Aprendizaje de sensorizado de entornos IoT mediante BeagleBone
- Alejandro Millan Del Rio 1
- José Alberto Benítez Andrades 1
- Carmen Benavides Cuellar 1
- Bruno Fernandes 2
- Fabio Silva 3
- José Luis Casteleiro Roca 4
- Isaías García Rodríguez 1
- Héctor Alaiz Moretón 1
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1
Universidad de León
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2
Universidade do Minho
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- 3 Polytechnic Institute of Porto (Portugal)
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4
Universidade da Coruña
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- Jose Luis Calvo Rolle (coord.)
- Jose Luis Casteleiro Roca (coord.)
- María Isabel Fernández Ibáñez (coord.)
- Óscar Fontenla Romero (coord.)
- Esteban Jove Pérez (coord.)
- Alberto José Leira Rejas (coord.)
- José Antonio López Vázquez (coord.)
- Vanesa Loureiro Vázquez (coord.)
- María Carmen Meizoso López (coord.)
- Francisco Javier Pérez Castelo (coord.)
- Andrés José Piñón Pazos (coord.)
- Héctor Quintián Pardo (coord.)
- Juan Manuel Rivas Rodríguez (coord.)
- Benigno Rodríguez Gómez (coord.)
- Rafael Alejandro Vega Vega (coord.)
Publisher: Servizo de Publicacións ; Universidade da Coruña
ISBN: 978-84-9749-716-9
Year of publication: 2019
Pages: 302-308
Congress: Jornadas de Automática (40. 2019. Ferrol)
Type: Conference paper
Abstract
The present work is oriented to the exploitation of the microcomputer called BeagleBone Black, and its use for learning purposes like an alternative to famous Arduino and RaspBerry PI. The work will present two basics implementations in order to demonstrate the feasibility of this solution for sensorized a domestic IoT environment. In addition. a comparison of the various existing solutions in the market is addressed.