In　practical　building　control,　quickly　obtaining　detailed　indoor　temperature　distribution　is　necessary　for　providing　satisfying　personal　comfort　and　improving　building　energy　efficiency.　The　aim　of　this　study　is　to　propose　a　fast　prediction　method　for　indoor　temperature　distribution　without　knowing　the　thermal　boundary　conditions　in　practical　applications.　In　this　method,　the　index　of　contribution　ratio　of　indoor　climate　(CRI),　which　represents　the　independent　contribution　of　each　heat　source　to　the　temperature　distribution,　has　been　combined　with　the　air　temperature　collected　by　one　mobile　sensor　at　the　height　of　the　working　area.　Based　on　a　typical　office　model,　the　effectiveness　of　using　mobile　sensors　was　discussed,　and　the　influence　of　its　acquisition　height　and　acquisition　distance　on　the　prediction　accuracy　was　analyzed　as　well.　The　results　showed　that　the　proposed　prediction　method　was　effective.　When　the　sensors　fixed　on　the　wall　were　used　to　predict　the　indoor　temperature　distribution,　the　maximum　average　relative　error　was　27.7%,　whereas　when　the　mobile　sensor　was　used　to　replace　the　fixed　sensors,　the　maximum　average　relative　error　was　4.8%.　This　indicates　that　using　mobile　sensors　with　flexible　acquisition　location　can　help　promote　both　reliability　and　accuracy　of　temperature　prediction.　In　the　human　activity　area,　data　from　a　set　of　mobile　sensors　were　used　to　predict　the　temperature　distribution　at　four　heights.　The　prediction　accuracy　was　2.1%,　2.1%,　2.3%,　and　2.7%,　respectively.　However,　the　influence　of　acquisition　distance　of　mobile　sensors　on　prediction　accuracy　cannot　be　ignored.　The　distance　should　be　large　enough　to　disperse　the　distribution　of　the　acquisition　points.　Due　to　the　influence　of　airflow,　some　distance　between　the　acquisition　points　and　the　room　boundaries　should　be　given.