Internet of medical things and coding as a service (IoMTCaaS) for monitoring people affected by Covid-19

Autores/as

  • Yair Rivera Corporación Universitaria Americana
  • Elmer Vega Corporación Universitaria Americana
  • Enrique Jonathan Peña Cantillo Corporación Universitaria Americana

Palabras clave:

Middleware, RLNC, Random Lineal Network Coding, IoMT, Internet of Medical Things, COVID-19, 5G-IoT

Resumen

Con la necesidad cada vez mayor de recursos computacionales y de transferencia de datos que exigen los servicios de telemedicina, no es realista que los dispositivos médicos móviles (IoMT, Internet of Medical Things) locales (con fuentes limitadas) implementen el procesamiento intenso de la información a gran escala para el envío continuo de los datos sobre una red inalámbrica móvil. Hablamos de la adquisición y envío de datos sanitarios móviles a través de gadgets médicos wearables y de la aplicación de estos datos en la monitorización de diversas condiciones de salud, especialmente en pacientes afectados por el COVID-19 en áreas remotas y de difícil acceso. Un monitoreo remoto permite la obtención de variables biométricas como el nivel de oxigeno en sangre, el ECG, la presión sanguínea, el asma, etc. y otros servicios relacionados con la atención medica como la videoconferencia. El rendimiento del sistema es muy importante para el sistema de salud móvil basado en el IoT. Por ello, los particulares o las empresas se inclinan por externalizar sus necesidades de envío de datos y generación de servicio a través de soluciones cerradas que exigen un consumo significativo del ancho de banda. Sin embargo, con la gran cantidad de recursos compartidos en el ancho de banda, la externalización conlleva a problemas de retardo y rendimiento del sistema, lo que hace que se genere un aumento del consumo energético producto de los errores del sistema, algo no ideal para dispositivos IoT. Recientemente, se han llevado a cabo numerosos trabajos basados en la codificación distribuida de ultima generación en la universidad americana. El objetivo es desarrollar un mecanismo (Middleware) complementario de codificación (RLNC, Random Lineal Network Coding) controlado desde la capa de aplicación, el cual permite reducir los errores del sistema y por consiguiente minimizar los tiempos de la comunicación en dispositivos médicos 5G-IoT. El esquema planteado basado en los códigos rateless, es un proceso de baja complejidad que permite subsanar fallas originadas por las variaciones del canal inalámbrico, como consecuencia garantiza un mínimo retardo sobre la red, especialmente en aquellas con poca cobertura, ubicadas en zonas remotas y de difícil acceso.

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Biografía del autor/a

Yair Rivera, Corporación Universitaria Americana

PhD Candidate in Computer science.
Master in Telematics Engineering

Advanced knowledge in the following areas:

1. Smart devices, including Android Raspberry Pi with Python, play the core role of user interaction and integrate with the embedded sensors or wearable accessories based on Arduino for environment detection.

2. Cloud/Fog clusters based on Hadoop provide highly-efficient computing power and storage for huge data, such as HDFS and SQL/NoSQL databases. Then, intelligent algorithms can be used to data analysis and decision support.

3. Heterogeneous mobile access technologies : - Data collection from sensors by means of a wireless sensor network (WSN), - information exchange between backhaul and end terminals using peer to peer (P2P) and content delivery network (CDN), or - interconnection inside the cloud cluster, e.g., software defined network (SDN) and then achieve autonomous machine-to-machine (M2M) communication.

4. Network applications and services are developed and optimized through Network Coding (RLNC, Fulcrum Code and Sparse network Coding). In addition to traditional web-based and multimedia streaming services, location-based service (LBS) exploiting user geographical location and healthcare service according user behavior or vital signs are also considered as the next-generation killer applications of IoT.

5. Code theory and programming of cryptographic algorithms with python and mobile devices: Arduino, Raspberry PI. Etc

6.Design and development of IoT Networks: LoRa, Sig-fox, NB-IoT

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Publicado

07-09-2022

Cómo citar

[1]
Y. Rivera, E. Vega, y E. J. . Peña Cantillo, «Internet of medical things and coding as a service (IoMTCaaS) for monitoring people affected by Covid-19», EIEI ACOFI, sep. 2022.