Selection of LPWAN Technology for the Adoption and Efficient Use of the IoT in the Rural Areas of the Province of Guayas Using AHP Method

Miguel Angel Quiroz Martinez, Gonzalo Antonio Loza González, Monica Daniela Gomez Rios, Maikel Yelandi Leyva Vazquez

Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

Ecuador, being a developing country, depends on the search and implementation of new technologies that help improve the productive matrix, this is the case of the agricultural sector, driven by the growth of the Internet market. Internet of Things (IoT) Low-power wide-area network (LPWAN) has allowed its expansion in underdeveloped countries. Sigfox, LoRa, and NB-IoT are the three leading LPWAN technologies that compete for large-scale IoT implementation. This document provides a comparative study of these technologies, focused on the livestock sector. Basic criteria are identified to facilitate decision making when using IoT technology for the development of livestock in rural areas of Guayas province. Through the analytical hierarchical process(AHP), the type of technologies to be implemented is ranked and selected.

Idioma originalInglés
Título de la publicación alojadaAdvances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2020 Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing
EditoresTareq Ahram
EditorialSpringer
Páginas497-503
Número de páginas7
ISBN (versión impresa)9783030513276
DOI
EstadoPublicada - 2021
EventoAHFE Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, 2020 - San Diego, Estados Unidos
Duración: 16 jul. 202020 jul. 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1213 AISC
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

ConferenciaAHFE Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, 2020
País/TerritorioEstados Unidos
CiudadSan Diego
Período16/07/2020/07/20

Nota bibliográfica

Funding Information:
This work has been supported by the GIIAR research group and the Salesian Polytechnic University of Guayaquil.

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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