The　Internet　of　Things　(IoT)　is　one　of　the　key　components　of　metro　train　safety　as　an　emerging　development　approach　due　to　its　great　potential　to　advance　environmental　sustainability.　A　bogie　is　a　key　component　for　carrying　a　passenger＇s　vehicle　body.　Its　damage　and　defects　can　destroy　fluent　operations　and　better　service　for　train　operation.　The　critical　problem　of　traditional　non-destructive　examination　for　bogie　is　the　high　cost　of　labour　and　environment.　Because　they　are　in　effect　only　after　the　whole　vehicle　has　to　be　split　into　many　sub-components　and　paint　removed.　This　study　provides　an　IoT　approach　and　practice　for　bogie　crack　identification　of　bogie.　The　presented　method　can　achieve　simple　and　efficient　detection　of　damage　with　cheap　PZT　sensor　network.　Its　advantages　is　that　non-split　work　and　non-removal　paint　pollution.　Compared　with　traditional　detection　methods,　this　method　is　more　sensitive　to　a　small　area　of　internal　damage　and　can　identify　the　level　of　damage　and　location　of　the　bogie　plate　frame　even　with　the　dirty　and　non-smooth　surface.