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数据融合是传感器网络的研究热点,传感器节点具有规模大、计算能力有限等特点,导致数据之间的冗余十分严重,为了减少数据传输量、有效降低减少数据的传输时延,提出一种基于模糊理论的无线传感器数据融合算法,首先对传感器节点采集数据特点进行分析,并指出了传统数据融合算法的优缺点,然后基于贴近度对传感器数据进行初步融合,删除其中的错误以及无用数据,最后采用模糊推理对初步融合的数据进行再次融合,得到传感器数据融合的最终结果,实验结果表明,本文算法融合后的数据可以准确描述监测对象的状态信息,加快了数据传输速度,提高了了数据的融合比,而且融合结果要优于当前无线传感器数据融合算法。
Data fusion is a hot research topic in sensor networks. Sensor nodes have the characteristics of large scale and limited computing power. As a result, data redundancy is very serious. In order to reduce the amount of data transmission and reduce the data transmission delay effectively, Fuzzy theory of wireless sensor data fusion algorithm, the characteristics of the sensor data collected at the first analysis, and pointed out the advantages and disadvantages of the traditional data fusion algorithm, and then based on close proximity of the sensor data fusion, delete the errors and useless data, and finally The results show that the fused data in this paper can accurately describe the state information of the monitoring object, speed up the data transmission speed and improve the quality of the data Fusion ratio, and the fusion result is superior to the current wireless sensor data fusion algorithm.