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Data fusion models in WSNs: Comparison and analysis

机译:WSN中的数据融合模型:比较和分析

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摘要

In WSNs, hundreds of sensors collect data from the environment but these sensors have limited energy. Therefore, energy consumption is a very challenging issue in the design of WSNs. Sometimes, sensors fail as they got affected by the pressure or temperature. Such failure can lead to misleading measurements which in turn are waste of energy. As a result, data fusion is needed to overcome such confusion where it assures data's efficiency and eliminates data's redundancy. This paper provides an analysis of the state-of-the-art data fusion models along with their architectures. It also presents a comparison between these models to highlight the main objectives of each. In addition, it analyzes the advantages and the limitation of these models.
机译:在无线传感器网络中,数百个传感器从环境中收集数据,但是这些传感器的能量有限。因此,在无线传感器网络的设计中,能耗是一个非常具有挑战性的问题。有时,传感器由于受到压力或温度的影响而发生故障。这种故障可能导致误导的测量,进而浪费能量。结果,需要数据融合来克服这种混淆,在这种混淆下,它可以确保数据的效率并消除数据的冗余。本文提供了对最新数据融合模型及其体系结构的分析。它还对这些模型进行了比较,以突出每个模型的主要目标。此外,它分析了这些模型的优点和局限性。

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