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dc.contributor.authorCadavid, Héctor
dc.contributor.authorGarzón, Wilmer
dc.contributor.authorPérez, Alexander
dc.contributor.authorLópez, Germán
dc.contributor.authorMendivelso, Cristian
dc.contributor.authorRamírez, Carlos
dc.date.accessioned2021-11-04T22:01:01Z
dc.date.available2021-11-04T22:01:01Z
dc.date.issued2018
dc.identifier.isbn9783319989983
dc.identifier.isbn9783319989976
dc.identifier.urihttps://repositorio.escuelaing.edu.co/handle/001/1802
dc.description.abstractColombia is a country with a huge agricultural potential, thanks to its size and geography diversity. Unfortunately, it is far from using it efficiently: 65% of its farmland is either unused or underused due to political problems. Furthermore, vast of Colombian agriculture is characterized - when compared with other countries - by low levels of productivity, due to the lack of good farming practices and technologies. The new political framework created by the recently signed peace agreement in this country opens new opportunities to increase its agricultural vocation. However, a lot of work is still required in this country to improve the synergy between academia, industry, agricultural experts, and farmers towards improving productivity in this field. Advances in smart-farming technologies such as Remote Sensing (RS), Internet of Things (IoT), Big Data/Data Analytics and Geographic Information Systems (GIS), bring a great opportunity to contribute to such synergy. These technologies allow not only to collect and analyze data directly from the crops in real time, but to extract new knowledge from it. Furthermore, this new knowledge, combined with the knowledge of local experts, could become the core of future technical assistance and decision support systems tools for countries with a great variety of soils and tropical floors such as Colombia. Motivated by these issues, this paper proposes an extension to Thingsboard, a popular open-source IoT platform. This extended version aims to be the core of a cloud-based Smart Farming platform that will concentrate sensors, a decision support system, and a configuration of remotely controlled and autonomous devices (e.g. water dispensers, rovers or drones). The architecture of the platform is described in detail and then showcased in a scenario with simulated sensors. In such scenario early warnings of an important plant pathogen in Colombia are generated by data analytics, and actions on third-party devices are dispatched in consequence.eng
dc.format.extent15 páginas.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherSpringer Naturespa
dc.relation.ispartofseriesCCIS;Vol. 885
dc.rights© Springer Nature Switzerland AG 2018eng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.titleTowards a Smart Farming Platform: From IoT-Based Crop Sensing to Data Analyticseng
dc.typeCapítulo - Parte de Librospa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_14cbspa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.contributor.researchgroupInformáticaspa
dc.publisher.placeSwitzerland.spa
dc.relation.citationendpage851spa
dc.relation.citationstartpage237spa
dc.relation.indexedN/Aspa
dc.relation.ispartofbookCommunications in Computer and Information Scienceeng
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dc.rights.accessrightsinfo:eu-repo/semantics/closedAccessspa
dc.rights.creativecommonsAtribución 4.0 Internacional (CC BY 4.0)spa
dc.subject.proposalSmart farmingeng
dc.subject.proposalData analyticseng
dc.subject.proposalPrecision agricultureeng
dc.subject.proposalIoTeng
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/bookPartspa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa


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© Springer Nature Switzerland AG 2018
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