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Abstract
In 2013, 85% of the peach production in the Mendoza region (Argentina) was lost because of frost. In a couple of hours, farmers can lose everything. Handling a frost event is possible, but it is hard to predict when it is going to happen. The goal of the PEACH project is to predict frost events by analyzing measurements from sensors deployed around an orchard. This article provides an in-depth description of a complete solution we designed and [ver mas...]
dc.contributor.authorWatteyne, Thomas
dc.contributor.authorDiedrichs, Ana Laura
dc.contributor.authorBrun-Laguna, Keoma
dc.contributor.authorChaar, Javier Emilio
dc.contributor.authorDujovne, Diego
dc.contributor.authorTaffernaberry, Juan Carlos
dc.contributor.authorMercado, Gustavo
dc.date.accessioned2019-08-09T12:28:59Z
dc.date.available2019-08-09T12:28:59Z
dc.date.issued2016
dc.identifier.issn2414-1399
dc.identifier.otherhttp://dx.doi.org/10.4108/eai.1-12-2016.151711
dc.identifier.urihttp://hdl.handle.net/20.500.12123/5604
dc.identifier.urihttps://eudl.eu/doi/10.4108/eai.1-12-2016.151711
dc.description.abstractIn 2013, 85% of the peach production in the Mendoza region (Argentina) was lost because of frost. In a couple of hours, farmers can lose everything. Handling a frost event is possible, but it is hard to predict when it is going to happen. The goal of the PEACH project is to predict frost events by analyzing measurements from sensors deployed around an orchard. This article provides an in-depth description of a complete solution we designed and deployed: the low-power wireless network and the back-end system. The low-power wireless network is composed entirely of commercial off-the-shelf devices. We develop a methodology for deploying the network and present the open-source tools to assist with the deployment and to monitor the network. The deployed low-power wireless mesh network is 100% reliable, with end-to-end latency below 2 s, and over 3 years of battery lifetime. This article discusses how the technology used is the right one for precision agriculture applications.eng
dc.formatapplication/pdfeng
dc.language.isoeng
dc.publisherEAI
dc.rightsinfo:eu-repo/semantics/openAccesseng
dc.sourceEAI endorsed transactions on Internet of things 2 (5) : e2 (2016)eng
dc.subjectDuraznoes_AR
dc.subjectPeacheseng
dc.subjectHeladaes_AR
dc.subjectFrosteng
dc.subjectTécnicas de Predicciónes_AR
dc.subjectForecastingeng
dc.subjectPrecision Agricultureeng
dc.subjectAgricultura de Precisiónes_AR
dc.subject.otherSmartMesh IPeng
dc.subject.otherSmart Agricultureeng
dc.subject.otherIoT Technologyeng
dc.titlePEACH: predicting frost events in peach orchards using IoT technologyeng
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.description.origenEEA Junínes_AR
dc.description.filFil: Watteyne, Thomas. Institut National de Recherche en Informatique et en Automatique (INRIA). EVA Team; Franciaes_AR
dc.description.filFil: Diedrichs, Ana Laura. Universidad Tecnológica Nacional (UTN), Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Brun-Laguna, Keoma. Institut National de Recherche en Informatique et en Automatique (INRIA). EVA Team; Franciaes_AR
dc.description.filFil: Chaar, Javier Emilio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Junín; Argentinaes_AR
dc.description.filFil: Dujovne, Diego. Universidad Diego Portales (UDP), Santiago; Chilees_AR
dc.description.filFil: Taffernaberry, Juan Carlos. Universidad Tecnológica Nacional (UTN), Mendoza; Argentinaes_AR
dc.description.filFil: Mercado, Gustavo. Universidad Tecnológica Nacional (UTN), Mendoza; Argentinaes_AR
dc.subtypecientifico


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