Remote detection of COVID-19 using 5G and AI

Raul Zamorano-Illanes; Ismael Soto; Alavia, Wilson; Verónica García Mena; Pablo Adasme; Francisco Rau; IEEE


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.

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Fecha de publicación: 2022
Año de Inicio/Término: 2022/7/20
Página de inicio: 395
Página final: 400
Idioma: english
URL: 10.1109/CSNDSP54353.2022.9907995