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International Conference on Ad Hoc Networks

ADHOCNETS 2019: Ad Hoc Networks pp 302–313Cite as

Rail Vehicle Fire Warning System Based on Gas Vapor Sensor Network

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Abstract

Fire accidents in rail vehicles often cause unpredictable catastrophic losses due to high population density and closed environment. At present, existing smart fire prevention schemes are mostly based on the emergency treatments after the fire. Since it takes time for firefighters arriving at the fire, the fire may already become disastrous at that time. This paper proposes a detection framework and also detailed sensing and data processing technologies, in order to detect volatile flammable liquid in closed spaces such as rail vehicle carriages. The proposed mechanism is designed to eliminate potential fire disaster based on gas vapor sensor network. Experiment results shows the proposed surveillant system can detect gasoline vapor components in small space with high sensitivity while maintaining very low false detection rates to external interferences.

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Author information

Authors and Affiliations

  1. China Railway Signal & Communication Shanghai Engineering Bureau Group Co., Ltd., Shanghai, 200436, China

    Min Ai

  2. Beijing Engineering Research Center for IoT Software and Systems, Information Department, Beijing University of Technology, Beijing, 100124, China

    Rui Tian

Authors
  1. Min Ai
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  2. Rui Tian
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Corresponding author

Correspondence to Rui Tian .

Editor information

Editors and Affiliations

  1. Southeast University, Nanjing, China

    Jun Zheng

  2. Memorial University of Newfoundland, St. John’s, Canada

    Cheng Li

  3. Auckland University of Technology, Auckland, New Zealand

    Peter Han Joo Chong

  4. Harbin Institute of Technology, Harbin, China

    Weixiao Meng

  5. Southeast University, Nanjing, China

    Feng Yan

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Ai, M., Tian, R. (2019). Rail Vehicle Fire Warning System Based on Gas Vapor Sensor Network. In: Zheng, J., Li, C., Chong, P., Meng, W., Yan, F. (eds) Ad Hoc Networks. ADHOCNETS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 306. Springer, Cham. https://doi.org/10.1007/978-3-030-37262-0_25

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  • DOI: https://doi.org/10.1007/978-3-030-37262-0_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37261-3

  • Online ISBN: 978-3-030-37262-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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