scholarly journals IHPG Algorithm for Efficient Information Fusion in Multi-Sensor Network via Smoothing Parameter Optimization

Informatica ◽  
2013 ◽  
Vol 24 (2) ◽  
pp. 291-313 ◽  
Author(s):  
Wen-Tsai Sung ◽  
Ching-Li Hsiao
Keyword(s):  
Sensor Network ◽  
Parameter Optimization ◽  
Information Fusion ◽  
Smoothing Parameter ◽  
Efficient Information

Resource-Constrained Wireless Sensor Network Information Decision Fusion in Ocean Environment

2013 ◽  
Vol 433-435 ◽  
pp. 229-232
Author(s):  
Xiao Guang Yuan ◽  
Dong Zhu Feng ◽  
Jian Deng ◽  
Yuan Jie Bai
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Likelihood Ratio ◽  
Information Fusion ◽  
Fusion Rule ◽  
Wireless Sensor ◽  
Resource Constrained ◽  
Fusion Rules ◽  
Ocean Environment

In order to solve the decision information fusion issues of resource-constrained wireless sensor network, several decision information fusion rules under exponential distribution fading channel are investigated in this paper. At first, optimal likelihood ratio rule is given. The detection performance of this fusion rule is best, however, this rule acquires channel information which is too costly for resource constrained sensor networks. To solve this problem, suboptimal likelihood ratio fusion rule is proposed which requires only the knowledge of channel statistics. In addition, the reduced forms of the suboptimal are also derived, in the case of extreme channel signal-to-noise ratio (SNR). Theoretical analysis and simulations show that suboptimal fusion rule needs much less computation and information, yet exhibits only slight performance degradation. Suboptimal fusion rules are practicable for resource constrained wireless sensor networks decision information fusion system working in ocean environment.

scholarly journals An Algorithm of Wireless Sensor Monitoring System

2018 ◽  
Vol 14 (01) ◽  
pp. 52
Author(s):  
Li Hongri
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Monitoring System ◽  
Information Fusion ◽  
Design Method ◽  
Storage System ◽  
Wireless Sensor ◽  
Fusion Method ◽  
Fusion Model ◽  
Accurate Identification

In order to realize more intelligent storage monitoring system, the information fusion model of wireless sensor network for storage environment monitoring is studied on the basis of analyzing information fusion technology. By analyzing the structure of storage monitoring system based on wireless sensor network, a two-layer information fusion method is established. The information fusion of homogeneous sensor based on adaptive weighting and the fusion method of heterogeneous sensor based on radial basis function neural network are designed and verified. The experimental results show that the design method can fuse the storage environment information and realize the accurate identification of the environmental state. Therefore, the algorithm can effectively improve the speed of network training, and the classification effect is good. To a certain extent, it can help enterprises to establish a safe and efficient storage system, to enhance the efficiency of enterprise warehousing operations.

Analysis and Design of Simulation System for Passive Acoustic Senor Network

2014 ◽  
Vol 533 ◽  
pp. 214-217
Author(s):  
Jun Hua Li ◽  
Hong Wei Quan ◽  
Xiu Yin Xue
Keyword(s):  
Sensor Network ◽  
Information Fusion ◽  
Measurement Model ◽  
Simulation System ◽  
System Structure ◽  
Main Function ◽  
Acoustic Sensor ◽  
Fusion System ◽  
Analysis And Design ◽  
Passive Acoustic

The simulation system for passive acoustic sensor network is an important part of information fusion system. Its main function is to simulate the detection process of acoustic sensor network and produce the simulation data which is needed for testing and evaluating the target tracking algorithms. For implementation of simulation system, the target motion model and the measurement model of passive acoustic sensor must be built, and a scenario will be defined in advance when it is running. This paper discussed the passive acoustic sensor network model and gave an information fusion system structure for passive acoustic sensor network. Then the basic principle of target detection for acoustic sensor is stated. Finally, we illustrated the operation process of a simulation system for passive acoustic sensor network.

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