Skip to main content

A Markovian Agent Model for Fire Propagation in Outdoor Environments

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6342))

Abstract

Markovian Agent Models are a rather new modeling technique to deal with complex systems composed by a multitude of interacting entities, whose spatial location is also relevant in determining their interaction. An example of application to the study of outdoor fire propagation is provided. The dynamic of this phenomenon strongly depends both on the type of materials being incinerated and on the wind direction and intensity. Therefore, the ability of the model to correctly reproduce the fire propagation is closely related to the spatial dependent interactions among agents. Moreover, the model is flexible enough to analyse scenarios in variable environmental conditions, such as wind direction and intensity, and in the presence of fire-barriers which prevent flames from propagating.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, D.H., Catchpole, E.A., DeMestre, N.J., Parkes, T.: Modeling the spread of grass fires. J. Aust. Math. Soc (B) 23, 451–466 (1982)

    Article  MATH  Google Scholar 

  2. Abdalhap, B.: A Methodology to Enhance the Prediction of Forest Fire Propagation. Phd thesis, Universitat Autnoma de Barcelona, Spain (2004), http://www.tdx.cat/TDX-1124104-161420/

  3. Bruneo, D., Scarpa, M., Bobbio, A., Cerotti, D., Gribaudo, M.: Analytical modeling of swarm intelligence in wireless sensor networks through Markovian Agents. In: VALUETOOLS 2009, ICST/ACM (October 2009)

    Google Scholar 

  4. Calafate, C.T., Lino, C., Cano, J.C., Manzoni, P.: Modeling emergency events to evaluate the performance of time-critical WSNs. In: IEEE Symposium on Computers and Communications (ISCC 2010), Riccione, Italy (June 2010)

    Google Scholar 

  5. Cerotti, D., Gribaudo, M., Bobbio, A.: Disaster Propagation in Heterogeneous Media via Markovian Agents. In: 3rd International Workshop on Critical Information Infrastructures Security (2008)

    Google Scholar 

  6. Doolin, D.M., Sitar, N.: Wireless sensors for wildfire monitoring. In: Sensors and smart structures technologies for civil, mechanical, and aerospace systems, San Diego, California, USA (2005)

    Google Scholar 

  7. Gribaudo, M., Bobbio, A.: Performability analysis of a sensor network by interacting markovian agents. In: Proceedings 8-th International Workshop on Performability Modeling of Computer and Communication Systems, PMCCS-8 (2007)

    Google Scholar 

  8. Bilgili Kucuk, O., Baysal, E., Baysal, I.: Fire development from a point source in surface fuels of a mature anatolian black pine stand. Turkish Journal of Agriculture and Forestry 31, 263–273 (2008)

    Google Scholar 

  9. Cerotti, D., Gribaudo, M., Bobbio, A.: Analysis of on-off policies in sensor networks using interacting Markovian agents. In: 4th Int. Workshop on Sensor Networks and Systems for Pervasive Computing - PerSens 2008, pp. 300–305 (2008)

    Google Scholar 

  10. Rehm, R.G.: The effects of winds from burning structures on ground-fire propagation at the wildland-urban interface. Combustion Theory and Modelling 12, 477–496 (2008)

    MATH  Google Scholar 

  11. Scott, R.E., Burgan, J.H.: Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. Gen. Tech. Rep. RMRS-GTR-153. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station (2005)

    Google Scholar 

  12. Trivedi, K.S.: Probability and statistics with reliability, queuing and computer science applications. John Wiley and Sons Ltd., Chichester (2002)

    MATH  Google Scholar 

  13. Li, Y., Wang, Z., Song, Y.: Wireless sensors network design for wildfire monitoring. In: Proceedings of the 6th IEEE World Congress on Intelligent Control and Automation, San Diego, California, USA (2006)

    Google Scholar 

  14. Yu, L., Wang, N., Meng, X.: Real-time forest fire detection with wireless sensor networks. In: Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing, vol. 2, pp. 1214–1217 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cerotti, D., Gribaudo, M., Bobbio, A., Calafate, C.T., Manzoni, P. (2010). A Markovian Agent Model for Fire Propagation in Outdoor Environments. In: Aldini, A., Bernardo, M., Bononi, L., Cortellessa, V. (eds) Computer Performance Engineering. EPEW 2010. Lecture Notes in Computer Science, vol 6342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15784-4_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15784-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15783-7

  • Online ISBN: 978-3-642-15784-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics