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Hardware Acceleration of Kalman Filter for Leak Detection in Water Pipeline Systems using Wireless Sensor Network

机译:无线传感器网络的输水管道泄漏检测卡尔曼滤波器的硬件加速

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The world migration towards automatic and wire-less systems results an increased usage of Wireless Sensor Networks (WSNs). The noticeable popularity of WSNs has imposed enlarged computational in-node demands. Hence, the recourse to fully-integrated and sophisticated systems with low power is a challenging task. Since wireless sensor nodes have limited power resources, it is important to find a balance between energy consumption and computational performance. The traditional software optimizations are not usually suited or enough to find this tradeoff. Consequently, the use of codesign methodology and the careful implementation of hardware accelerator with low frequency processors could offer a good compromise between energy consumption and performance. In this paper, we present a SoC WSN node prototype based on Leon 3 processor for leak detection in water pipeline using Kalman Filter (KF). A hardware acceleration of the KF has been designed and implemented to reduce energy consumption. We have compared also the software implementation of the algorithm and its hardware acceleration in terms of the execution time, the energy consumption and the area requirements. The results show about 97% reduction in energy consumption and execution time without noticeable increased area.
机译:向自动和无线系统的世界迁移导致无线传感器网络(WSN)的使用增加。 WSN的引人注目的流行已经对节点内的计算提出了更高的要求。因此,采用低功耗的完全集成和复杂的系统是一项艰巨的任务。由于无线传感器节点的电源有限,因此重要的是在能耗和计算性能之间找到平衡。传统的软件优化通常不适合或不足以找到这种折衷。因此,使用代码签名方法以及在低频处理器上精心实施硬件加速器可以在能耗和性能之间取得很好的折衷。在本文中,我们提出了一种基于Leon 3处理器的SoC WSN节点原型,用于使用卡尔曼滤波器(KF)进行水管道泄漏检测。已设计并实现了KF的硬件加速功能,以减少能耗。我们还从执行时间,能耗和面积要求方面比较了该算法的软件实现及其硬件加速。结果表明,能耗和执行时间减少了约97%,而面积却没有明显增加。

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