Journal of Shanghai Jiao Tong University (Science) ›› 2018, Vol. 23 ›› Issue (4): 577-.doi: 10.1007/s12204-018-1959-0

• • 上一篇    下一篇

An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

LI Shuoming (李硕明), CHEN Lei (陈磊), CHEN Shihong (陈世鸿)   

  1. (a. National Engineering Research Center for Multimedia Software; b. School of Computer Science, Wuhan University, Wuhan 430072, China)
  • 发布日期:2018-08-02
  • 通讯作者: CHEN Shihong (陈世鸿) E-mail:53131128@qq.com

An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

LI Shuoming (李硕明), CHEN Lei (陈磊), CHEN Shihong (陈世鸿)   

  1. (a. National Engineering Research Center for Multimedia Software; b. School of Computer Science, Wuhan University, Wuhan 430072, China)
  • Published:2018-08-02
  • Contact: CHEN Shihong (陈世鸿) E-mail:53131128@qq.com

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.

关键词: sensor and sensor network (SSN), data fusion, intelligent irrigation, environment monitoring

Abstract: 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.

Key words: sensor and sensor network (SSN), data fusion, intelligent irrigation, environment monitoring

中图分类号: