Advertisement

Applied Geomatics

, Volume 4, Issue 3, pp 143–153 | Cite as

Benefit of the integration of semantic 3D models in a fire-fighting VR simulator

  • Aitor MorenoEmail author
  • Álvaro Segura
  • Sisi Zlatanova
  • Jorge Posada
  • Alejandro García-Alonso
Original Paper

Abstract

Virtual reality (VR) simulators have become a great tool for training purposes, especially for risky and uncertain situations such as today’s widely extended driving or flying simulators. One of these cases is the fire-fighting simulators. The usage of a VR simulator to support the training process of fire fighters and managers has two main advantages. On one hand, it supports the simulation of complex scenarios like big cities, where a fire cannot be simulated in the real world; and on the other hand, fire-fighting VR simulators allow trainees to experience situations as close as possible to real fire events, thereby reducing the probability of accidents when they are going through training exercises with real fire. However, the success of the VR simulator depends on how close to reality the simulation process is, one of the most important aspects to ensure how realistic the scenarios shown in the training sessions are. This paper discusses how existing and dynamic 3D geoinformation can be loaded into a fire-fighting VR system and how the preservation of the semantic knowledge can benefit the user experience in the VR simulator. Semantic technologies are intended to help in the selection of information to get a seamless integration between the GIS data, the VR system and the tasks and users involved in the fire-fighting processes. The benefit of semantics is illustrated with some practical cases.

Keywords

Semantics Virtual reality Fire fighting Formalization Real time 3D models CityGML 

Notes

Acknowledgements

This work was supported by COST Action TU0801 “Semantic Enrichment of 3D City Models for Sustainable Urban Development”, and it was carried out in the context of project SIGEM, funded by the Spanish Industry Ministry through its Avanza I + D Programme. Dr. García-Alonso was supported by the Spanish MEC TIN2009-14380 and the Basque Government IT421-10.

Supplementary material

12518_2012_93_MOESM1_ESM.mpg (1.3 mb)
ESM 1 (MPG 1365 kb)
12518_2012_93_MOESM2_ESM.mpg (3 mb)
ESM 2 (MPG 3118 kb)
12518_2012_93_MOESM3_ESM.avi (4.9 mb)
ESM 3 (AVI 5010 kb)
12518_2012_93_MOESM4_ESM.avi (2.9 mb)
ESM 4 (AVI 2998 kb)
12518_2012_93_MOESM5_ESM.avi (1.4 mb)
ESM 5 (AVI 1476 kb)

References

  1. BIM (2006) National BIM Standard Purpose, US National Institute of Building Sciences Facilities Information Council, BIM Committee. Retrieved from: http://www.buildingsmartalliance.org/client/assets/files/bsa/nbimspurpose.pdf. Accessed 31 August 2011
  2. Breton T, Duthen Y (2008) Les simulations de propagation de feu en milieu urbain. hal-00287987, version 1 - 13 Jun 2008, Technical Report from Institut National Polytechnique de Toulousse (INPT). http://hal.archives-ouvertes.fr/hal-00287987/. Accessed 7 September 2012
  3. Bullex Safety (2011) Bullex digital safety fire training programs. http://www.bullexsafety.com. Accessed 31 August 2011
  4. CityGML(2011) Collaborative wiki with all relevant links and tools. http://www.citygmlwiki.org. Accessed 31 August 2011
  5. CityGML(2011) Exchange and storage of virtual 3D city models http://www.citygml.org/. Accessed 31 August 2011
  6. DC Water (2011) District of Columbia water and sewer authority. http://www.dcwater.com/hydrants/status.cfm. Accessed 31 August 2011
  7. Dumond Y (2008) Forest fire growth modelling with geographical information fusion. 11th International Conference on Information Fusion. June 30–July 3, 2008, Cologne, Germany, pp 1–6Google Scholar
  8. European Directive (2007) Directive 2007/2/EC of the European Parliament and of the council of 1 March 2007 establishing an infrastructure for spatial information in the European community (inspire). European Commission, BrusselsGoogle Scholar
  9. Fan Z, Zlatanova S (2011) Exploring ontologies for semantic interoperability of data in emergency response. Appl Geomatics 3(2):109–122CrossRefGoogle Scholar
  10. Finney M (1998) FARSITE: fire area simulator-model development and evaluation. Res Pap RMRS-RP-4, vol 1. USDA Forest Service, Rocky Mountain Research Station, Ogden, UT, 47 ppGoogle Scholar
  11. Iwami T, Ohmiya Y, Hayashi Y, Kagiya K, Takahashi W, Naruse T (2004) Simulation of city fire. Fire Sci Technol 23(2):132–140CrossRefGoogle Scholar
  12. Kirila Fire (2011) Kirila Fire training facilities. http://www.kirilafire.info. Accessed 31 August 2011
  13. Kolbe T, Grger G, Plmer L (2005) CityGML interoperable access to 3D city models. In: Oosterom ZSFF P (ed) Proceedings of the International Symposium on Geo-information for Disaster Management, Springer, HeidelbergGoogle Scholar
  14. Kuhn W (2005) Geospatial semantics: why, of what, and how? J Data Semant Spec Issue Semant-Based Geogr Inf Syst 534:1–24Google Scholar
  15. Ling Y, Zhou F, Wang X, Yang B (2009) Integration of heterogeneous geospatial data based on middleware technology. WASE Int Conf Inf Eng 2:314–317CrossRefGoogle Scholar
  16. Marchese M, Vaccari L, Shvaiko P, Pane J (2008) An application of approximate ontology matching in eResponse. In: Proceedings 5th International Conference on Information Systems for Crisis Response and Management (ISCRAM), Washington DC, USA, May 4–7 2008, pp 294–304Google Scholar
  17. Moreno A, Segura A, Korchi A, Posada J, Otaegui O (2011) Interactive urban and forest fire simulation with extinguishment support. In: Advances in 3D geo information sciences, Lecture notes in geoinformation and cartography, Springer, Heidelberg, pp 131–148Google Scholar
  18. OpenFireMap (2011) Using OpenStreetMap to show the location of fire stations and fire hydrant in Nuremberg. http://toolserver.org/˜ti/ofm2/. Accessed 31 August 2011
  19. Rothermel R (1972) A mathematical model for predicting fire spread in wildland fuel. Tech. Rep., USDA, Washington, DCGoogle Scholar
  20. Scawthorn C (2008) Fire following earthquake, supplemental study for the shakeout scenario: the shakeout scenario. US Geological Survey and California Geological Survey, Pasadena, Tech. Rep., US Geol Surv Open File Rep 2008–1150, California Geological Survey Preliminary Report 2 version 1.0, US Geological Surv Circu 1324, California Geological Survey Special Report 207 version 1.0Google Scholar
  21. Stanimirovic A, Bogdanovic M, Stoimenov L (2009) Data access layer generation for interoperable GIS environments. In: Proceedings of the 12th AGILE International Conference on GI Science, Hannover, Germany, June 2009Google Scholar
  22. Stoimenov L, Predic B, Mihajlovic V, Stankovic M (2005) GIS interoperability platform for emergency management in local community environment. In: Proceedings of 8th AGILE Conference on GIScience, Estoril, Portugal, May 2005Google Scholar
  23. Tanaka T, Himoto K (2006) Physics-based model of urban fire spread and mitigation of post-earthquake fire risk in historic cities. Abstr Ann Disaster Prev Res Inst Kyoto Univ (CD-ROM) 49:1–5Google Scholar
  24. Toro C, Posada J, Termenón M, Oyarzun J, Falcón J, Gabrys B, Howlett R, Jain L (2006) Knowledge based tools to support the structural design process. Lect Notes Comput Sci 4251(679):686Google Scholar
  25. Weise DR, Biging GS (1996) Effects of wind velocity and slope on flame properties. Can J For Res 26:1849–1858CrossRefGoogle Scholar
  26. Zlatanova S (2008) Sii for emergency response: the 3rd challenges. In: ISPRS Archives, the XXI ISPRS Congress, Part B4-TYC IV, Beijing, July 2008, pp 1631–1637Google Scholar

Copyright information

© Società Italiana di Fotogrammetria e Topografia (SIFET) 2012

Authors and Affiliations

  • Aitor Moreno
    • 1
    Email author
  • Álvaro Segura
    • 1
  • Sisi Zlatanova
    • 2
  • Jorge Posada
    • 1
  • Alejandro García-Alonso
    • 3
  1. 1.VicomtechSan SebastiánSpain
  2. 2.Section GIS-technology, OTBDelft University of TechnologyDelftThe Netherlands
  3. 3.University of the Basque CountrySan SebastiánSpain

Personalised recommendations