All Issue

2021 Vol.12, Issue 4 Preview Page

General Article

31 December 2021. pp. 410-421
Abstract
References
1
F. Zhao, O. Fashola, T. Olarewaju, and I. Onwumere, Smart city research: A holistic and state-of-the-art literature review. Cities. 119 (2021), 103406. 10.1016/j.cities.2021.103406
2
C. Rocon and C. Alvarez, Smart cities: selection of indicators for Vitória. International Journal of Sustainable Building Technology and Urban Development. 8(2) (2017), pp. 135-143. 10.12972/susb.20170011
3
G. Masik, I. Sagan, and J. Scott, Smart City strategies and new urban development policies in the Polish context. Cities. 108 (2021), 102970. 10.1016/j.cities.2020.102970
4
R. Janani, K. Renuka, A. Aruna, and K. Narayanan, IoT in smart cities: A contemporary survey. Global Transitions Proceedings. 2(2) (2021), pp. 187-193. 10.1016/j.gltp.2021.08.069
5
Electronics and Telecommunications Research Institute, The Study of Geospatial based on Realistic Contents Fusion and Mixed Realty Service Research Report, 2017.
6
S. Park, 3D GIS and Map Data Technology Trend, National IT Industry Promotion Agency Weekly Technology Trend Report, 2011.
7
H. Kang, Established Smart Disaster Safety Management Response System based on the 4th Industrial Revolution. Journal of Digital Contents Society. 19(3) (2018), pp. 561-567.
8
Korea Safety Map. Available at: http://www.safemap.go.kr/main/smap.do?flag=2 [Accessed on 13/8/2021].
9
J. Youn and T. Kim, Derivation of Building Fire Safety Assessment Factors for Generating 3D Safety Status Map. J. Korea Acad. Ind. Coop. Soc. 21 (2020), pp. 40-47.
10
F. Khalifa, An approach to define smart sustainable urbanism locally through expert's perspective. International Journal of Sustainable Building Technology and Urban Development. 12(1) (2021), pp. 14-26.
11
M.-Y. Choi and S. Jun, Fire Risk Assessment Models Using Statistical Machine Learning and Optimized Risk Indexing. Appl. Sci. 10 (2020), 4199. 10.3390/app10124199
12
D. Radke, A. Hessler, and D. Ellsworth, FireCast: Leveraging Deep Learning to PredictWildfire Spread. Proceedings of the Twen-ty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) 2019, pp. 4575-4581. 10.24963/ijcai.2019/636
13
J. Anderson-Bell, C. Schillaci, and A. Lipani, Predicting non-residential building fire risk using geospatial information and convolutional neural networks. Remote Sens. Appl. Soc. Environ. 21 (2021), 100470. 10.1016/j.rsase.2021.100470
14
M. Madaio, S.T. Chen, O. Haimson, W. Zhang, X. Cheng, M. Hinds-Aldrich, D.H. Chau, and B. Dilkina, Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta, Association for Computing Machinery International Conference 2016, pp. 13-17. 10.1145/2939672.2939682
15
E. Kim and K. Kim, A Study on the Construction and Institutionalization of Building Safety Management System, Architecture & Urban Research Institute: Sejong, Korea, 2019.
16
N. Wang, Y. Gao, C.Y. Li, and W.M. Gai, Integrated agent-based simulation and evacuation risk-assessment model for underground building fire: A case study. J. Build. Eng. 40 (2021), 102609. 10.1016/j.jobe.2021.102609
17
M. Yagoub and A. Jalil, Urban Fire Risk Assessment Using GIS: Case Study on Sharjah, UAE. Int. Geoinform. Res. Dev. J. 5 (2014), pp. 1-8.
18
D. Brzezińska and P. Bryant, Risk index method-a tool for building fire safety assessments. Appl. Sci. 11 (2021), 11083566. 10.3390/app11083566
19
Z. Masoumi, J. Genderen, and J. Maleki, Fire Risk Assessment in Dense Urban Areas Using Information Fusion Techniques. ISPRS Int. J. Geo-Inf. 8 (2019), 579. 10.3390/ijgi8120579
20
R. Nisanci, GIS based fire analysis and production of fire-risk maps: The Trabzon experience. Sci. Res. Essays. 5 (2010), pp. 970-977.
21
L. Wang, W. Li, W. Feng, and R. Yang, Fire risk assessment for building operation and maintenance based on BIM technology. Build. Environ. 205 (2021), 108188. 10.1016/j.buildenv.2021.108188
22
Z. Xia, H. Li, and Y. Chen, An Integrated Spatial Clustering Analysis Method for Identifying Urban Fire Risk Locations in a Network-Constrained Environment: A Case Study in Nanjing, China. ISPRS Int. J. Geo-Inf. 6 (2017), 370. 10.3390/ijgi6110370
23
H. Lee, S. Park, S. Roh, and S. Lee, Preliminary Items for Evaluating the Fire Risk Index of Deteriorated Building Districts using Spatial Information Technology. Proceedings of the Spring Annual Conference of Architectural Institute of Korea. April, 41(1) (2021), pp. 774-775.
24
S. Park and S. Roh, Proposal of a Plan for Linking Geospatial Information Convergence Technology for Evaluating the Fire Risk Index of Deteriorated Building Districts. Proceedings of the International Conference on Innovation Convergence Technology (ICICT20201). 2021 May, pp. 161-163.
25
H. Lee, S. Park, S. Roh, J. Ryu, B. Son, S. Ryu, S. Lee, and W. Park, Deriving Major Fire Risk Evaluation Items Utilizing Spatial Information Convergence Technology in Dense Areas of Small Obsolete Buildings. Sustainability. 13 (2021), 12593. 10.3390/su132212593
26
S. Park, J. Ryu, B. Son and S. Roh, Analysis of the relative importance of fire risk index evaluation items in deteriorated building districts using the analytic hierarchy process. International Journal of Sustainable Building Technology and Urban Development. 12(3) (2021), pp. 271-281.
Information
  • Publisher :Sustainable Building Research Center (ERC) Innovative Durable Building and Infrastructure Research Center
  • Publisher(Ko) :건설구조물 내구성혁신 연구센터
  • Journal Title :International Journal of Sustainable Building Technology and Urban Development
  • Volume : 12
  • No :4
  • Pages :410-421
  • Received Date :2021. 11. 19
  • Accepted Date : 2021. 12. 14
Journal Informaiton International Journal of Sustainable Building Technology and Urban Development International Journal of Sustainable Building Technology and Urban Development
  • scopus
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close