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.