Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/48864
DC FieldValueLanguage
dc.contributor.authorRossello, Nicolas Bonoit
dc.contributor.authorRossini, Lucait
dc.contributor.authorSperanza, Stefanoit
dc.contributor.authorGarone, Emanueleit
dc.date.accessioned2023-01-06T18:39:29Z-
dc.date.available2023-01-06T18:39:29Z-
dc.date.issued2022it
dc.identifier.urihttp://hdl.handle.net/2067/48864-
dc.description.abstractThis paper introduces an observer-based scheme to estimate pest populations in agricultural fields. The proposed scheme describes the different stages of the life cycle of insects as a system of ODEs and it uses an Extended Kalman Filter with intermittent observations to provide a state estimation. This scheme aims at providing a general framework to formally combine physiologically-based models and field measurements, contrary to current best practices where both methodologies are used independently in parallel. The presented approach allows to apply this framework to a large number of species of agricultural interest and to take advantage from different counting systems. The improvement of the presented approach with respect to current best practices is demonstrated by means of numerical simulations based on the case of Drosophila suzukii.it
dc.format.mediumELETTRONICOit
dc.language.isoengit
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleState Estimation of Pest Populations subject to Intermittent Measurementsit
dc.typeconferenceObject*
dc.identifier.doi10.1016/j.ifacol.2022.11.128it
dc.identifier.scopus2-s2.0-85144819148it
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S2405896322027616it
dc.relation.journalIFAC-PAPERSONLINEit
dc.relation.ispartofbook7th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture AGRICONTROL 2022it
dc.relation.firstpage135it
dc.relation.lastpage140it
dc.relation.conferencename7th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture, AGRICONTROL 2022it
dc.relation.conferenceplaceMunichit
dc.relation.conferencedate14-16 settembre 2022it
dc.relation.volume55it
dc.subject.scientificsectorAGR/11it
dc.description.numberofauthors4it
dc.description.internationalit
dc.contributor.countryITAit
dc.contributor.countryBELit
dc.type.refereeREF_1it
dc.type.invitednoit
dc.type.miur273*
dc.publisher.nameKidlington : Elsevier Ltdit
item.fulltextWith Fulltext-
item.openairetypeconferenceObject-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.journal.journalissn2405-8963-
crisitem.journal.anceE233702-
Appears in Collections:D1. Contributo in Atti di convegno
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