Application of machine learning technology for construction site

Heejae Ahn, Dongmin Lee, Seongsoo Lee, Taehoon Kim, Hun Hee Cho, Kyung In Kang

Research output: Contribution to conferencePaper

Abstract

Although several research studies on the application of machine learning to the construction field are actively underway, no study has yet been done on the areas where the application is primarily needed. Using the importance–performance analysis method, this paper identified the top five areas of construction sites where machine learning technology needs to be applied. Furthermore, it suggests application plans developed by using the Delphi method. The identified top five areas were unmanned tower crane, inspection of joint connections, prediction of construction safety accidents, operation of construction lift, layout of tower crane. This study is expected to facilitate the effective application of machine learning technology at construction sites in the future. Ultimately, the purpose of this study is to reduce waste of labor and the safety risks at construction sites through machine learning technologies.

Original languageEnglish
Publication statusPublished - 2018 Jan 1
Event35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018 - Berlin, Germany
Duration: 2018 Jul 202018 Jul 25

Other

Other35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018
CountryGermany
CityBerlin
Period18/7/2018/7/25

Fingerprint

Learning systems
Tower cranes
Accidents
Inspection
Personnel

Keywords

  • Construction site
  • Delphi method
  • IPA method
  • Machine learning

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Building and Construction

Cite this

Ahn, H., Lee, D., Lee, S., Kim, T., Cho, H. H., & Kang, K. I. (2018). Application of machine learning technology for construction site. Paper presented at 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018, Berlin, Germany.

Application of machine learning technology for construction site. / Ahn, Heejae; Lee, Dongmin; Lee, Seongsoo; Kim, Taehoon; Cho, Hun Hee; Kang, Kyung In.

2018. Paper presented at 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018, Berlin, Germany.

Research output: Contribution to conferencePaper

Ahn, H, Lee, D, Lee, S, Kim, T, Cho, HH & Kang, KI 2018, 'Application of machine learning technology for construction site', Paper presented at 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018, Berlin, Germany, 18/7/20 - 18/7/25.
Ahn H, Lee D, Lee S, Kim T, Cho HH, Kang KI. Application of machine learning technology for construction site. 2018. Paper presented at 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018, Berlin, Germany.
Ahn, Heejae ; Lee, Dongmin ; Lee, Seongsoo ; Kim, Taehoon ; Cho, Hun Hee ; Kang, Kyung In. / Application of machine learning technology for construction site. Paper presented at 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things, ISARC 2018, Berlin, Germany.
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