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Journal Article 증강현실을 활용한 영상 기반 소방시설 점검 시스템
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Authors
오다솜, 김정균, 이강복, 홍상기
Issue Date
2023-06
Citation
한국화재소방학회 논문지, v.37, no.3, pp.41-48
ISSN
2765-060X
Publisher
한국화재소방학회
Language
Korean
Type
Journal Article
DOI
https://dx.doi.org/10.7731/KIFSE.05a96a47
Abstract
With the rapid development of digital-based industrial structures, the construction industry is also rapidly adopting smart-based technologies and unmanned automation, leading to an increase in the construction of new buildings. To protect against fire, disasters, and other emergency situations, installing firefighting facilities is mandatory , and continuous management is required. However, owing to the increase in new buildings, the installation of firefighting facilities is increasing, but the manpower to manage and inspect these firefighting facilities is lacking. In this paper, a technical improvement plan is proposed for the existing analog method of facility inspection. By combining deep learning algorithm and augmented reality, a fire protection inspection system is developed and inspections are performed through wearable devices. To train the object detection model, we built a dataset of five types of firefighting facilities. The trained YOLO v4 model achieved a performance accuracy of 93.6%. The proposed system is expected to perform more convenient and reliable inspections and to help with fire safety management by enabling both fire safety professionals and the general public to learn about fire protection inspection systems and perform self-inspections.
KSP Keywords
Analog method, Augmented reality(AR), Construction industry, Detection model, Fire protection, Object detection, Performance accuracy, Rapid development, Technical improvement, Wearable device, deep learning(DL)
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC)
CC BY NC