PEACH: predicting frost events in peach orchards using IoT technology

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...

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Autores principales: Watteyne, Thomas, Diedrichs, Ana Laura, Brun-Laguna, Keoma, Chaar, Javier Emilio, Dujovne, Diego, Taffernaberry, Juan Carlos, Mercado, Gustavo
Formato: info:ar-repo/semantics/artículo
Lenguaje:Inglés
Publicado: EAI 2019
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/5604
https://eudl.eu/doi/10.4108/eai.1-12-2016.151711
http://dx.doi.org/10.4108/eai.1-12-2016.151711
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author Watteyne, Thomas
Diedrichs, Ana Laura
Brun-Laguna, Keoma
Chaar, Javier Emilio
Dujovne, Diego
Taffernaberry, Juan Carlos
Mercado, Gustavo
author_browse Brun-Laguna, Keoma
Chaar, Javier Emilio
Diedrichs, Ana Laura
Dujovne, Diego
Mercado, Gustavo
Taffernaberry, Juan Carlos
Watteyne, Thomas
author_facet Watteyne, Thomas
Diedrichs, Ana Laura
Brun-Laguna, Keoma
Chaar, Javier Emilio
Dujovne, Diego
Taffernaberry, Juan Carlos
Mercado, Gustavo
author_sort Watteyne, Thomas
collection INTA Digital
description 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 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.
format info:ar-repo/semantics/artículo
id INTA5604
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2019
publishDateRange 2019
publishDateSort 2019
publisher EAI
publisherStr EAI
record_format dspace
spelling INTA56042019-08-09T12:40:42Z PEACH: predicting frost events in peach orchards using IoT technology Watteyne, Thomas Diedrichs, Ana Laura Brun-Laguna, Keoma Chaar, Javier Emilio Dujovne, Diego Taffernaberry, Juan Carlos Mercado, Gustavo Durazno Helada Técnicas de Predicción Agricultura de Precisión Peaches Frost Forecasting Precision Agriculture SmartMesh IP Smart Agriculture IoT Technology 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 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. EEA Junín Fil: Watteyne, Thomas. Institut National de Recherche en Informatique et en Automatique (INRIA). EVA Team; Francia Fil: Diedrichs, Ana Laura. Universidad Tecnológica Nacional (UTN), Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Brun-Laguna, Keoma. Institut National de Recherche en Informatique et en Automatique (INRIA). EVA Team; Francia Fil: Chaar, Javier Emilio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Junín; Argentina Fil: Dujovne, Diego. Universidad Diego Portales (UDP), Santiago; Chile Fil: Taffernaberry, Juan Carlos. Universidad Tecnológica Nacional (UTN), Mendoza; Argentina Fil: Mercado, Gustavo. Universidad Tecnológica Nacional (UTN), Mendoza; Argentina 2019-08-09T12:28:59Z 2019-08-09T12:28:59Z 2016 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/5604 https://eudl.eu/doi/10.4108/eai.1-12-2016.151711 2414-1399 http://dx.doi.org/10.4108/eai.1-12-2016.151711 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf EAI EAI endorsed transactions on Internet of things 2 (5) : e2 (2016)
spellingShingle Durazno
Helada
Técnicas de Predicción
Agricultura de Precisión
Peaches
Frost
Forecasting
Precision Agriculture
SmartMesh IP
Smart Agriculture
IoT Technology
Watteyne, Thomas
Diedrichs, Ana Laura
Brun-Laguna, Keoma
Chaar, Javier Emilio
Dujovne, Diego
Taffernaberry, Juan Carlos
Mercado, Gustavo
PEACH: predicting frost events in peach orchards using IoT technology
title PEACH: predicting frost events in peach orchards using IoT technology
title_full PEACH: predicting frost events in peach orchards using IoT technology
title_fullStr PEACH: predicting frost events in peach orchards using IoT technology
title_full_unstemmed PEACH: predicting frost events in peach orchards using IoT technology
title_short PEACH: predicting frost events in peach orchards using IoT technology
title_sort peach predicting frost events in peach orchards using iot technology
topic Durazno
Helada
Técnicas de Predicción
Agricultura de Precisión
Peaches
Frost
Forecasting
Precision Agriculture
SmartMesh IP
Smart Agriculture
IoT Technology
url http://hdl.handle.net/20.500.12123/5604
https://eudl.eu/doi/10.4108/eai.1-12-2016.151711
http://dx.doi.org/10.4108/eai.1-12-2016.151711
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