Objective:To design a remote monitoring and early warning system of ventilators,so as to adapt to data collection for different types of ventilators,and achieve early warning for abnormal status in operation data of ventilators.Methods:A three-layer structure,which used information gateway of Internet of Things(IoTs)with multi communication standard as the core,and integrated with multiple interfaces,was adopted to construct a remote monitoring and early warning system of ventilators.Boolean function was used to determine strings of incorrect data,and extract respiratory information.Using incremental isolated forest algorithm processed ventilators'operation data for realizing anomaly detection.And then,the detection results were presented through a display module,so as to conduct early warning for existing abnormal situations.Results:The remote monitoring and early warning system of ventilator had an accuracy rate of monitoring over 98.0%for abnormity of different types of ventilators,which timely warning rate was over 98.5%.Conclusion:The designed remote monitoring and early warning system of ventilator can provide clear results of remote monitoring and early warning of ventilator,which can timely find abnormal status,and effectively improve management efficiency for ventilator,and promote the intelligent development of medical treatment.

Objective:To design a remote monitoring and early warning system of ventilators,so as to adapt to data collection for different types of ventilators,and achieve early warning for abnormal status in operation data of ventilators.Methods:A three-layer structure,which used information gateway of Internet of Things(IoTs)with multi communication standard as the core,and integrated with multiple interfaces,was adopted to construct a remote monitoring and early warning system of ventilators.Boolean function was used to determine strings of incorrect data,and extract respiratory information.Using incremental isolated forest algorithm processed ventilators'operation data for realizing anomaly detection.And then,the detection results were presented through a display module,so as to conduct early warning for existing abnormal situations.Results:The remote monitoring and early warning system of ventilator had an accuracy rate of monitoring over 98.0%for abnormity of different types of ventilators,which timely warning rate was over 98.5%.Conclusion:The designed remote monitoring and early warning system of ventilator can provide clear results of remote monitoring and early warning of ventilator,which can timely find abnormal status,and effectively improve management efficiency for ventilator,and promote the intelligent development of medical treatment.