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Author:

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

Indexed by:

EI

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

Keyword:

Accidents Sensor networks Data handling Rail motor cars Ad hoc networks Fires Anomaly detection Vehicles Population statistics Fireproofing

Author Community:

  • [ 1 ] [Ai, Min]China Railway Signal & Communication Shanghai Engineering Bureau Group Co., Ltd., Shanghai; 200436, China
  • [ 2 ] [Tian, Rui]Beijing Engineering Research Center for IoT Software and Systems, Information Department, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • [tian, rui]beijing engineering research center for iot software and systems, information department, beijing university of technology, beijing; 100124, china

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Source :

ISSN: 1867-8211

Year: 2019

Volume: 306 LNICST

Page: 302-313

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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