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13 December 2024 Android software design for Bluetooth fluorescence spectrometer and its application of vegetable oil type identification
Guiying Fu, Ying Guo, Zongjie Bi, Songlin Yin, Xiaohua Che, Zhaoshuo Tian
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Proceedings Volume 13494, AOPC 2024: Optical Spectroscopy and Applications; 1349407 (2024) https://doi.org/10.1117/12.3046437
Event: Applied Optics and Photonics China 2024 (AOPC2024), 2024, Beijing, China
Abstract
At present, most of the spectrometers used in food detection have some problems such as complex operation, large volume and high cost, which are not conducive to their popularization and application. Therefore, we have developed a small-scale Bluetooth fluorescence spectrometer which can be used for the detection of vegetable oil. The 405 nm semi-conductor laser can be integrated in the spectrometer to excite the fluorescence spectrum of vegetable oil, the spectrum data detected by the spectrometer is transmitted to the Android mobile phone by wireless Bluetooth, and the data is received, displayed and processed by the Android mobile phone software developed by App Inventor. The software can also be used to identify vegetable oils in real time by using machine learning to analyze spectral data on Baidu's AI open platform. In the experiment, the spectrometer collected 600 sets of spectral data of six kinds of vegetable oils, and trained and tested these data by software. The accuracy of oil identification can reach 96.1% . The experimental results show that the spectrometer can identify the kinds of vegetable oil quickly and accurately by using the developed software. It has the advantages of simple operation, high sensitivity, low cost and no pollution to the sample, it has a good application prospect in the field of food safety rapid detection.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Guiying Fu, Ying Guo, Zongjie Bi, Songlin Yin, Xiaohua Che, and Zhaoshuo Tian "Android software design for Bluetooth fluorescence spectrometer and its application of vegetable oil type identification", Proc. SPIE 13494, AOPC 2024: Optical Spectroscopy and Applications, 1349407 (13 December 2024); https://doi.org/10.1117/12.3046437
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KEYWORDS
Spectroscopy
Fluorescence
Fluorescence spectroscopy
Vegetable oil
Artificial intelligence
Data transmission
Calibration
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