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Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array
For decades, near-infrared (NIR) spectroscopy has been a valuable tool for material analysis in a variety of applications, ranging from industrial process monitoring to quality assessment. Traditional spectrometers are typically bulky, fragile and expensive, which makes them unsuitable for portable...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501814/ https://www.ncbi.nlm.nih.gov/pubmed/36146377 http://dx.doi.org/10.3390/s22187027 |
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author | Ou, Fang van Klinken, Anne Ševo, Petar Petruzzella, Maurangelo Li, Chenhui van Elst, Don M. J. Hakkel, Kaylee D. Pagliano, Francesco van Veldhoven, Rene P. J. Fiore, Andrea |
author_facet | Ou, Fang van Klinken, Anne Ševo, Petar Petruzzella, Maurangelo Li, Chenhui van Elst, Don M. J. Hakkel, Kaylee D. Pagliano, Francesco van Veldhoven, Rene P. J. Fiore, Andrea |
author_sort | Ou, Fang |
collection | PubMed |
description | For decades, near-infrared (NIR) spectroscopy has been a valuable tool for material analysis in a variety of applications, ranging from industrial process monitoring to quality assessment. Traditional spectrometers are typically bulky, fragile and expensive, which makes them unsuitable for portable and in-field use. Thus, there is a growing interest for miniaturized, robust and low-cost NIR sensors. In this study, we demonstrate a handheld NIR spectral sensor module, based on a fully-integrated multipixel detector array, sensitive in the 850–1700 nm wavelength range. Differently from a spectrometer, the spectral sensor measures a limited number of NIR spectral bands. The capabilities of the spectral sensor module were evaluated alongside a commercially available portable spectrometer for two application cases: to quantify the moisture content in rice grains and to classify plastic types. Both devices achieved the two sensing tasks with comparable performance. Moisture quantification was achieved with a root mean square error (RMSE) prediction of 1.4% and 1.1% by the spectral sensor and spectrometer, respectively. Classification of the plastic type was achieved with a prediction accuracy on unknown samples of 100% and 96.4% by the spectral sensor and spectrometer, respectively. The results from this study are promising and demonstrate the potential for the compact NIR modules to be used in a variety of NIR sensing applications. |
format | Online Article Text |
id | pubmed-9501814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95018142022-09-24 Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array Ou, Fang van Klinken, Anne Ševo, Petar Petruzzella, Maurangelo Li, Chenhui van Elst, Don M. J. Hakkel, Kaylee D. Pagliano, Francesco van Veldhoven, Rene P. J. Fiore, Andrea Sensors (Basel) Article For decades, near-infrared (NIR) spectroscopy has been a valuable tool for material analysis in a variety of applications, ranging from industrial process monitoring to quality assessment. Traditional spectrometers are typically bulky, fragile and expensive, which makes them unsuitable for portable and in-field use. Thus, there is a growing interest for miniaturized, robust and low-cost NIR sensors. In this study, we demonstrate a handheld NIR spectral sensor module, based on a fully-integrated multipixel detector array, sensitive in the 850–1700 nm wavelength range. Differently from a spectrometer, the spectral sensor measures a limited number of NIR spectral bands. The capabilities of the spectral sensor module were evaluated alongside a commercially available portable spectrometer for two application cases: to quantify the moisture content in rice grains and to classify plastic types. Both devices achieved the two sensing tasks with comparable performance. Moisture quantification was achieved with a root mean square error (RMSE) prediction of 1.4% and 1.1% by the spectral sensor and spectrometer, respectively. Classification of the plastic type was achieved with a prediction accuracy on unknown samples of 100% and 96.4% by the spectral sensor and spectrometer, respectively. The results from this study are promising and demonstrate the potential for the compact NIR modules to be used in a variety of NIR sensing applications. MDPI 2022-09-16 /pmc/articles/PMC9501814/ /pubmed/36146377 http://dx.doi.org/10.3390/s22187027 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ou, Fang van Klinken, Anne Ševo, Petar Petruzzella, Maurangelo Li, Chenhui van Elst, Don M. J. Hakkel, Kaylee D. Pagliano, Francesco van Veldhoven, Rene P. J. Fiore, Andrea Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array |
title | Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array |
title_full | Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array |
title_fullStr | Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array |
title_full_unstemmed | Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array |
title_short | Handheld NIR Spectral Sensor Module Based on a Fully-Integrated Detector Array |
title_sort | handheld nir spectral sensor module based on a fully-integrated detector array |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501814/ https://www.ncbi.nlm.nih.gov/pubmed/36146377 http://dx.doi.org/10.3390/s22187027 |
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