Mejoramiento del algoritmo ADR en una red de internet de las cosas LoRaWAN usando aprendizaje de máquina

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

Resumen

The Internet of Things (IoT) is an enabling paradigm for Industry 4.0, where sensors and actuators connect to the Internet. The protocol LoRaWAN (Long Range Area Network) is one of the most used in the IoT, and its primary objective is to transmit sensor information over long distances with minimal energy consumption. This protocol implements Adaptive Data Rate scheme to optimize the energy consumed per node, which, when evaluated through exhaustive simulations in Omnet ++, has exhibited opportunities for improvement in convergence time. The present work shows machine learning models based on parametric and non-parametric methods based on Support Vector Machines (SVM) and Artificial Neural Networks (ANN). The results indicate that the SVM and ANN methods have a success rate greater than 90% in the estimated parameters.

Título traducido de la contribuciónImprovement of the algorithm ADR in an internet of things network LoRaWAN by using machine learning
Idioma originalEspañol
Páginas (desde-hasta)67-83
Número de páginas17
PublicaciónRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volumen2020
N.º39
DOI
EstadoPublicada - oct 2020

Palabras clave

  • Energy consumption
  • Industry 4.0
  • Internet of Things
  • LoRaWAN
  • Machine Learning

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