| Autor: |
Brais Galdo, Daniel Rivero, Enrique Fernandez-Blanco |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Proceedings, Vol 21, Iss 1, p 48 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2504-3900 |
| DOI: |
10.3390/proceedings2019021048 |
| Popis: |
It is a fact that, non-destructive measurement technologies have gain a lot of attention over the years. Among those technologies, NIR technology is the one which allows the analysis of electromagnetic spectrum looking for carbon-link interactions. This technology analyzes the electromagnetic spectrum in the band between 700 nm and 2500 nm, a band very close to the visible spectrum. Traditionally, the devices used to measure are utterly expensive and enormously bulky. That is why this project was focused on a portable spectrophotometer to make measures. This device is smaller and cheaper than the common spectrophotometer, although at the cost of a lower resolution. In this work, that device in combination with the use of machine learning was used to detect if a beer contains alcohol or it can be labeled as non-alcoholic drink. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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