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作者:

Ai, Min (Ai, Min.) | Tian, Rui (Tian, Rui.)

收录:

CPCI-S EI

摘要:

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.

关键词:

Outlier detection Fire alarming Sensor network Gas vapor

作者机构:

  • [ 1 ] [Ai, Min]China Railway Signal & Commun Shanghai Engn Bur G, Shanghai 200436, Peoples R China
  • [ 2 ] [Tian, Rui]Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Informat Dept, Beijing 100124, Peoples R China

通讯作者信息:

  • [Tian, Rui]Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Informat Dept, Beijing 100124, Peoples R China

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来源 :

AD HOC NETWORKS, ADHOCNETS 2019

ISSN: 1867-8211

年份: 2019

卷: 306

页码: 302-313

语种: 英文

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WoS核心集被引频次: 0

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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