導入建築資訊模型與本體論之室內避難收容所空間配置作法

AUTOMATED SPATIAL CONFIGURATION FOR INDOOR REFUGEE SHELTERS USING BUILDING INFORMATION MODELING AND ONTOLOGY

10.6652/JoCICHE.202311_35(7).0005

戴荏國(Jen-Kuo Tai)；劉展元(Chang-Yuan Liu)；朱峻平(Chun-Ping Chu)；王如觀(Ru-Guan Wang)；王蘇杰(Sujie Wang)；周建成(Chien-Cheng Chou)

收容所 ； 建築資訊模型 ； 本體論 ； 空間配置 ； refugee shelter ； building information modeling ； ontology ； space configuration

中國土木水利工程學刊

35卷7期（2023 / 11 / 01）

669 - 680

繁體中文;英文

依據我國災害防救法，政府有義務協助安置受災民眾，但目前我國並未有室內避難收容所空間配置之統一標準或模板建議，使得基層鄉鎮市區公所防災人員無從依循，加上地方人員異動頻繁及開設經驗可能不足，當實際災害發生時，往往造成在避難收容民眾及工作同仁有所抱怨，例如生活或作業空間不足、動線不佳及未設置適合功能設施空間等。本研究從國內外文獻，歸納整理出室內避難收容所空間配置之規則及實務經驗，嘗試定義我國室內避難收容所空間設施配置規則，並藉由建築資訊模型與本體論技術，發展自動化空間配置作法。此法有考量前述規則，並依收容民眾類型與基本休憩面積需求，產出該所空間配置圖及預估可收容人數，預期可協助基層防災人員更快速與動態調整空間配置，讓實際現場佈置時間及人員動線可更順暢，提升室內避難收容所營運品質。

According to the Disaster Prevention and Rescue Law of Taiwan, the government is obliged to assist in the resettlement of the affected people. However, at present, there is no uniform standard or template suggestion for the space allocation of indoor refugee shelters in Taiwan, which makes it difficult for the disaster prevention personnel in the grassroots townships and municipalities to follow. Additionally since the local personnel may change jobs frequently and lack of experience in setting up an indoor refugee shelter, when an actual disaster occurs, such a shelter often causes complaints from the residents and other colleagues. Among these complaints, the most common ones are insufficient living or working space, poor circulation, and no space for suitable functional facilities. This study summarizes the practical experience of indoor refugee shelter space allocation from the literature, attempts to define the rules of space facility allocation for indoor refugee shelters. This study also develops an automated space allocation method, with the help of building information modeling and ontology technology. This method takes into account the rules summarized, and according to the type of residents and the basic resting area requirements, it produces the space configuration map and the estimated number of people that can be accommodated. It is expected to help the grassroots disaster prevention personnel to adjust the space configuration more quickly and dynamically, so that the adequate actual on-site layout can be generated. Not only the time and personnel flow can be smoother, but the operational quality of the indoor refugee shelters can be improved.

1. (2019)。,內政部建築研究所。
2. Amailef, K.,Lu, J.(2013).Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services.Decision Support Systems,55(1),79-97.
3. American Red Cross(2018).American Red Cross, Mass Care Standards and Indicators, Washington, D.C., USA, p. 4 (2018)..
4. Azhar, S.(2011).Building Information Modeling (BIM): Trends, Benefits, Risks, and Challenges for the AEC Industry.Leadership and Management in Engineering,11(3),241-252.
5. Bader, S. R.,Grangel-Gonz´alez, I.,Tasnim, M.,Lohmann, S.(2019).Structuring the industry 4.0 landscape.24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA),Zaragoza, Spain:
6. Beetz, J.(2009).Eindhoven, Netherlands,Technische Universiteit Eindhoven.
7. Centers for Disease Control and Prevention(2019).Centers for Disease Control and Prevention, Environmental Health Disaster Shelters Assessment Guide, Atlanta, Georgia, USA, pp.1-3 (2019)..
8. Chang, C. H.,Chuang, M. L.,Tan, J. C.,Hsieh, C. C.,Chou, C. C..Indoor safety monitoring for falls or restricted areas using Wi-Fi channel state information and deep learning methods in mega building construction projects.Sustainability,14(22),15034.
9. Charlesraj, V.,Paul, C.(2014).Knowledge-based Building Information Modeling (K16-BIM) for facilities management.31st International Symposium on Automation and Robotics in Construction and Mining,Oulu, Finland:
10. Chen, A. Y.,Huang, T.(2015).Toward BIM-enabled decision making for in-building response missions.IEEE Transactions on Intelligent Transportation Systems,16(5),2765-2773.
11. Chou, C. C.,Chiang, C. T.,Wu, P. Y.,Chu, C. P.,Lin, C. Y.(2017).Spatiotemporal analysis and visualization of power consumption data integrated with building information models for energy savings.Resources, Conservation and Recycling,123,219-229.
12. Chou, C. C.,Jeng, A. P.,Chu, C. P.,Chang, C. H.,Wang, R. G.(2018).Generation and visualization of earthquake drill scripts for first responders using ontology and serious game platforms.Advanced Engineering Informatics,38,538-554.
13. Chou, J. S.,Cheng, M. Y.,Hsieh, Y. M.,Yang, I. T.,Hsu, H. T.(2019).Optimal path planning in real time for dynamic building fire rescue operations using wireless sensors and visual guidance.Automation in Construction,99,1-17.
14. De Nicola, A.,Missikoff, M.,Navigli, R.(2009).A software engineering approach to ontology building.Information Systems,34(2),258-275.
15. De Nicola, A.,Missikoff, M.,Navigli, R.(2009).A software engineering approach to ontology building information systems.Information System,34(2),258-275.
16. Deshpande, N.,Kumbhar, R.(2011).Construction and applications of ontology: Recent trends.DESIDOC Journal of Library & Information Technology,31(2),84-89.
17. Fu, C.,Liu, C.,Ishi, C.,Yoshikawa, Y.,Ishiguro, H.(2020).SeMemNN: A semantic matrix-based memory neural network for text classification.2020 IEEE 14th International Conference on Semantic Computing (ICSC),San Diego, California, USA:
18. Gao, X.,Pishdad-Bozorgi, P.(2019).BIM-enabled facilities operation and maintenance: A review.Advanced Engineering Informatics,39,227-247.
19. Hsieh, C. C.,Liu, C. Y.,Wu, P. Y.,Jeng, A. P.,Wang, R. G.,Chou, C. C.(2019).Building information modeling services reuse for facility management for semiconductor fabrication plants.Automation in Construction,102,270-287.
20. Kim, T. W.,Fischer, M.(2014).Ontology for representing building users’ activities in space-use analysis.Journal of Construction Engineering and Management,140(8),04014035.
21. Leite, F.,Akinci, B.(2012).Formalized representation for supporting automated identification of critical assets in facilities during emergencies triggered by failures in building systems.Journal of Computing in Civil Engineering,26(4),519-529.
22. Luo, H.,Peng, X.,Zhong, B.(2016).Application of ontology in emergency plan management of metro operation.Procedia Engineering,164,158-165.
23. Nunavath, V.,Prinz, A.(2017).Visualization of exchanged information with dynamic networks: A case study of fire emergency search and rescue operation.2017 IEEE 7th International Advance Computing Conference,Hyderabad, India:
24. Pouchard, L.,Ivezic, N.,Schlenoff, C.(2000).Ontology engineering for distributed collaboration in manufacturing.Proceedings of the AIS2000 Conference,Gaithersburg, Maryland, USA:
25. Pouchard, L.,Ivezic, N.,Schlenoff, C.(2000).Ontology engineering for distributed collaboration in manufacturing.Artificial Intelligence and Simulation Conference,Tucson, Arizona, USA:
26. Ren, Z.,Anumba, C.(2004).Multi-agent systems in construction–state of the art and prospects.Automation in Construction,13(3),421-434.
27. Tan, L.,Hu, M.,Lin, H.(2015).Agent-based simulation of building evacuation: Combining human behavior with predictable spatial accessibility in a fire emergency.Information Sciences,295,53-66.
28. Tsetsos, V.,Anagnostopoulos, C.,Kikiras, P.,Hadjiefthymiades, S.(2006).Semantically enriched navigation for indoor environments.International Journal of Web and Grid Services,2(4),453.
29. United States Department of Homeland Security - Federal Emergency Management Agency=FEMA(2016).Shelter Field Guide FEMA P-785.Washington, D.C., USA:
30. Volk, R.,Stengel, J.,Schultmann, F.(2014).Building information modeling (BIM) for existing buildings-Literature review and future needs.Automation in Construction,38,109-127.
31. Wang, R. G.,Wu, P. Y.,Liu, C. Y.,Tan, J. C.,Chuang, M. L.,Chou, C. C.(2022).Route planning for fire rescue operations in long-term care facilities using ontology and building information models.Buildings,12(7),1060.
32. Zhou, Z.,Goh, Y. M.,Shen, L.(2016).Overview and analysis of ontology studies supporting development of the construction industry.Journal of Computing in Civil Engineering,30(6),4016026.
33. 京都事情報館(2022)。京都市收容所運営マニュアル。日本:京都府。
34. 東京都福祉保健局，收容所管理運営の指針，東京都，日本，pp. 7-8 [Web page] https://www.fukushihoken.metro.tokyo.lg.jp/joho/soshiki/syoushi/syoushi/hinanjo-shishin/hinanjokanriunei3.html, Access date: 2023/1/1 (2022)。
35. 國家災害防救科技中心，「縣市政府防災 \ 防災任務怎麼做 \ 災民收容 – 防災易起來」，[Web page] https://easy2do.ncdr.nat.gov.tw/county/subject/shelter/sheltering, Access date: 2023/1/1 (2022)。
36. 許俊逸,徐景文,林傑,李文欽(2014)。BIM 帶來的變革與政府的前瞻作為。中國工程師學會工程雙月刊，87(5)，2-9。
37. 許秋玲、廖楷民、李香潔，「八八水災後災民收容任務之調整與檢討」，國家災害防救科技中心災害防救電子報，第 112 期，第 4 頁 (2014)。
38. 新竹縣政府(2020)。新竹縣政府，新竹縣地區災害防救計畫-第二篇風、水災害及土石流防救對策篇，第 65-73、94-103 頁(2020)。
39. 劉玉祥,盧鏡臣(2017)。鄉鎮層級地區災害防救計畫地震避難安置規劃與現實落差之評估。防災科學期刊，2，29-58。
40. 戴荏國(2023)。桃園，國立中央大學土木所防災與資訊應用組。