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

Abstract

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.