Intelligent forest fire monitoring system
- 728 Downloads
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.
KeywordsEnvironmental Monitoring Information Systems Software architecture Image processing Data organization Fire protection
- Beck, K., & Andres, C. (2005). Extreme programming explained: Embrace change (2nd Edition). Addison-Wesley.Google Scholar
- Bellifemine, F. L., Caire, G., & Greenwood, D. (2007). Developing multi-agent systems with JADE. John Wiley & Sons.Google Scholar
- 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
- 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
- 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
- EUMETSAT Active Fire Monitoring (FIR). http://www.eumetsat.int/. Accessed 07 December 2010.
- Fire Monitoring, Mapping, and Modeling (Fire M3). http://cwfis.cfs.nrcan.gc.ca/en_CA/background/summary/fm3. Accessed 12 October 2010.
- FireWatch. http://www.fire-watch.de/cms/. Accessed 29 September 2010.
- Forest Fire Finder. http://www.ngns-is.com/html/florestas/fff_intro_eng.html. Accessed 29 September 2010.
- 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
- Isakowitz, T., Bieber, M., & Vitali, F. (1998). Web information systems. Communications of the ACM, doi: 10.1145/278476.278490
- Jain, A. K. (1989). Fundamentals of digital image processing. Prentice-Hall, Inc.Google Scholar
- 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
- 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
- MacEachren, A. M. (2010). Geovisual Analytics for Crisis Management: Moving Beyond GIS. ISCRAM'10 Conference Proceeding 2010, Seattle, USA.Google Scholar
- 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
- Ministry of the Interior, statistical report. http://policija.hr/mup.hr/UserDocsImages/statistika/2007/statistika_pozari.pdf. Accessed 20 September 2010.
- MODIS Rapid Response System. http://rapidfire.sci.gsfc.nasa.gov/. Accessed 10 July 2010.
- 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
- 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
- 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
- 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
- Seric, L. J. (2010). PhD report Agent based environmental intelligence, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split.Google Scholar
- 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
- 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
- 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
- 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.
- Szyperski, C. (1998). Component software: beyond object-oriented programming. Addison-Wesley.Google Scholar