基于多传感器的温室环境数据融合算法研究

Research on greenhouse environment data fusion algorithm based on multi-sensor

无线传感器网络中采集的数据存在着较大的冗余与误差,影响数据的可靠性;而在温室环境监测中,对数据的准确性要求比较高。因此,为了提高多传感器采集数据的准确性,在研究了现有的几种数据融合算法以后,提出一种基于多传感器的综合数据融合算法。给出了采用格罗布斯准则消除粗大误差,并引入哈夫曼树的思想对数据进行项融合的方法。结果表明,该算法可以有效提高测量数据的准确性。

There are many redundances and errors in the data collected from wireless sensor networks, which influences the reliability of data. The greenhouse environment monitoring requires high accuracy of data, Therefore, in order to improve the accuracy of data collected by multiple sensors, a comprehensive data fusion algorithm based on multi-sensor is presented through the study of some existing data fusion algorithms. Grubbs criterion is uesd to eliminate the gross errors, and idea of Hoffmann tree is introduced for data fusion. The results show that the algorithm is effective to improve the accuracy of the measured data.