Remote detection of COVID-19 using 5G and AI

Raul Zamorano-Illanes, I. Soto, W. Alavia, V. Garcia, P. Adasme, Francisco Rau
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Abstract

This work presents a novel solution for the detection of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2) that produces the disease COVID-19 from gel electrophoresis images for the application of the analysis of samples from sewage systems for the control of the pandemic, using the fifth generation mobile network (5G) and artificial intelligence (AI) for the reduction of noise in the samples and the detection of characteristic bands of the virus. It is composed of five steps, allowing to reduce the fatigue of the experts and the cost to perform the SARS-CoV-2 detection process compared to an RT-qPCR. In terms of energy savings in transmission, a gain was achieved that stops the value of a BER of $10^{-4}$, it is 0.5 dB when going from N from 64 to 128, similar for the difference from 32 to 64 and a gain of 1dB when going from N from 16 to 32, respectively.
利用5G和人工智能远程检测COVID-19
这项工作提出了一种新的解决方案,用于检测从凝胶电泳图像中产生COVID-19的严重急性呼吸综合征冠状病毒2 (SARSCoV-2),用于分析来自污水系统的样本以控制大流行,使用第五代移动网络(5G)和人工智能(AI)来降低样本中的噪声并检测病毒的特征波段。它由五个步骤组成,与RT-qPCR相比,可以减少专家的疲劳和执行SARS-CoV-2检测过程的成本。在传输节能方面,获得的增益阻止了$10^{-4}$的BER值,当N从64到128时,其值为0.5 dB,类似于从32到64的差异,以及从N从16到32时的增益为1dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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