For　the　activity　recognition　of　operators　in　low-voltage　distribution　rooms,　a　human　activity　recognition　system　based　on　the　bidirectional　gated　recurrent　unit　model　(BiGRU)　is　proposed　to　realize　the　skeleton　information　acquisition　by　the　WiFi　Channel　State　Information　(CSI)　sensor.　The　CSI　sensor　is　used　to　collect　the　activity　data　and　the　Kinect　v2　camera　is　used　to　capture　the　skeleton　of　the　human　body　as　annotations　of　the　CSI　data.　The　BiGRU　model　is　employed　to　effectively　extract　the　characteristics　of　the　data.　Aiming　at　the　problem　of　poor　remote　communication,　the　MQTT　connection　can　be　established　by　using　Message　Queuing　Telemetry　Transport　(MQTT)　protocol　combined　with　ESP8266　WiFi　serial　port　communication　module　is　proposed　to　improve　the　poor　communication　situation　and　carry　out　better　data　communication.　The　system　achieves　remote　intelligent　monitoring　of　the　activities　of　the　operator　in　the　low-voltage　distribution　room.　　©　Published　under　licence　by　IOP　Publishing　Ltd.