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Performance evaluation of edge-computing platforms for the prediction of low temperatures in agriculture using deep learning

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Performance evaluation of edge-computing platforms for the prediction of low temperatures in agriculture using deep learning

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Guillén-Navarro, MA.; Llanes, A.; Imbernón, B.; Martínez-España, R.; Bueno-Crespo, A.; Cano, J.; Cecilia-Canales, JM. (2021). Performance evaluation of edge-computing platforms for the prediction of low temperatures in agriculture using deep learning. The Journal of Supercomputing. 77:818-840. https://doi.org/10.1007/s11227-020-03288-w

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/196324

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Título: Performance evaluation of edge-computing platforms for the prediction of low temperatures in agriculture using deep learning
Autor: Guillén-Navarro, Miguel A. Llanes, Antonio Imbernón, Baldomero Martínez-España, Raquel Bueno-Crespo, Andrés Cano, Juan-Carlos Cecilia-Canales, José María
Entidad UPV: Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Fecha de fin de embargo: 1999-01-01
Resumen:
[EN] The Internet of Things (IoT) is driving the digital revolution. AlSome palliative measures aremost all economic sectors are becoming "Smart" thanks to the analysis of data generated by IoT. This analysis is carried ...[+]
Palabras clave: Edge computing , LSTM , Deep learning , Precision Agriculture
Derechos de uso: Reserva de todos los derechos
Fuente:
The Journal of Supercomputing. (issn: 0920-8542 )
DOI: 10.1007/s11227-020-03288-w
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s11227-020-03288-w
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096384-B-I00/ES/SOLUCIONES PARA UNA GESTION EFICIENTE DEL TRAFICO VEHICULAR BASADAS EN SISTEMAS Y SERVICIOS EN RED/
info:eu-repo/grantAgreement/AGENCIA ESTATAL DE INVESTIGACION//RTC-2017-6389-5-AR//PLANIFICACIÓN Y GESTIÓN DE RECURSOS HÍDRICOS A PARTIR DE ANÁLISIS DE DATOS DE IOT/
info:eu-repo/grantAgreement/f SéNeCa//20813%2FPI%2F18/
Agradecimientos:
This work was partially supported by the Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia under Project 20813/PI/18, and by Spanish Ministry of Science, Innovation and Universities ...[+]
Tipo: Artículo

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