Abstract

Wireless sensor network (WSN) has been paid more attention by scholars due to the practical communication of a system of devices to transfer information gathered from a monitored field through wireless links. Precise and accurate data of aggregating messages from sensor nodes is a vital demand for a success WSN application. This paper proposes a new scheme of identifying the correctness data scheme for aggregating data in cluster heads in hierarchical WSN based on naive Bayes classification. The collecting environmental information includes temperature, humidity, sound, and pollution levels, from sensor nodes to cluster heads that classify data fault and aggregate and transfer them to the base station. The collecting data is classified based on the classifier to aggregate in the cluster head of WSN. Compared with some existing methods, the proposed method offers an effective way of forwarding the correct data in WSN applications.

中文翻译：

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基于朴素贝叶斯分类的无线传感器网络簇头中聚合数据的正确性数据识别方案

摘要

由于设备系统的实际通信可以通过无线链路传输从受监视领域收集的信息，因此无线传感器网络（WSN）已引起学者的更多关注。来自传感器节点的聚合消息的准确而准确的数据是成功实现WSN应用的重要要求。提出了一种基于朴素贝叶斯分类的，用于识别WSN中的簇头数据的正确性数据方案。收集的环境信息包括温度，湿度，声音和污染水平，从传感器节点到簇头，这些簇头对数据故障进行分类并将它们汇总并传输到基站。基于分类器对收集的数据进行分类，以汇总到WSN的簇头中。与一些现有方法相比，