A Novel Method for UV Measurement Using PLA-Based Photochromic Material and Machine Learning Models

A new method has been developed that can accurately measure the relationship between color change under ultraviolet (UV) light and the amount of UV using a mobile phone camera to observe the color changes of a polylactic acid-based photochromic material (PLA-PM). The videos of the color change of the PLA-PM were recorded using a mobile phone camera. The obtained data were used for machine learning, and the amount of UV light causing the color change was predicted using machine learning models. The target variable in the models is the voltage values read from the UV sensor via Arduino. Dataset preparations process different high-resolution and frames/s images through six image processing stages. Image processing stages end with the normalization of values for the final image’s three-color space channels. This work, which enhances traditional colorimetric measurements with artificial intelligence technologies, demonstrates potential applicability in studies, such as UV index measurement, medical measurements, and UV-sensitive textile products. The study experimentally shows the feasibility of measuring UV with mobile phones without relying on expensive devices.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-11-25
DOI
https://doi.org/10.1109/jsen.2024.3502217
Citations
1
Primary Topic
Analytical Chemistry and Sensors
Type
article
Field-Weighted Citation Impact
0.29
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article

A Novel Method for UV Measurement Using PLA-Based Photochromic Material and Machine Learning Models

Ömer Galip Saraçoğlu, Esra Kayacan Erdoğan, Şekip Esat Hayber
1 citations
IEEE Sensors Journal
Analytical Chemistry and Sensors
0.29
article

A Novel Method for UV Measurement Using PLA-Based Photochromic Material and Machine Learning Models

Ömer Galip Saraçoğlu, Esra Kayacan Erdoğan, Şekip Esat Hayber
article en
1 citations

Abstract

A new method has been developed that can accurately measure the relationship between color change under ultraviolet (UV) light and the amount of UV using a mobile phone camera to observe the color changes of a polylactic acid-based photochromic material (PLA-PM). The videos of the color change of the PLA-PM were recorded using a mobile phone camera. The obtained data were used for machine learning, and the amount of UV light causing the color change was predicted using machine learning models. The target variable in the models is the voltage values read from the UV sensor via Arduino. Dataset preparations process different high-resolution and frames/s images through six image processing stages. Image processing stages end with the normalization of values for the final image’s three-color space channels. This work, which enhances traditional colorimetric measurements with artificial intelligence technologies, demonstrates potential applicability in studies, such as UV index measurement, medical measurements, and UV-sensitive textile products. The study experimentally shows the feasibility of measuring UV with mobile phones without relying on expensive devices.

IEEE Sensors JournalVol. 25(2)
Cukurova University (TR), Erciyes University (TR)
Openalex Percentile: Top 46%
Analytical Chemistry and Sensors
0.29
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