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Fire Data Analysis and Feature Reduction Using Computational Intelligence Methods

  • Majid Bahrepour
  • Berend Jan van der Zwaag
  • Nirvana Meratnia
  • Paul Havinga
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 4)

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.

Keywords

Sensor Node Mean Square Error Wireless Sensor Network Feed Forward Neural Network Input Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2010

Authors and Affiliations

  • Majid Bahrepour
    • 1
  • Berend Jan van der Zwaag
    • 1
  • Nirvana Meratnia
    • 1
  • Paul Havinga
    • 1
  1. 1.University of TwenteThe Netherlands

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