Wearable ultraviolet sensor based on convolutional neural network image processing method

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

11 Scopus Citations
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Author(s)

  • Yan Chen
  • Zimei Cao
  • Jiejian Zhang
  • Yuanqing Liu
  • Duli Yu
  • And 1 others
  • Xiaoliang Guo

Detail(s)

Original languageEnglish
Article number113402
Journal / PublicationSensors and Actuators: A. Physical
Volume338
Online published25 Jan 2022
Publication statusPublished - 1 May 2022
Externally publishedYes

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.

Research Area(s)

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

Citation Format(s)

Wearable ultraviolet sensor based on convolutional neural network image processing method. / Chen, Yan; Cao, Zimei; Zhang, Jiejian et al.
In: Sensors and Actuators: A. Physical, Vol. 338, 113402, 01.05.2022.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review