Method of Wireless Sensor Network Data Fusion

Lili Ma, Jiangping Liu, Jidong Luo


In order to better deal with large data information in computer networks, a large data fusion method based on wireless sensor networks is designed. Based on the analysis of the structure and learning algorithm of RBF neural networks, a heterogeneous RBF neural network information fusion algorithm in wireless sensor networks is presented. The effectiveness of information fusion processing methods is tested by RBF information fusion algorithm. The proposed algorithm is applied to heterogeneous information fusion of cluster heads or sink nodes in wireless sensor networks. The simulation results show the effectiveness of the proposed algorithm.  Based on the above finding, it is concluded that the RBF neural network has good real-time performance and small network delay. In addition, this method can reduce the amount of information transmission and the network conflicts and congestion.


wireless sensor networks, information fusion; RBF neural networks; big data

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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