Journal of the Earthquake Engineering Society of Korea (한국지진공학회논문집)

Earthquake Engineering Society of Korea (한국지진공학회)
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Development of Chatbot Self-Inspection Scenario for Structural Safety of Existing Reinforced Concrete Buildings

챗봇 활용 철근콘크리트 건축물 구조안전 자가점검 시나리오 개발에 관한 연구

  • Yang, Jaekwang (Research Institute for Safety Performance, Korean Authority of Land & Infrastructure Safety) ;
  • Kang, Taewook (Department of Architectural Engineering, Gyeongsang National University) ;
  • Shin, Jiuk (Department of Architectural Engineering, Gyeongsang National University)
  • 양재광 (국토안전관리원 안전성능연구소) ;
  • 강태욱 (경상국립대학교 건축공학과) ;
  • 신지욱 (경상국립대학교 건축공학과)
  • Received : 2023.10.15
  • Accepted : 2023.10.17
  • Published : 2023.11.01
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Abstract

Due to the aging of a building, 38.8% (about 2.82 million buildings) of the total buildings are old for more than 30 years after completion and are located in a blind spot for an inspection, except for buildings subject to regular legal inspection (about 3%). Such existing buildings require users to self-inspect themselves and make efforts to take preemptive risks. The scope of this study was defined as the general public's visual self-inspection of buildings and was limited to structural members that affect the structural stability of old buildings. This study categorized possible damage to reinforced concrete to check the structural safety of buildings and proposed a checklist to prevent the damage. A damage assessment methodology was presented during the inspection, and a self-inspection scenario was tested through a chatbot connection. It is believed that it can increase the accessibility and convenience of non-experts and induce equalized results when performing inspections, according to the chatbot guide.

Keywords

Acknowledgement

본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호 RS-2022-00143584).

References

  1. Ministry of Land and Transport. Special Act on the Safety Control and Maintenance of Establishments; c2021.
  2. Ministry of Land and Transport. Building Management Act; c2021.
  3. Ko KJ, Oh SH, Lee CS. Application Prototype Development for the Building Safety Periodic Inspection. Journal of the Architectural Institute of Korea Structure & Construction. 2016 Jan;32(1):63-71. https://doi.org/10.5659/JAIK_SC.2016.32.1.63
  4. Kim YS. Small Facilities that Conduct Safety Checks Together through the App. Architectural Institute of Korea. 2023 Mar;67(3): 29-33.
  5. Yoo JY. Design and Implementation of Library Chatbot for Nonface. Korean Society for Information Society. 2020 Dec;37(4):151-179.
  6. Jung JK, Lee J, Kim HS. A Study on the Development of AI Chatbot for Korean Language Education Using Chatbot Builder. Journal of the International Network for Korean Language and Culture. 2022 Dec;19(3):405-441. https://doi.org/10.15652/ink.2022.19.3.405
  7. Ahn SH. Exploring Ways to Build a Chatbot System for Effective Guidance of University Undergraduate Operation. Journal of Creative Information Culture. 2022 Aug;8(3):145-152.
  8. Lee JS, Choi JH, Hwang SH, Lim CH, Gil JM. A Design and Implementation of DCUchatbot Based on Kakaotalk Open Builder. Korea Information Processing Society. 2019 Nov;26(2):595-597.
  9. Ministry of Land and Transport. Small Vulnerable Facility Safety Inspection Manual; c2023.
  10. Park IS. A Study for the Improvement of Periodic Safety Report and Inspection on site in the Third type of Building Facilities. Dept. of Architecture & Safety Engineering Graduate School of Engineering Kyonggi University; c2019.
  11. Lee HB, Kim JW, Jang IY. Development of Automatic Crack Detection System for Concrete Structure Using Image Processing Method. Journal of The Korea Institute for Structural Maintenance and Inspection. 2012 Jan;16(1):64-77. https://doi.org/10.11112/JKSMI.2012.16.1.064
  12. Lee BY, Park YD, Kim JK. A Technique for Pattern Recognition of Concrete Surface Cracks. Journal of the Korea Concrete Institute. 2005 Jun;17(3):369-374. https://doi.org/10.4334/JKCI.2005.17.3.369
  13. Lee YI, Kim BH, Cho SJ. Image-based Spalling Detection of Concrete Structures Using Deep Learning. Journal of the Korea Concrete Institute. 2018 Feb;30(1):91-99. https://doi.org/10.4334/JKCI.2018.30.1.091
  14. Cho SJ, Kim BH, Lee YI. Image-Based Concrete Crack and Spalling Detection using Deep Learning. The Magazine of the Korean Society of Civil Engineers. 2018 Aug;66(8).
  15. Kang HK, Hong SG. Causes and Mitigation of Concrete Cracking. Journal of the Korea Concrete Institute. 2008 Sep;20(5):61-68.
  16. Lim DH. An Experimental Study on the Failure Behavior of Reinforced Concrete Columns Strengthened with NSM and EBR CFRP Strips. Journal of the Korea Concrete Institute. 2020 Feb;32(1):45-51. https://doi.org/10.4334/JKCI.2020.32.1.045