HEC/PVDF-Coated Micro-Sphere Humidity Sensor Using CNN-Based Barcoding

Whispering gallery mode (WGM) sensors offer a promising alternative to conventional relative humidity (RH) sensors, due to their high quality (Q) factors and sensitivity to environmental changes. In this work, we demonstrate a WGM microsphere-based RH sensor featuring a 170 μm diameter resonator coupled with a tapered optical fiber. The resonator was coated with a hydroxyethyl cellulose/polyvinylidene fluoride (HEC/PVDF) composite to enhance humidity sensitivity, resulting in a wavelength shift sensitivity of 0.4 pm/%RH and an attenuation response of 0.125 dB/%RH. The sensor was further utilized to generate a dataset of barcoded spectral responses, which were used to train and test a convolutional neural network (CNN) classifier, achieving an accuracy of 98%.

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Publication Details

Journal
IEEE Photonics Technology Letters
Published
2025-10-03
DOI
https://doi.org/10.1109/lpt.2025.3617015
Citations
2
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
1.46
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article

HEC/PVDF-Coated Micro-Sphere Humidity Sensor Using CNN-Based Barcoding

Huda Adnan Zain, Khurram Karim Qureshi
2 citations
IEEE Photonics Technology Letters
Advanced Fiber Optic Sensors
1.46
article

HEC/PVDF-Coated Micro-Sphere Humidity Sensor Using CNN-Based Barcoding

Huda Adnan Zain, Khurram Karim Qureshi
article en
2 citations

Abstract

Whispering gallery mode (WGM) sensors offer a promising alternative to conventional relative humidity (RH) sensors, due to their high quality (Q) factors and sensitivity to environmental changes. In this work, we demonstrate a WGM microsphere-based RH sensor featuring a 170 μm diameter resonator coupled with a tapered optical fiber. The resonator was coated with a hydroxyethyl cellulose/polyvinylidene fluoride (HEC/PVDF) composite to enhance humidity sensitivity, resulting in a wavelength shift sensitivity of 0.4 pm/%RH and an attenuation response of 0.125 dB/%RH. The sensor was further utilized to generate a dataset of barcoded spectral responses, which were used to train and test a convolutional neural network (CNN) classifier, achieving an accuracy of 98%.

IEEE Photonics Technology LettersVol. 38(2)
King Fahd University of Petroleum and Minerals (SA)
Openalex Percentile: Top 15%
Advanced Fiber Optic Sensors
1.46
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