摘要
In order to realize high precision of environment parameters detection in irrigation applications,a sensor and sensor network(SSN) ontology based data fusion method is proposed.An SSN sub-ontology for soilstate monitoring is revised,which includes the sensing devices hierarchies and measurement properties selection according to the detection feature interests.As for sensor data processing,a tuning data method by data pool filtering and clustering is adopted,as well as a useful data fusion method for multi-sensor system.The testing results show that both the accuracy and efficiency of the proposed method are higher after related filtering and clustering process,which enables a thorough monitoring for intelligent irrigation systems and can be extended into environment monitoring and control applications.
In order to realize high precision of environment parameters detection in irrigation applications, a sensor and sensor network （SSN） ontology based data fusion method is proposed. An SSN sub-ontology for soil- state monitoring is revised, which includes the sensing devices hierarchies and measurement properties selection according to the detection feature interests. As for sensor data processing, a tuning data method by data pool filtering and clustering is adopted, as well as a useful data fusion method for multi-sensor system. The testing results show that both the accuracy and efficiency of the proposed method are higher after related filtering and clustering process, which enables a thorough monitoring for intelligent irrigation systems and can be extended into environment monitoring and control applications.
作者
LI Shuoming
CHEN Lei
CHEN Shihong
李硕明;陈磊;陈世鸿(National Engineering Research Center for Multimedia Software,Wuhan University;School of Computer Science,Wuhan University)
基金
the National Natural Science Foundation of China(No.61100133)
the Science Guidance Project of Education Department of Hubei Province(No.B20101104)
