Transfer Learning‐Assisted Porous Polymer Humidity Sensor for Powered Air‐Purifying Mask

Masks protect respiratory health in the coal, oil, and gas industries. However, prolonged exposure to high humidity inside masks can cause discomfort and increase the risk of respiratory diseases. To address the issue, in this work, a porous polymer humidity sensor suitable for monitoring respiratory changes in high humidity environment is prepared and integrated into the power air‐purifying mask. Combined with the transfer learning algorithm, the problem with respiratory resistance caused by delayed air supply due to signal processing in the traditional power air‐purifying mask is overcome, and the respiratory signal is effectively predicted in advance, so as to achieve real‐time on‐demand air supply. The brief process is as follows: A porous polymer humidity sensor with fast response/recovery times (2.94/4.86 s) at 95% relative humidity (RH) is developed for monitoring respiratory rate changes in high humidity environments. By integrating this sensor with a powered air‐purifying system and employing a transfer learning algorithm, the system predicts respiratory signals and adjusts the air supply in real‐time. This reduces mask humidity from 95% RH to 40–50% RH in 1.8 s, ensuring comfortable, low‐resistance breathing for workers.This work will be conductive to the development of comfortable poweredair‐purifying respirators with low resistance and humidity.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Transfer Learning‐Assisted Porous Polymer Humidity Sensor for Powered Air‐Purifying Mask ; day:28 ; month:10 ; year:2024 ; extent:12
Advanced intelligent systems ; (28.10.2024) (gesamt 12)

Creator
Wang, Yue
Qi, Xinkai
Chen, Lu
Cheng, Yongchao
Mu, Zhefu
Gu, Xiuquan
Li, Shiyin
Song, Yunfeng
He, Xinjian
Huang, Sheng

DOI
10.1002/aisy.202400537
URN
urn:nbn:de:101:1-2410281317580.692258576912
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:37 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Associated

  • Wang, Yue
  • Qi, Xinkai
  • Chen, Lu
  • Cheng, Yongchao
  • Mu, Zhefu
  • Gu, Xiuquan
  • Li, Shiyin
  • Song, Yunfeng
  • He, Xinjian
  • Huang, Sheng

Other Objects (12)