Evaluación de AIoT en modelos computacionales en la nube y en el borde aplicado a la detección de mascarillas
Barra lateral del artículo
Publicado:
Jan 1, 2022
Palabras clave:
AIoT, COVID-19, computación en la nube, computación de borde, detección de máscara facial, YOLO
Contenido principal del artículo
Resumen
La COVID-19 ha provocado graves daños a la salud: centenas de millones de personas infectadas y varios millones de fallecidos en el mundo. Los programas de vacunación de cada Gobierno han influido en el decaimiento de estos índices, pero con la aparición de nuevas mutaciones del coronavirus más contagiosas, la preocupación sobre la efectividad de las vacunas se hace presente. Frente a esta situación el uso de mascarillas sigue siendo eficaz para prevenir la transmisión y contagio de la COVID-19. Lo que ha generado una creciente demanda de servicios de detección automática de mascarillas, que permita recordar a las personas la importancia del empleo de estas. En este trabajo se plantea un análisis del rendimiento de un sistema AIoT para la detección del uso correcto, incorrecto y sin mascarilla basado en dos modelos computacionales de Cloud y Edge, con la finalidad de determinar qué modelo se adecua mejor en un entorno real (interior y exterior) sobre la base de la confiabilidad del algoritmo, uso de recursos computacionales y tiempo de respuesta. Los resultados experimentales demuestran que el modelo computacional Edge presentó un mejor desempeño en comparación con el Cloud.
Detalles del artículo
Número
Sección
Número Especial: Uso de técnicas de ingeniería para combatir COVID-19
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El autor/es abajo firmante transfiere parcialmente los derechos de propiedad (copyright) del presente trabajo a la Universidad Politécnica Salesiana del Ecuador, para las ediciones impresas.
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El autor/es certifican que este trabajo no ha sido publicado, ni está en vías de consideración para su publicación en ninguna otra revista u obra editorial.
El autor/es se responsabilizan de su contenido y de haber contribuido a la concepción, diseño y realización del trabajo, análisis e interpretación de datos, y de haber participado en la redacción del texto y sus revisiones, así como en la aprobación de la versión que finalmente se remite en adjunto.
Referencias
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