Spectral Sensing Using a Handheld NIR Module Based on a Fully Integrated Sensor Chip
| Autor: | Fang Ou, Anne van Klinken, Kaylee D. Hakkel, Maurangelo Petruzzella, Don M.J. van Elst, Petar Ševo, Chenhui Li, Francesco Pagliano, Rene P.J. van Veldhoven, Andrea Fiore |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Spectroscopy. :34-38 |
| ISSN: | 1939-1900 0887-6703 |
| Popis: | Near-infrared (NIR) spectroscopy is widely used for the classification of materials and the quantification of their properties. Today, there is a high demand for extending the use of this technique to portable applications, and eventually, the integration with consumer appliances and smartphones. To reach this goal, the overall size of the NIR sensor, its production cost, robustness, and resistance to vibrations are of particular importance. This paper describes an approach to spectral sensing in the NIR (850–1700 nm) using a handheld sensor module based on a fully integrated multipixel detector array with a footprint of around 2×2 mm2. The capabilities of the spectral sensor module were recently evaluated in two application cases: Quantification of the fat percentage in raw milk and the classification of plastic types. Fat quantification was achieved with a root mean square error (RMSE) of prediction of 0.14% and classification of plastic types was achieved with a prediction accuracy on unknown samples of 100%. The results demonstrate the feasibility of the direct NIR sensing approach used by the integrated sensor, which has potential to be used in a variety of applications. |
| Databáze: | OpenAIRE |
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