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For5G: Systematic approach for creating digital twins of cherry orchards

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dc.contributor.authorMeyer, Lukas
dc.contributor.authorGilson, Andreas
dc.contributor.authorUhrmann, Franz
dc.contributor.authorWeule, Mareike
dc.contributor.authorKeil, Fabian
dc.contributor.authorHaunschild, Bernhard
dc.contributor.authorOschek, Joachim
dc.contributor.authorSteglich, Marco
dc.contributor.authorHansen, Jonathan
dc.contributor.authorStamminger, Marc
dc.contributor.authorScholz, Oliver
dc.contributor.editorHoffmann, Christa
dc.contributor.editorStein, Anthony
dc.contributor.editorRuckelshausen, Arno
dc.contributor.editorMüller, Henning
dc.contributor.editorSteckel, Thilo
dc.contributor.editorFloto, Helga
dc.date.accessioned2023-02-21T15:14:10Z
dc.date.available2023-02-21T15:14:10Z
dc.date.issued2023
dc.description.abstractWe present a systematic approach for creating digital twins of cherry trees in orchards as part of the project “For5G: Digital Twin”. We aim to develop a basic concept for 5G applications in orchards using a mobile campus network. Digital twins monitor the status of individual trees in every aspect and are a crucial step for the digitalization of processes in horticulture. Our framework incorporates a transformation of photometric data to a 3D reconstruction, which is subsequently segmented and modeled using learning-based approaches. Collecting objective phenotypic features from individual trees over time and storing them in a knowledge graph offers a convenient foundation for gaining new insights. Our approach shows promising results at this point for creating a detailed digital twin of a cherry tree and ultimately the entire orchard.en
dc.identifier.isbn978-3-88579-724-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40283
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-330
dc.subject5G
dc.subjectcherry tree
dc.subjectdeep learning
dc.subjectdigital horticulture
dc.subjectdigital twin
dc.subjectknowledge graph
dc.subjectorchard
dc.subjectphenotyping
dc.subjectphotogrammetry
dc.subjectprecision farming
dc.subjectUAV
dc.titleFor5G: Systematic approach for creating digital twins of cherry orchardsen
dc.typeText/Conference Paper
gi.citation.endPage416
gi.citation.publisherPlaceBonn
gi.citation.startPage411
gi.conference.date13.-14. Februar 2023
gi.conference.locationOsnabrück

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P330 - 43. GIL-Jahrestagung 2023 - Fokus: Resiliente Agri-Food-Systeme