With　the　development　of　the　next　generation　of　information　technology,　an　increasing　amount　of　attention　is　being　paid　to　smart　residential　spaces,　including　smart　cities,　smart　buildings,　and　smart　homes.　Building　indoor　safety　intelligence　is　an　important　research　topic.　However,　current　indoor　safety　management　methods　cannot　comprehensively　analyse　safety　data,　owing　to　a　poor　combination　of　safety　management　and　building　information.　Additionally,　the　judgement　of　danger　depends　significantly　on　the　experience　of　the　safety　management　staff.　In　this　study,　digital　twins　(DTs)　are　introduced　to　building　indoor　safety　management.　A　framework　for　an　indoor　safety　management　system　based　on　DT　is　proposed　which　exploits　the　Internet　of　Things　(IoT),　building　information　modelling　(BIM),　the　Internet,　and　support　vector　machines　(SVMs)　to　improve　the　level　of　intelligence　for　building　indoor　safety　management.　A　DT　model　(DTM)　is　developed　using　BIM　integrated　with　operation　information　collected　by　IoT　sensors.　The　trained　SVM　model　is　used　to　automatically　obtain　the　types　and　levels　of　danger　by　processing　the　data　in　the　DTM.　The　Internet　is　a　medium　for　interactions　between　people　and　systems.　A　building　in　the　bobsleigh　and　sled　stadium　for　the　Beijing　Winter　Olympics　is　considered　as　an　example;　the　proposed　system　realises　the　functions　of　the　scene　display　of　the　operation　status,　danger　warning　and　positioning,　danger　classification　and　level　assessment,　and　danger　handling　suggestions.