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首页> 外文期刊>Journal of ambient intelligence and smart environments >Clustering based fuzzy logic for multimodal sensor networks: A preprocessing to decision fusion
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Clustering based fuzzy logic for multimodal sensor networks: A preprocessing to decision fusion

机译:多模式传感器网络的基于聚类的模糊逻辑:决策融合的预处理

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摘要

The advances of Micro-electromechanical systems (MEMS) technology lead to new types of sensors named "mul-timodal" sensors where multiple features can be sensed and reported by one sensor. Forming a wireless sensor network of such sensors poses new challenges to the wireless sensor networks in addition to the current challenges. Currently, each multimodal sensor reports periodically a message for each feature or a long message that contains all the features compared to the traditional sensors. Such multimodal sensor networks could be used for multiple purposes and serve different applications. However, data handling and information processing as well as data/decision tasks became much harder than before. In this paper, we introduce a set of clustering algorithms taking into consideration the reported multiple features as well as some of the sensors parameters such as nodes' residual energy and clusterheads' degree. The paper utilizes different clustering techniques including fuzzy logic. The proposed algorithms are designed to simplify the next step operation which is data/decision fusion and decision making operations. Through an extensive set of experiments, the proposed algorithms are evaluated.
机译:微机电系统(MEMS)技术的进步导致了一种新型的传感器,称为“多模式”传感器,其中一个传感器可以感知并报告多个特征。由这种传感器构成的无线传感器网络除了当前的挑战之外,还对无线传感器网络提出了新的挑战。当前,与传统传感器相比,每个多模式传感器都会定期报告每个功能的消息或包含所有功能的长消息。这样的多模式传感器网络可以用于多种目的并服务于不同的应用。但是,数据处理和信息处理以及数据/决策任务变得比以前困难得多。在本文中,我们引入了一组聚类算法,其中考虑了报告的多个特征以及一些传感器参数,例如节点的剩余能量和簇头的程度。本文利用了包括模糊逻辑在内的不同聚类技术。提出的算法旨在简化下一步操作,即数据/决策融合和决策操作。通过广泛的实验,对提出的算法进行了评估。

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