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AI-supported selection procedure for spectral sensors based on technical and economic characteristics

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dc.contributor.authorMenz, Patrick
dc.contributor.authorKlein, Lauritz
dc.contributor.authorHerzog, Andreas
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorGergeleit, Martin
dc.contributor.editorMartin, Ludger
dc.date.accessioned2024-10-21T18:24:12Z
dc.date.available2024-10-21T18:24:12Z
dc.date.issued2024
dc.description.abstractThis study presents an AI-supported spectral sensor selection process that combines technical and economic criteria to recommend the optimal sensor for specific applications, such as quality control of roasted coffee beans. Using a comprehensive database of spectral sensor characteristics, the SMART algorithm guides decisions that focus on both performance and cost-effectiveness. Our methodology involves simulating spectral responses and using an AI model to evaluate sensor effectiveness in classifying coffee bean types. Initial results highlight the method's ability to optimise sensor selection, effectively balancing performance with budget considerations, and underscore its potential to improve user decision making in technology applications and enhance their digital sovereignty.en
dc.identifier.doi10.18420/inf2024_111
dc.identifier.eissn2944-7682
dc.identifier.isbn978-3-88579-746-3
dc.identifier.issn2944-7682
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45083
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-352
dc.subjectartificial intelligence
dc.subjectspectral sensor selection
dc.subjectspectra simulation
dc.subjectselection problem
dc.titleAI-supported selection procedure for spectral sensors based on technical and economic characteristicsen
dc.typeText/Conference Paper
gi.citation.endPage1267
gi.citation.publisherPlaceBonn
gi.citation.startPage1261
gi.conference.date24.-26. September 2024
gi.conference.locationWiesbaden
gi.conference.sessiontitleKoLaZ-24-Kolloquium Landwirtschaft der Zukunft 2024: Digitale Souveränität in der Landwirtschaft, der Lebensmittelkette und dem ländlichen Raum: Trotz, mit oder durch KI?

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P352 - INFORMATIK 2024 - Lock in or log out? Wie digitale Souveränität gelingt