Information Systems Frontiers

, Volume 14, Issue 3, pp 725–739 | Cite as

Intelligent forest fire monitoring system

Article

Abstract

This paper presents iForestFire, an Environmental Monitoring Information System for forest fire protection. The system is composed of several components, each having a particular function. Automatic fire detection is a crucial component of the system. It is based on various complex image processing algorithms. Complexity of the system also emerges from integration, based on multi agent technology, of different environment information. The presented system contributes to the environment protection and is in use in Croatia for several years.

Keywords

Environmental Monitoring Information Systems Software architecture Image processing Data organization Fire protection 

References

  1. Beck, K., & Andres, C. (2005). Extreme programming explained: Embrace change (2nd Edition). Addison-Wesley.Google Scholar
  2. Bellifemine, F. L., Caire, G., & Greenwood, D. (2007). Developing multi-agent systems with JADE. John Wiley & Sons.Google Scholar
  3. Benezeth, Y., Jodoin, P. M., Emile, B., Laurent, H., & Rosenberger, C. (2008). Review and evaluation of commonly-implemented background subtraction algorithms. Proc. 19th International Conference on Pattern Recognition, Tampa, Florida, USA, pp 1–4.Google Scholar
  4. Bodrozic, L. J., Stipanicev, D., & Stula, M. (2006). Agent based data collecting in a forest fire monitoring system. Proc. International Conference on Software, Telecommunications and Computer Networks, Split-Dubrovnik, Croatia, pp 326–330.Google Scholar
  5. Collins, R., Lipton, A., Kanade, T., Fujiyoshi, H., Duggins, D., Tsin, Y., et al. (2000). A system for video surveillance and monitoring. Tech. report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University.Google Scholar
  6. EUMETSAT Active Fire Monitoring (FIR). http://www.eumetsat.int/. Accessed 07 December 2010.
  7. Fire Monitoring, Mapping, and Modeling (Fire M3). http://cwfis.cfs.nrcan.gc.ca/en_CA/background/summary/fm3. Accessed 12 October 2010.
  8. FireWatch. http://www.fire-watch.de/cms/. Accessed 29 September 2010.
  9. Forest Fire Finder. http://www.ngns-is.com/html/florestas/fff_intro_eng.html. Accessed 29 September 2010.
  10. Forgy, C. (1982). Rete: a fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence, 19, 17–37.CrossRefGoogle Scholar
  11. Fukunaga, K. (1993). Statistical pattern recognition. In C. H. Chen, L. F. Pau, & P. S. P. Wang (Eds.), Handbook of pattern recognition and computer vision (pp. 33–60). River Edge: World Scientific Publishing Co.CrossRefGoogle Scholar
  12. Han, S., Youn, H. Y., & Song, O. (2010). Efficient category-based service discovery on multi-agent platform. Information Systems Frontiers, doi:10.1007/s10796-010-9281-x
  13. Isakowitz, T., Bieber, M., & Vitali, F. (1998). Web information systems. Communications of the ACM, doi:10.1145/278476.278490
  14. Jain, A. K. (1989). Fundamentals of digital image processing. Prentice-Hall, Inc.Google Scholar
  15. Jakovcevic, T., Stipanicev, D., & Krstinic, D. (2009). False Alarm Reduction in Forest fire Video Monitoring System. Proc. of MIPRO 2009, 32nd International Convention, Opatija, Croatia, 3, 265–270.Google Scholar
  16. Krstinic, D., Stipanicev, D., & Jakovcevic, T. (2009). Histogram-based smoke segmentation in forest fire detection system. Information Technology and Control, 38(3), 237–244.Google Scholar
  17. MacEachren, A. M. (2010). Geovisual Analytics for Crisis Management: Moving Beyond GIS. ISCRAM'10 Conference Proceeding 2010, Seattle, USA.Google Scholar
  18. Meer, P. (2004). Robust techniques for computer vision. In G. Medioni & S. B. Kang (Eds.), Emerging topics in computer vision (pp. 107–190). Prentice Hall.Google Scholar
  19. Ministry of the Interior, statistical report. http://policija.hr/mup.hr/UserDocsImages/statistika/2007/statistika_pozari.pdf. Accessed 20 September 2010.
  20. MODIS Rapid Response System. http://rapidfire.sci.gsfc.nasa.gov/. Accessed 10 July 2010.
  21. Piccardi, M. (2004). Background subtraction techniques: a review. Proc. of IEEE SMC 2004 International Conference on Systems, Man and Cybernetics, 4, 3099–3104.Google Scholar
  22. Puras, J. C., & Iglesias, C. A. (2009), Disasters2.0. Application of Web2.0 technologies in emergency situations. Conference on Information Systems for Crisis Response and Management, ISCRAM'09 Conference Proceeding 2009, Gothenburg, Sweden.Google Scholar
  23. Rothermel, R. C. (1972). A mathematical model for predicting fire spread in wildland fuels, Research Paper INT-115. United States Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden.Google Scholar
  24. Scott, D. W., & Sain, S. R. (2004). Multi-dimensional density estimation. In C. R. Rao & E. J. Wegman (Eds.), Handbook of statistics—data mining and computational statistics (v.23, pp. 229–263). Elsevier.Google Scholar
  25. Seric, L. J. (2010). PhD report Agent based environmental intelligence, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split.Google Scholar
  26. Stipanicev, D., Vuko T., Krstinic, D., Stula, M., & Bodrozic, L. J. (2006). Forest fire protection by advanced video detection system—croatian experiences. Proceedings of the third TIEMS Workshop-Improvement of Disaster Management System, Trogir, Croatia.Google Scholar
  27. Stipanicev, D., Bugaric, M., & Seric, L. J. (2009a). Integration of forest fire video monitoring system and geographic information system. Proc. of the 51st Int. Symp. ELMAR 2009, Zadar, Croatia, pp 1–5.Google Scholar
  28. Stipanicev, D., Stula, M., Krstinic, D., & Seric, L. J. (2009b). Agent based intelligent forest fire monitoring system. Proc. of MIPRO 2009, 32nd International Convention, Opatija, Croatia, 3, pp 260–265.Google Scholar
  29. Summary Report on the Status of Environmental Monitoring and Reporting in Europe by Nesis project. http://www.nesis.eu/documents/d3.1.sop_report_revised%20version_v6.1_100331.pdf. Accessed 01 October 2010.
  30. Szyperski, C. (1998). Component software: beyond object-oriented programming. Addison-Wesley.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering, Machine Engineering and Naval ArchitectureUniversity of SplitSplitCroatia

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