한국건축시공학회지 (Journal of the Korea Institute of Building Construction)

  • 제20권6호
  • /
  • Pages.577-584
  • /
  • 2020
  • /
  • 1598-2033(pISSN)
  • /
  • 2233-5706(eISSN)
한국건축시공학회 (The Korean Institute of Building Construction)
권호 표지
DOI QR코드

DOI QR Code

Knowledge Evolution in Construction Automation Research

  • Mun, Seong-Hwan (Department of Architectural Engineering, Chosun University) ;
  • Kim, Taehoon (Department of Architectural Engineering, Chosun University) ;
  • Lee, Ung-Kyun (Department of Architectural Engineering, Catholic Kwandong University) ;
  • Cho, Kyuman (Department of Architectural Engineering, Chosun University) ;
  • Lim, Hyunsu (Department of Architecture, Soonchunhyang University)
  • 투고 : 2020.09.18
  • 심사 : 2020.10.30
  • 발행 : 2020.12.20
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Construction automation and robotics have been widely adopted in the construction industry as a promising solution to such issues like a shortage of skilled labor and the difficulties workers face in harsh working environments. The analysis of the knowledge structure and its evolution from the existing articles helps identify essential knowledge elements and possible future research directions. This study attempts to (1) construct keyword networks from the papers published in the International Symposium on Automation and Robotics in Construction (ISARC), (2) investigate how keywords and keyword communities are associated with each other, and (3) examine the changes in the crucial keywords over time. Through cluster analysis, 79 keywords were categorized into four groups (BIM, Building construction, Sensing, and GPS as representative keywords) with similar structural positions. Research trends show that research themes related to Infrastructure, Construction equipment, and 3D have consistently received a large amount of attention, regardless of geographical region. Research on as-built status model utilization through BIM and Laser scanning and improving Energy performance is taking place more frequently. In contrast, research studies related to problem-solving based on Neural networks are not as common as previously. This study provides useful insights into the construction automation field, at both the macro and micro levels.

키워드

참고문헌

  1. Jin GH. A study on the innovation of construction technology for global industry. Construction Economy. 2019 Mar;86:36-44.
  2. Kim JY. Collaborative relationship analysis between members of apartment construction organizations. Journal of the Korea Institute of Building Construction. 2014 Jan;14(1):102-9. http://dx.doi.org/10.5345/JKIBC.2014.14.1.102
  3. Law J, Whittaker J. Mapping acidification research: A test of the co-word method. Scientometrics. 1992 Mar;23(3):417-61. https://doi.org/10.1007/BF02029807
  4. Newman MEJ, Girvan M. Finding and evaluating community structure in networks. Physical Review. 2004 Feb;69(2):026113. https://doi.org/10.1103/PhysRevE.69.026113
  5. Ding Y, Chowdhury GG, Foo S. Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing & Management. 2001 Nov;37(6):817-42. https://doi.org/10.1016/S0306-4573(00)00051-0
  6. Helms R, Buijsrogge K. Knowledge Network Analysis: A technique to analyze knowledge management. Proceedings of the 16th International Workshop on Database and Expert Systems Applications; 2005 Aug 22-26; Cophenhagen, Denmark. New York (USA): IEEE; 2005. p.410-4. 10.1109/DEXA.2005.127
  7. Lee SH, Kim HS. A study on activation plan of youth hostel using text mining technique: Focusing on Busan youth hostel ARPINA. The Journal of Industrial Innovation. 2018 Jun;34(2):267-88. 10.22793/indinn.2018.34.2.010
  8. Ban HJ, Jun JK. A study on the semantic network analysis of luxury hotel and business hotel through the big data. Culinary Science & Hospitality Research. 2019 Jan;25(1):18-28. 10.20878/cshr.2019.25.1.003
  9. Ahn SH, Lee SJ. Improving university homepage FAQ using semantic network analysis. Journal of Digital Convergence. 2018 Sep;16(9):11-20. https://doi.org/10.14400/JDC.2018.16.9.011
  10. Kim YS, Seo JW, Lee JB, Kim SK. A study on the development of technology roadmap for construction automation. Journal of the Korean Society of Civil Engineers. 2008 Jul;28(4):493-504.
  11. Lee JH, Ok CE, Choi HS, Kim YS. A development priority and technology roadmap for construction automation. Journal of the Architectural Institute of Korea (Structure &Construction). 2010 Oct;26(10):131-40.
  12. Son H, Kim C, Kim H, Han SH, Kim MK. Trend analysis of research and development on automation and robotics technology in the construction industry. KSCE Journal of Civil Engineering. 2010 Mar;14(2):131-9. https://doi.org/10.1007/s12205-010-0131-7
  13. Kim HJ, Jo NO, Shin KS. Text mining-based emerging trend analysis for the aviation industry. Journal of Intelligent Information Systems. 2015 Mar;21(1):65-82. https://doi.org/10.13088/jiis.2015.21.1.65
  14. Kim YH. Social Network Analysis. 3rd ed. Seoul: Pakyoungsa;2011.
  15. Kim EJ. Network analysis on the recognition of 'low cost carrier' using social big data. Journal of Tourism Management Research. 2019 May;23(3):767-82. https://doi.org/10.18604/tmro.2019.23.3.37
  16. Tao S, Aralbayeva S, Kim HS. A study of comparison between restaurant industries in Seoul and Busan through big data analysis. Culinary Science & Hospitality Research. 2018 Sep;24(7):109-18. https://doi.org/10.20878/cshr.2018.24.7.013