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SmartSpectrometer - Embedded Optical Spectroscopy for Applications in Agriculture and Industry

 
: Krause, Julius; Grüger, Heinrich; Gebauer, Lucie; Zheng, Xiaorong; Knobbe, Jens; Pügner, Tino; Kicherer, Anna; Gruna, Robin; Längle, Thomas; Beyerer, Jürgen

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Fulltext ()

Sensors. Online journal 21 (2021), No.13, Art. 4476, 18 pp.
https://www.mdpi.com/journal/sensors
ISSN: 1424-8220
ISSN: 1424-8239
ISSN: 1424-3210
English
Journal Article, Electronic Publication
Fraunhofer IOSB ()
Fraunhofer IPMS ()
Industrial Internet of Things; near-infrared spectroscopy; miniaturized optical spectrometer; machine learning; smart viticulture

Abstract
The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be acquired and evaluated in real time, and the results can be integrated directly into process and automation units, saving resources and costs. Multivariate data analysis is needed to integrate optical spectrometers as sensors. Therefore, a spectrometer with integrated artificial intelligence (AI) called SmartSpectrometer and its interface is presented. The advantages of the SmartSpectrometer are exemplified by its integration into a harvesting vehicle, where quality is determined by predicting sugar and acid in grapes in the field.

: http://publica.fraunhofer.de/documents/N-636421.html