According　to　the　American　Academy　of　Sleep　Medicine　(AASM),　patients　with　apnea　of　10　seconds　or　more,　and　more　than　5　times　per　hour　can　be　diagnosed　with　sleep　disorders.　The　current　gold　standard　for　detecting　this　type　of　people　with　sleep　disorder　is　Polysomnography　(PSG).　But　more　than　80%　Obstructive　Sleep　Apnea(OSA)　patients　of　the　Sleep　Disorder(SD)　have　not　been　detected.　The　reason　is　that　the　current　configuration　of　PSG　is　insufficient　in　more　than　2,500　sleep　labs　in　the　United　States,　and　that　the　lack　of　manpower　of　sleep　professional　technicians　who　analyze　PSG　signal　has　caused　many　OSA　patients　to　be　diagnosed　in　a　timely　and　effective　manner.　It　is　no　effective　measures　to　reduce　the　risk　even　after　OSA　patients　have　been　diagnosed.　Current　medical　treatments　are　either　surgical　or　a　lifelong　Continuous　positive　dual　channel　air　pressure　ventilator(CPAP).　Domestic　research　shows　that　OSA　patients　have　poor　sleep　at　night　and　sleepiness　during　the　day.　It　often　results　in　inefficient　work　and　causes　many　traffic　accidents.　Therefore,　how　to　take　effective　monitoring　measures　for　these　already　diagnosed　OSA　patients　has　become　an　urgent　problem　to　be　solved.　This　paper　extracts　an　interactive　monitoring　system　for　patients　with　OSA　based　on　the　Internet　of　Things(IoT)　framework.　It　can　reduce　the　timely　rescue　of　OSA　patients　when　they　are　in　danger　in　field　operations.　At　the　same　time,　through　the　interactive　function　of　this　indicator　mark,　the　anxiety　during　the　waiting　process　can　be　reduced.　It　is　also　convenient　for　the　peers　to　report　the　progress　of　the　patient　in　time.　The　specific　method　is　to　use　the　existing　IoT　framework.　The　IoT　data　acquisition　layer　uses　wearable　sensors　to　collect　vital　signs　of　patients,　with　emphasis　on　ECG　and　SpO2　signals.　The　network　layer　transmits　the　collected　physiological　signals　to　the　Beidou　indicator　using　the　Bluetooth　Low　Energy　(BLE)　protocol.　The　platform　layer　adopts　the　mature　rescue　interaction　platform　of　Beidou&GPS.　The　previous　GPS　indicator　has　no　short　message　function,　and　the　patient　can　only　passively　wait　for　rescue.　Positional　standard　is　improved　through　Beidou　model,　and　the　short　message　interaction　function　has　been　added.　Then　the　patient　can　report　the　progress　of　the　disease　in　time　while　waiting　for　the　rescue.　After　our　simulation　test,　the　effectiveness　of　the　OSA　patient　rescue　monitoring　system　based　on　the　IoT　framework　has　been　greatly　improved,　especially　in　outdoor　work,　where　the　mobile　phone　signal　coverage　is　relatively　weak.　The　short　message　function　added　by　the　Beidou　indicator　can　be　used　to　provide　timely　progress　of　the　patient＇s　condition,　and　provide　the　medical　rescue　team　with　the　data　support　to　offer　a　more　accurate　rescue　plan.　After　a　comparative　trial,　the　rescue　rate　of　the　OSA　patients　with　the　detection　device　of　this　article　increased　by　10　percentage　points　compared　with　the　rescue　rate　with　only　GPS　satellite　phones.