Abstract
Fire is basically the fast oxidation of a substance that produces gases and chemical productions. These chemical productions can be read by sensors to yield an insight about type and place of the fire. However, as fires may occur in indoor or outdoor areas, the type of gases and therefore sensor readings become different. Recently, wireless sensor networks (WSNs) have been used for environmental monitoring and real-time event detection because of their low implementation costs and their capability of distributed sensing and processing. In this paper, the authors investigate spatial analysis of data for indoor and outdoor fires using data-mining approaches for WSN-based fire detection purposes. This paper also delves into correlated data features in fire data sets and investigates the most contributing features for fire detection applications.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bahrepour, M., Meratnia, N., Havinga, P.J.M.: Automatic fire detection: a survey from wireless sensor network perspective. Technical Report TR-CTIT-08-73, Centre for Telematics and Information Technology, University of Twente, Enschede (2008) ISSN 1381-3625
Bahrepour, M., Meratnia, N., Havinga, P.J.M.: Use of AI techniques for residential fire detection in wireless sensor networks. In: AIAI 2009, Thessaloniki, Greece (2009)
Bahrepour, M., Meratnia, N., Havinga, P.J.M.: Sensor fusion-based event detection in wireless sensor networks. In: SensorFusion 2009, Toronto, Canada. IEEE, Los Alamitos (2009)
Bahrepour, M., Zhang, Y., Meratnia, N., Havinga, P.J.M.: Use of event detection approaches for outlier detection in wireless sensor networks. In: ISSNIP 2009, Melbourne, Australia (2009)
Brain, M.: How smoke detectors work (2000), http://home.howstuffworks.com/smoke1.htm
Jin, G., Nittel, S.: NED: an efficient noise-tolerant event and event boundary detection algorithm in wireless sensor networks. In: 7th International Conference on Mobile Data Management. IEEE Computer Society, Los Alamitos (2006)
Kohonen, T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics 43, 59–69 (1982)
Lee, B.S., Alexander, M.E., Hawkes, B.C., Lynham, T.J., Stocks, B.J., Englefield, P.: Information systems in support of wildland fire management decision making in Canada. Computers and Electronics in Agriculture 37, 185–198 (2002)
Li, D., Wong, K.D., Hu, Y.H., Sayeed, A.M.: Detection, classification, and tracking of targets. Signal Processing Magazine 19(2), 17–29 (2002)
Liang, Q., Wang, L.: Event detection in sensor networks using fuzzy logic system. In: EEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, Orlando, FL, USA (2005)
Lim, Y.-s., Lim, S., Choi, J., Cho, S., Kim, C.-k., Lee, Y.-W.: A fire detection and rescue support framework with wireless sensor networks. In: International Conference on Convergence Information Technology, pp. 135–138. IEEE Computer Society, Los Alamitos (2007)
Marin-Perianu, M., Havinga, P.: D-FLER – a distributed fuzzy logic engine for rule-based wireless sensor networks. In: Ichikawa, H., Cho, W.-D., Satoh, I., Youn, H.Y. (eds.) UCS 2007. LNCS, vol. 4836, pp. 86–101. Springer, Heidelberg (2007)
Milke, J.A.: Using multiple sensors for discriminating fire detection. In: Fire Suppression and Detection Research Application Symposium, National Fire Protection Research Foundation,, pp. 150–164 (1999)
Milke, J.A., McAvoy, T.J.: Analysis of signature patterns for discriminating fire detection with multiple sensors. Fire Technology 31(2), 120–136 (1995)
National Interagency Fire Center: Fire Information – National Fire News, http://www.nifc.gov/fire_info/nfn.htm (March 17, 2010)
Segal, M.L., Antonio, F.P., Elam, S., Erlenbach, J., de Paolo, K.R.: Method and apparatus for automatic event detection in a wireless communication system, USA Patent (2000)
Vu, C.T., Beyah, R.A., Li, Y.: Composite event detection in wireless sensor networks. In: IEEE International, Performance, Computing, and Communications Conference, IPCCC 2007 (2007)
Werner-Allen, G., Lorincz, K., Ruiz, M., Marcillo, O., Johnson, J., Lees, J., Welsh, M.: Deploying a wireless sensor network on an active volcano. IEEE Internet Computing 10(2), 18–25 (2006)
Wikipedia: Artificial neural network, http://en.wikipedia.org/wiki/Artificial_neural_network (accessed in March 2010)
Xue, W., Luo, Q., Chen, L., Liu, Y.: Contour map matching for event detection in sensor networks. In: International Conference on Management of Data. ACM, New York (2006)
Zoumboulakis, M., Roussos, G.: Escalation: complex event detection in wireless sensor networks. In: Kortuem, G., Finney, J., Lea, R., Sundramoorthy, V. (eds.) EuroSSC 2007. LNCS, vol. 4793, pp. 270–285. Springer, Heidelberg (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Berlin Heidelberg
About this paper
Cite this paper
Bahrepour, M., van der Zwaag, B.J., Meratnia, N., Havinga, P. (2010). Fire Data Analysis and Feature Reduction Using Computational Intelligence Methods. In: Phillips-Wren, G., Jain, L.C., Nakamatsu, K., Howlett, R.J. (eds) Advances in Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14616-9_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-14616-9_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14615-2
Online ISBN: 978-3-642-14616-9
eBook Packages: EngineeringEngineering (R0)