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18253 Fire data analysis and feature reduction using computational intelligence methods
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Bahrepour, M. and van der Zwaag, B.J. and Meratnia, N. and Havinga, P.J.M. (2010) Fire data analysis and feature reduction using computational intelligence methods. In: Advances in Intelligent Decision Technologies - Proceedings of the Second KES International Symposium IDT 2010, 28-30 July 2010, Baltimore, Maryland, USA. pp. 289-298. Smart Innovation, Systems and Technologies 4. Springer-Verlag. ISSN 2190-3018 ISBN 978-3-642-14615-2

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Official URL: http://dx.doi.org/10.1007/978-3-642-14616-9_28

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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.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-PS: Pervasive Systems
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:SENSEI: Integrating the PhySical with the Digital World of the Network of the Future
ID Code:18253
Status:Published
Deposited On:16 August 2010
Refereed:Yes
International:Yes
More Information:statisticsmetis

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