DOI QR코드

DOI QR Code

A Study on Risk Situation Recognition Using OpenCV

OpenCV를 활용한 위험 상황 인식에 관한 연구

  • 김동현 (청암대학교 전기제어과) ;
  • 김성열 (울산과학대학교 IT응용기술학부)
  • Received : 2021.01.28
  • Accepted : 2021.04.17
  • Published : 2021.04.30

Abstract

Construction sites have various risk factors. There are various approaches to reduce safety accidents, but they have limitations to some extent. By utilizing the wireless communication technology of IT and the rapidly developing image processing technology, it will be possible to reduce accidents at the construction site if risk factors are identified and actively responded to. Therefore, in this study, a system that can detect risk factors of construction sites in advance is constructed, and a system is proposed to discover and respond to risk factors of construction sites using OpenCV for the purpose of real-time computer vision.

건설 현장은 다양한 위험요소가 존재하고 있다. 안전재해를 줄이고자하는 다양한 접근이 있으나 어느 정도 한계성을 가지고 있다. IT의 무선통신 기술과 빠르게 발전하고 있는 이미지 처리 기술을 활용하여 위험요소를 사전에 식별하고 능동적으로 대응한다면 건설 현장에서의 재해를 감소시킬 수 있을 것이다. 따라서 본 연구에서는 건설 현장의 위험요소를 사전에 발견할 수 있는 시스템을 구성하고 실시간 컴퓨터 비전을 목적으로 한 OpenCV를 이용하여 건축현장의 위험요소를 발견하고 대응할 수 있도록 하는 시스템을 제안하였다.

Keywords

References

  1. KOSHA(Korea Occupational Safety and Health Agency), "2019 Industrial Accident Analysis," Korea Occupational Safety and Health Agency report, Jan. 2021.
  2. D. Kim, "A Study on the Classification of Risk Factors for Image Recognition Technology Application in Construction," Master's thesis, Chung-Ang University Graduate School, 2019.
  3. Y. Yun, K. Jeong, J. Kim, and S. Kim, "A study on the effect of reducing accidents at construction sites through the introduction of a specialized safety patrol management system (SPMS)," In Proc. Architectural Institute of Korea, vol. 35, no. 1, 2015, pp. 521-522.
  4. N. Park, J. Seo, and Y. Kim, "Design of Construction Site Safety Management System based IT Technology," In Proc. Korea Institute of construction Engneering and Management Conf. National university students, Suwon, Korea, 2015.11. pp. 184-187.
  5. G. Jeong, "A Study on the Actual Condition Analysis and Improvement Plan of Safety Management in Construction Sites," Master's thesis, Seoul National University of Science and Technology Graduate School, 2015.
  6. Y. Kim, "A Study on thme Efficiency Plan of Safety Management in Apartment Construction Sppot," Master's thesis, Seoul Industrial University Graduate School, 2003.
  7. J. Yun, "Improvement Measures of Safty & Health Education for Construction Disaster Reduction," Master's thesis, Hanbat National University Graduate School, 2016.
  8. H. Kim, "Study on the Activation Plan of Preliminary Safety Management in the Construction Works," Master's thesis, Hanyang University Graduate School, 2010.
  9. Y. Keon, "Development of Construction Safety Information System for Ensuring Safety," Master's thesis, Myongji University Graduate School, 2005.
  10. H. Ryu and T. Kim, "Development of a safety accident prevention system for construction equipment utilizing IoT and RTLS technology," Journal of the Korea Convergence Society, vol. 10, no. 9, 2019, pp. 179-186.
  11. S. Kim, C. Kang, and H. Ryu, "IoT-based Dangerous Zone Alarming System for Safety Management in Construction Sites," Journal of the Korea Convergence Society, vol. 10. no. 10, 2019. pp. 107-115. https://doi.org/10.15207/JKCS.2019.10.10.107
  12. S. Park, "UConstruction site safety management system development using USN," Master's thesis, Yeungnam University Graduate School, 2013.
  13. B. Choi, "USN-based real-time monitoring system for construction safety," Master's thesis, Busan University Graduate School, 2009.
  14. J. Lee, "AI image recognition technology trend," Journal of Telecommunications Technology Association, no. 187, 2020, pp. 44-51.
  15. S. Jun, M. Kim and H. Jun Kim, "A Study on the Analysis of Architectural Spatial Information Using Visual Cognitive Process of Image Analysis Technology - Focus on disaster response information for micro drone," In Proc. Architectural Institute of Korea, vol. 37, no. 2, 2017, pp. 25-27.
  16. S. Lee, "OpenCV-based Object Traking System," Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, vol. 6, no. 5, 2016. pp. 29-37. https://doi.org/10.14257/AJMAHS.2016.05.37
  17. S. Shim and S. Choi, "Development on Identification Algorithm of Risk Situation around Construction Vehicle using YOLO-v3," Journal of the Korea Academia-Industrial cooperation Society, vol. 20, no. 7, 2019, pp. 622-629. https://doi.org/10.5762/KAIS.2019.20.7.622
  18. D. Yun, and M. Moon, "Development of Kid Height Measurement Application based on Image using Computer Vision," Journal of the Korea Institute of Electronic Communication Sciences, vol. 16, no. 01, 2021, pp. 117-124. https://doi.org/10.13067/JKIECS.2021.16.1.117
  19. C. Yoon, "The study of Authorized/Unauthorized Vehicle Recognition System using Image Recognition with Neural Network," Journal of the Korea Institute of Electronic Communication Sciences, vol. 15 no. 2, 2020, pp. 299-306. https://doi.org/10.13067/JKIECS.2020.15.2.299