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Promoting olive groves’s soil quality by a digital twin’s predictive based control: the sensor’s network

dc.contributor.authorSilva, Letícia
dc.contributor.authorGiugge, Romina Eliana
dc.contributor.authorRodríguez-Sedano, Francisco Jesús
dc.contributor.authorBaptista, Paula
dc.contributor.authorCoelho, João Paulo
dc.date.accessioned2023-02-23T16:13:32Z
dc.date.available2023-02-23T16:13:32Z
dc.date.issued2022
dc.description.abstractIn Portugal, the olive groves soil has been subject to severe degradation due to harsh farming techniques combined with uncontrollable conditions such as climate changes and steep terrain orography. In this framework, this tendency must be reverted by adopting different farm management policies. The MAN4HEALTH project address this subject in two-folds: one, at an agronomic level, where the soil will be protected by growing a layer of indigenous plants and other, that resort to the soil’s digitization in order to improve the deployment of fertilizers. This paper addresses the latter and aims to provide an overall description of the architecture of a predictive control system based on the soil’s digital twin. In this control paradigm, an artificial intelligence layer will follow the entire cultivation process through the development of a soil’s digital twin. This model will be able to describe the spatial and temporal dynamics of fertilization policies and be included within a model predictive control strategy in order to both decrease the concentration of chemicals released into the soil and promote the economic income of the farmer. In particular, this paper tackles one of the phases of this project where soil digitization must be carried out in order to feed the data to the digital twin. In particular, the description of the sensor network and the data management architecture.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSilva, Letícia; Giugge, Romina; Rodríguez-Sedano, Francisco J.; Baptista, Paula; Coelho, João Paulo (2022). Promoting olive groves’s soil quality by a digital twin’s predictive based control: the sensor’s network. In 15th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2022. Caparica. 930, p. 241 - 250. ISBN 978-3-031-10047-5pt_PT
dc.identifier.doi10.1007/978-3-031-10047-5_21pt_PT
dc.identifier.issn978-3-031-10047-5
dc.identifier.urihttp://hdl.handle.net/10198/27153
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectSmart farmingpt_PT
dc.subjectAgriculture digitizationpt_PT
dc.subjectDigital twinspt_PT
dc.subjectSensor networkspt_PT
dc.subjectModel predictive controlpt_PT
dc.titlePromoting olive groves’s soil quality by a digital twin’s predictive based control: the sensor’s networkpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceCaparicapt_PT
oaire.citation.endPage250pt_PT
oaire.citation.startPage241pt_PT
oaire.citation.title15th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2022pt_PT
oaire.citation.volume930pt_PT
person.familyNameSilva
person.familyNameBaptista
person.familyNameCoelho
person.givenNameLetícia
person.givenNamePaula
person.givenNameJoão Paulo
person.identifierR-001-EXZ
person.identifier.ciencia-idC01E-87BA-67D7
person.identifier.ciencia-id7D11-FE1E-CD0F
person.identifier.ciencia-idD61E-A586-7D4A
person.identifier.orcid0000-0003-3812-2794
person.identifier.orcid0000-0001-6331-3731
person.identifier.orcid0000-0002-7616-1383
person.identifier.ridJ-6887-2013
person.identifier.scopus-author-id14051688000
person.identifier.scopus-author-id55137039300
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationa2aa1be8-574c-4e0b-afd6-d3c61efad820
relation.isAuthorOfPublication3f35226a-b17a-4f7d-8da1-3297105cbfe9
relation.isAuthorOfPublication2861f33b-b49a-421d-9bfa-92b4304d2668
relation.isAuthorOfPublication.latestForDiscovery2861f33b-b49a-421d-9bfa-92b4304d2668

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