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Towards Digital Twins for Multi-Sensor Land and Plant Monitoring

2022Artigo científico Acesso aberto
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dc.contributor.authorMadeira, Rui Neves
dc.contributor.authorSantos, Pedro Albuquerque
dc.contributor.authorJava, Oskars
dc.contributor.authorPriebe, Torsten
dc.contributor.authorGraça, Eduardo
dc.contributor.authorSarközi, Eszter
dc.contributor.authorAsprion, Bernward
dc.contributor.authorGomez, Raquel Pinto Bello
dc.contributor.institutionNOVALincs
dc.contributor.pblElsevier
dc.date.accessioned2026-01-14T10:47:39Z
dc.date.available2026-01-14T10:47:39Z
dc.date.issued2022
dc.descriptionFunding Information: This work was supported by the project E3UDRES2 - Engaged and Entrepreneurial European University as Driver for European Smart and Sustainable Regions (GA 101004069), co-funded by the Erasmus+ Programme of the European Union. The content of this paper represents the views of the authors only and is their sole responsibility. The European Commission and the Agency do not accept any responsibility for use that may be made of the information it contains. Publisher Copyright: © 2022 Elsevier B.V.. All rights reserved.
dc.description.abstractSmall and medium-sized farms struggle with increased needs for monitoring in different dimensions, even by having to respond to regulatory requirements, e.g., by the global push to reduce pesticides and to improve soil health. Moreover, with the rising needs for food production there has been an effort to shift agriculture into a new era, in which the sector needs to be modernized by using new digital technologies. The goal of our research work is to provide farmers with a reliable "digital twin", i.e., a monitoring ecosystem that allows them to visualize multi-sensor data collected from their fields, but also to "plug in" predictive models, e.g., for plant disease prediction. The paper presents an extensible solution, designed in co-creation with stakeholders, that can use a wide range of "sensors", ranging from free satellite images, low-cost off-the-shelf sensors, to even novel technologies, such as odour sensors. The TWINSOR concept is introduced, but also a first prototype applied to the vineyard is described as a first result.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent8
dc.format.extent804316
dc.identifier.doi10.1016/j.procs.2022.10.118
dc.identifier.issn1877-0509
dc.identifier.otherPURE: 53329477
dc.identifier.otherPURE UUID: ad14e504-02d6-459a-a163-a4cce5b7b4bf
dc.identifier.otherScopus: 85144815382
dc.identifier.urihttp://hdl.handle.net/10362/198793
dc.identifier.urlhttps://www.scopus.com/pages/publications/85144815382
dc.language.isoeng
dc.peerreviewedyes
dc.subjectdigital agriculture
dc.subjectdigital twin
dc.subjectHCI
dc.subjectIoT
dc.subjectmobile application
dc.subjectmulti-sensor monitoring
dc.subjectvineyard
dc.subjectGeneral Computer Science
dc.subjectSDG 3 - Good Health and Well-being
dc.titleTowards Digital Twins for Multi-Sensor Land and Plant Monitoringen
dc.typejournal article
degois.publication.firstPage45
degois.publication.issueC
degois.publication.lastPage52
degois.publication.titleProcedia Computer Science
degois.publication.volume210
dspace.entity.typePublication
rcaap.rightsopenAccess

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