Schnur, Christopher ; Dorst, Tanja ; Deshmukh, Kapil Sajjan ; Zimmer, Sarah ; Litzenburger, Philipp ; Schneider, Tizian ; Lennard, Margies ; Müller, Rainer ; Schütze, Andreas (2023)
PIA - a concept for a personal information assistant for data analysis and machine learning of time-continuous data in industrial applications.
In: ing.grid : FAIR data management in engineering sciences, 1 (2)
doi: 10.48694/inggrid.3827
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
A database with high-quality data must be given to fully use the potential of Artificial Intelligence (AI). Especially in small and medium-sized companies with little experience with AI, the underlying database quality is often insufficient. This results in an increased manual effort to process the data before using AI. In this contribution, the authors developed a concept to enable inexperienced users to perform a first data analysis project with machine learning and record data with high quality. The concept comprises three modules: accessibility of (meta)data and knowledge, measurement and data planning, and data analysis. Furthermore, the concept was implemented as a front-end demonstrator on the example of an assembly station and published on the GitHub platform for potential users to test and review the concept.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Schnur, Christopher ; Dorst, Tanja ; Deshmukh, Kapil Sajjan ; Zimmer, Sarah ; Litzenburger, Philipp ; Schneider, Tizian ; Lennard, Margies ; Müller, Rainer ; Schütze, Andreas |
| Art des Eintrags: | Bibliographie |
| Titel: | PIA - a concept for a personal information assistant for data analysis and machine learning of time-continuous data in industrial applications |
| Sprache: | Englisch |
| Publikationsjahr: | 2023 |
| Ort: | Darmstadt |
| Verlag: | Universitäts- und Landesbibliothek Darmstadt |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | ing.grid : FAIR data management in engineering sciences |
| Jahrgang/Volume einer Zeitschrift: | 1 |
| (Heft-)Nummer: | 2 |
| Kollation: | 19 Seiten |
| DOI: | 10.48694/inggrid.3827 |
| URL / URN: | https://www.inggrid.org/article/id/3827/ |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | A database with high-quality data must be given to fully use the potential of Artificial Intelligence (AI). Especially in small and medium-sized companies with little experience with AI, the underlying database quality is often insufficient. This results in an increased manual effort to process the data before using AI. In this contribution, the authors developed a concept to enable inexperienced users to perform a first data analysis project with machine learning and record data with high quality. The concept comprises three modules: accessibility of (meta)data and knowledge, measurement and data planning, and data analysis. Furthermore, the concept was implemented as a front-end demonstrator on the example of an assembly station and published on the GitHub platform for potential users to test and review the concept. |
| Freie Schlagworte: | machine learning, data analysis, measurement and data planning |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Fluidsystemtechnik (FST) (seit 01.10.2006) 16 Fachbereich Maschinenbau > Institut für Fluidsystemtechnik (FST) (seit 01.10.2006) > Forschungsdatenmanagement und digital literacy |
| Hinterlegungsdatum: | 06 Dez 2023 13:23 |
| Letzte Änderung: | 26 Mär 2024 08:04 |
| PPN: | 513704094 |
| Zugehörige Links: | |
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| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
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PIA - A Concept for a Personal Information Assistant for Data Analysis and Machine Learning of Time-Continuous Data in Industrial Applications. (deposited 25 Mär 2024 13:30)
- PIA - a concept for a personal information assistant for data analysis and machine learning of time-continuous data in industrial applications. (deposited 06 Dez 2023 13:23) [Gegenwärtig angezeigt]
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