Augmented reality system for facility management using image-based indoor localization

Francis Baek, Inhae Ha, Hyoungkwan Kim

Research output: Contribution to journalArticlepeer-review

79 Citations (Scopus)


Image-based localization has provided opportunities for efficient facility management. Combined with augmented reality (AR), automated localization can offer visually assistive information in facility management. However, implementing an AR-based facility management system with image-based localization is difficult. Device-intensive methods or markers were prerequisites for facility information display. Localization accuracy and information readability and accessibility were some of the issues to be resolved for a successful representation of facility information. This paper presents an AR system for facility management using an image-based indoor localization method that estimates the user's indoor position and orientation by comparing the user's perspective to building information modeling (BIM) based on a deep learning computation. A graphics processing unit (GPU)-enabled server is used for the deep learning computation, and the resultant information is wirelessly transferred to the mobile AR device through transmission control protocol/Internet protocol (TCP/IP). Thereafter, spatial mapping visually fits the object of interest (e.g. pipes) onto the AR image using three-dimensional (3D) sensing capability of AR device. Experts evaluated that the proposed system has potential for improved facility management and identified future research direction, such as integrated information presentation and effective reflection of rehabilitation efforts on the drawings.

Original languageEnglish
Pages (from-to)18-26
Number of pages9
JournalAutomation in Construction
Publication statusPublished - 2019 Mar

Bibliographical note

Funding Information:
This work was supported by a grant from the National Research Foundation of Korea (NRF) funded by the Korean government (MSIP) (No. 2018R1A2B2008600 ).

Publisher Copyright:
© 2018 Elsevier B.V.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction


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