Context-Awareness and Learning Fusion Method of Fluid Property Sensor Networks Based on Fuzzy Entropy

Fluid sensor network is very difficult to make context-awareness and learning fusion because there is a variety of complex dynamic uncertainties involved ranging from information redundancy, information complementary, to information instability. This paper introduces a fuzzy entropy method into context-awareness and learning fusion method of fluid property sensor networks. First, the architecture of fluid property sensor network is analyzed, and based on it the context characteristics are described. Second, by the introduction of fuzzy entropy, the learning fusion method of fluid property sensor networks is proposed, where the fusion hierarchy of context information is discussed and the fusion algorithm is also illustrated. Third, an example is presented for verification of the proposed model, where the multiple sensor information fusion based on fuzzy logic analysis method can effectively tackle uncertain information. At last, some interesting conclusions are carried out and future researching directions are also indicated at the end of the paper.