Wearable ultraviolet sensor based on convolutional neural network image processing method

Yan Chen, Zimei Cao, Jiejian Zhang, Yuanqing Liu, Duli Yu, Xiaoliang Guo*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

The wearable sensors based on image processing possess distinct advantages such as being power-free and without complex wire connections, which are of low cost and easy to manufacture. In this paper, a wearable UV sensor made from photochromic material and PDMS was proposed to be employed in real-time UV monitoring and daily solar protection. The convolutional neural network image processing method was introduced and developed for quantifying UV intensity, and it was shown to decrease the impact of ambient light significantly. The limit of detection of the sensor was about 9 μW/cm2 and the recognition rate of the network exceeded 90% under different ambient light conditions. The CNN test was complete within 3 s. Finally, regarding applied scenarios, a UV intensity recognition APP based on a mobile convolutional neural network was designed, which displayed the real-time UV intensity by simple photting.

Original languageEnglish
Article number113402
JournalSensors and Actuators A: Physical
Volume338
DOIs
Publication statusPublished - 1 May 2022

Keywords

  • Convolutional neural network
  • Image processing
  • Photochromic material
  • UV sensors

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