Ray Tracing -driven System of Virtual Fitting Based on Trustworthy Identification of IIoT

Xiangnan Gong, Yanhong Wang, Jiping Xu, Cheng Chi, Zhaoyang Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Virtual fitting system is a promising direction for artificial intelligence (AI) application in the Industrial Internet of things (IIoT). However, existing research is beyond the overall links between IIoT and real-world experience. In this paper, the Product Lifecycle Management (PLM) data is integrated through the identification of IIoT to realize a digital twin system. The entire process involves multiple production companies with various PLM systems through identification. The system introduces dynamic ray tracing to imitate fitting effect in the way of rendering where the whole process of monitoring makes the traceability of the product simple and reliable. In addition, the system has an AI analysis model of user preference with a selection interface, which can build the virtual fitting model according to the users' wishes. The design help users have a more immersive shopping experience. Finally, consumers' desire is stimulated to prove the feasibility and effectiveness of the virtual fitting system.

Original languageEnglish
Title of host publicationProceedings of the 41st Chinese Control Conference, CCC 2022
EditorsZhijun Li, Jian Sun
PublisherIEEE Computer Society
Pages5780-5787
Number of pages8
ISBN (Electronic)9789887581536
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event41st Chinese Control Conference, CCC 2022 - Hefei, China
Duration: 25 Jul 202227 Jul 2022

Publication series

NameChinese Control Conference, CCC
Volume2022-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference41st Chinese Control Conference, CCC 2022
Country/TerritoryChina
CityHefei
Period25/07/2227/07/22

Keywords

  • IIoT
  • PLM
  • Ray tracing
  • trustworthy identification
  • virtual fitting

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