A high-performance IoT solution to reduce frost damages in stone fruits

[EN] Agriculture is one of the key sectors where technology is opening new opportunities to break up the market. The Internet of Things (IoT) could reduce the production costs and increase the product quality by providing intelligence services via IoT analytics. However, the hard weather conditions...

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Detalles Bibliográficos
Autores: Guillén-Navarro, Miguel A., Martínez-España, Raquel, López, Belén, Cecilia-Canales, José María|||0000-0001-5648-214X
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/182445
Acceso en línea:https://riunet.upv.es/handle/10251/182445
Access Level:acceso abierto
Palabra clave:Edge computing
Frost crops
GPUs
IoT system
Precision agriculture
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
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spelling A high-performance IoT solution to reduce frost damages in stone fruitsGuillén-Navarro, Miguel A.Martínez-España, RaquelLópez, BelénCecilia-Canales, José María|||0000-0001-5648-214XEdge computingFrost cropsGPUsIoT systemPrecision agricultureARQUITECTURA Y TECNOLOGIA DE COMPUTADORES[EN] Agriculture is one of the key sectors where technology is opening new opportunities to break up the market. The Internet of Things (IoT) could reduce the production costs and increase the product quality by providing intelligence services via IoT analytics. However, the hard weather conditions and the lack of connectivity in this field limit the successful deployment of such services as they require both, ie, fully connected infrastructures and highly computational resources. Edge computing has emerged as a solution to bring computing power in close proximity to the sensors, providing energy savings, highly responsive web services, and the ability to mask transient cloud outages. In this paper, we propose an IoT monitoring system to activate anti-frost techniques to avoid crop loss, by defining two intelligent services to detect outliers caused by the sensor errors. The former is a nearest neighbor technique and the latter is the k-means algorithm, which provides better quality results but it increases the computational cost. Cloud versus edge computing approaches are analyzed by targeting two different low-power GPUs. Our experimental results show that cloud-based approaches provides highest performance in general but edge computing is a compelling alternative to mask transient cloud outages and provide highly responsive data analytic services in technologically hostile environments.This work was partially supported by the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia under Project 20813/PI/18, and by Spanish Ministry of Science, Innovation and Universities under grants TIN2016-78799-P (AEI/FEDER, UE) and RTC-2017-6389-5. Finally, we thank the farmers for the availability of their resources to be able to asses and improve the IoT monitoring system proposed.John Wiley & SonsDepartamento de Informática de Sistemas y ComputadoresEscuela Técnica Superior de Ingeniería InformáticaGrupo de Redes de ComputadoresAGENCIA ESTATAL DE INVESTIGACIONEuropean Regional Development FundMinisterio de Ciencia, Innovación y UniversidadesFundación Séneca-Agencia de Ciencia y Tecnología de la Región de MurciaRepositorio Institucional de la Universitat Politècnica de València Riunet20212021-01-25journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/182445reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengFundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia https://doi.org/10.13039/100007801 20813%2FPI%2F18Ministerio de Ciencia, Innovación y Universidades https://doi.org/10.13039/100014440 TIN2016-78799-PAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 RTC-2017-6389-5-AR PLANIFICACIÓN Y GESTIÓN DE RECURSOS HÍDRICOS A PARTIR DE ANÁLISIS DE DATOS DE IOTopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1824452026-06-13T07:49:27Z
dc.title.none.fl_str_mv A high-performance IoT solution to reduce frost damages in stone fruits
title A high-performance IoT solution to reduce frost damages in stone fruits
spellingShingle A high-performance IoT solution to reduce frost damages in stone fruits
Guillén-Navarro, Miguel A.
Edge computing
Frost crops
GPUs
IoT system
Precision agriculture
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
title_short A high-performance IoT solution to reduce frost damages in stone fruits
title_full A high-performance IoT solution to reduce frost damages in stone fruits
title_fullStr A high-performance IoT solution to reduce frost damages in stone fruits
title_full_unstemmed A high-performance IoT solution to reduce frost damages in stone fruits
title_sort A high-performance IoT solution to reduce frost damages in stone fruits
dc.creator.none.fl_str_mv Guillén-Navarro, Miguel A.
Martínez-España, Raquel
López, Belén
Cecilia-Canales, José María|||0000-0001-5648-214X
author Guillén-Navarro, Miguel A.
author_facet Guillén-Navarro, Miguel A.
Martínez-España, Raquel
López, Belén
Cecilia-Canales, José María|||0000-0001-5648-214X
author_role author
author2 Martínez-España, Raquel
López, Belén
Cecilia-Canales, José María|||0000-0001-5648-214X
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Informática de Sistemas y Computadores
Escuela Técnica Superior de Ingeniería Informática
Grupo de Redes de Computadores
AGENCIA ESTATAL DE INVESTIGACION
European Regional Development Fund
Ministerio de Ciencia, Innovación y Universidades
Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Edge computing
Frost crops
GPUs
IoT system
Precision agriculture
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
topic Edge computing
Frost crops
GPUs
IoT system
Precision agriculture
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
description [EN] Agriculture is one of the key sectors where technology is opening new opportunities to break up the market. The Internet of Things (IoT) could reduce the production costs and increase the product quality by providing intelligence services via IoT analytics. However, the hard weather conditions and the lack of connectivity in this field limit the successful deployment of such services as they require both, ie, fully connected infrastructures and highly computational resources. Edge computing has emerged as a solution to bring computing power in close proximity to the sensors, providing energy savings, highly responsive web services, and the ability to mask transient cloud outages. In this paper, we propose an IoT monitoring system to activate anti-frost techniques to avoid crop loss, by defining two intelligent services to detect outliers caused by the sensor errors. The former is a nearest neighbor technique and the latter is the k-means algorithm, which provides better quality results but it increases the computational cost. Cloud versus edge computing approaches are analyzed by targeting two different low-power GPUs. Our experimental results show that cloud-based approaches provides highest performance in general but edge computing is a compelling alternative to mask transient cloud outages and provide highly responsive data analytic services in technologically hostile environments.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-25
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/182445
url https://riunet.upv.es/handle/10251/182445
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia https://doi.org/10.13039/100007801 20813%2FPI%2F18
Ministerio de Ciencia, Innovación y Universidades https://doi.org/10.13039/100014440 TIN2016-78799-P
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 RTC-2017-6389-5-AR PLANIFICACIÓN Y GESTIÓN DE RECURSOS HÍDRICOS A PARTIR DE ANÁLISIS DE DATOS DE IOT
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons
publisher.none.fl_str_mv John Wiley & Sons
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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