communication Atmospheric modeling Attenuation Terahertz communications Public healthcare COVID-19 Viruses (medical) Path planning Optimization methods Detection algorithms 

摘      要：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) and terahertz communication systems to detect violent expiratory 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 violent expiratory aerosol cloud can lead to new added value of telecommunication infrastructures for sensor monitoring data that can be used for public health.