Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

A Study on the Implement of AI-based Integrated Smart Fire Safety (ISFS) System in Public Facility

Full metadata record
DC Field Value Language
dc.contributor.authorLee, Myung Sik-
dc.contributor.authorSeo, Pill Sun-
dc.date.accessioned2024-08-08T08:31:43Z-
dc.date.available2024-08-08T08:31:43Z-
dc.date.issued2023-09-
dc.identifier.issn2234-7224-
dc.identifier.issn2288-9930-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/20653-
dc.description.abstractEven at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the realtime decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS). © (2023), (Korean Council on Tall Buildings and Urban Habitat). All Rights Reserved.-
dc.format.extent10-
dc.language영어-
dc.language.isoENG-
dc.publisher(사)한국초고층도시건축학회-
dc.titleA Study on the Implement of AI-based Integrated Smart Fire Safety (ISFS) System in Public Facility-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.21022/IJHRB.2023.12.3.225-
dc.identifier.scopusid2-s2.0-85184750048-
dc.identifier.bibliographicCitationInternational Journal of High-Rise Buildings, v.12, no.3, pp 225 - 234-
dc.citation.titleInternational Journal of High-Rise Buildings-
dc.citation.volume12-
dc.citation.number3-
dc.citation.startPage225-
dc.citation.endPage234-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorAI engine-
dc.subject.keywordAuthorCapacity constrained routing problem-
dc.subject.keywordAuthorDigital Twin-
dc.subject.keywordAuthorSafety digital transformation-
dc.subject.keywordAuthorSmart location guidance-
dc.subject.keywordAuthorTime-expanded graph network modeling-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > Department of Architectural Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Myung Sik photo

Lee, Myung Sik
College of Engineering (Department of Architectural Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE