Earticle

초록

영어

Purpose: The purpose of this paper is to develop a deep learning model to detect fire extinguishers in images taken from CCTVs in underground utility tunnels. Method: Various fire extinguisher images were collected for detection of fire extinguishers in the running-based underground utility tunnel, and a model applying the One-stage Detector method was developed based on the CNN algorithm. Result: The detection rate of fire extinguishers photographed within 10m through CCTV video in the underground common area is over 96%, showing excellent detection rate. However, it was confirmed that the fire extinguisher object detection rate drops sharply at a distance of 10m or more, in a state where it is difficult to see with the naked eye. Conclusion: This paper develops a model for detecting fire extinguisher objects in underground common areas, and the model shows high performance, and it is judged that it can be used for underground common area digital twin model synchronizing.

한국어

연구목적: 본 논문은 지하공동구 내 CCTV에서 촬영된 영상에서 소화기를 탐지하기 위해 딥러닝 모델을 개발하는데 목적이 있다. 연구방법: 딥러닝 기반 지하공동구 내 소화기 탐지를 위해 다양한 소화기 이미 지를 수집하였으며 CNN 알고리즘을 기반으로 하여 One-stage Detector 방식을 적용한 모델을 개발하였 다. 연구결과: 지하공동구 내 CCTV 영상을 통해 10m 이내의 거리에서 촬영되는 소화기의 검출률은 96%이상으로 우수한 검출률을 보여준다. 다만 10m 이상의 거리에서는 육안으로도 확인하기 힘든 상태 로, 소화기 객체 검출률이 급격하게 낮아지는 것을 확인하였다. 결론: 본 논문은 지하공동구 내 소화기 객체를 검출하는 모델을 개발하였으며, 해당 모델이 높은 성능을 보여 지하공동구 디지털트윈 모델 연 동에 활용할 수 있을 것으로 판단된다.

목차

ABSTRACT
요약
서론
연구 배경 및 목적
문헌조사
딥러닝 기반 소화기 탐지를 위한 데이터셋 구축
이미지데이터 수집
데이터 전처리
딥러닝 기반 소화기 객체 검출 모델 구축
딥러닝 기반 소화기 탐지 모델 학습
딥러닝 기반 소화기 탐지 모델 평가
지하공동구 영상 테스트
결론
References

저자

• 박상미 [ Sangmi Park | Post-Doctor Researcher, Korea Institute of Civil Engineering and Building Technology, Department of Future and Smart Construction and BIM Cluster, Goyang, Republic of Korea ]
• 홍창희 [ Changhee Hong | Research Fellow, Korea Institute of Civil Engineering and Building Technology, Department of Future and Smart Construction and BIM Cluster, Goyang, Republic of Korea ] Corresponding Author
• 박승화 [ Seunghwa Park | Senior Researcher, Korea Institute of Civil Engineering and Building Technology, Department of Future and Smart Construction and BIM Cluster, Goyang, Republic of Korea ]
• 이재욱 [ Jaewook Lee | Senior Researcher, Korea Institute of Civil Engineering and Building Technology, Department of Future and Smart Construction and BIM Cluster, Goyang, Republic of Korea ]
• 김정수 [ Jeongsoo Kim | Research Specialist, Korea Institute of Civil Engineering and Building Technology, Department of Future and Smart Construction and BIM Cluster, Goyang, Republic of Korea ]

참고문헌