A Distributed Computing Solution Based on Distributed Kalman Filter for Leak Detection in WSN-Based Water Pipeline Monitoring.

Valery Nkemeni,Fabien Mieyeville,Pierre Tsafack

doi:10.3390/s20185204

Abstract

Wireless Sensor Network (WSN) applications that favor more local computations and less communication can contribute to solving the problem of high power consumption and performance issues plaguing most centralized WSN applications. In this study, we present a fully distributed solution, where leaks are detected in a water distribution network via only local collaborations between a sensor node and its close neighbors, without the need for long-distance transmissions via several hops to a centralized fusion center. A complete approach that includes the design, simulation, and physical measurements, showing how distributed computing implemented via a distributed Kalman filter improves the accuracy of leak detection and the power consumption is presented. The results from the physical implementation show that distributed data fusion increases the accuracy of leak detection while preserving WSN lifetime.

Highlights

A Wireless Sensor Network (WSN) consists of several embedded nodes with sensing, processing and wireless communications capabilities, distributed over an area of interest to monitor physical or environmental conditions [1]
The fusion center used in decentralized systems is a local aggregation unit present in the field and may have a direct communication with the base station, which collects data from the sensor nodes within a cluster and locally processes them [32,37,41,75]
WSN-based Water Pipeline Monitoring (WWPM) systems are practically developed from two main parts: the sensors/equipment installed along the pipeline that periodically collect useful information relating to some pipeline parameters and the algorithms that process this information in order to detect and localize leaks in the pipeline [26]

Summary

Introduction

A Wireless Sensor Network (WSN) consists of several embedded nodes with sensing, processing and wireless communications capabilities, distributed over an area of interest to monitor physical or environmental conditions [1]. They are spatially distributed systems that exploit wireless communication as the means of communication between nodes and are typically constrained in terms of energy, computing power, memory and communication bandwidth due to their requirements of a small size and low power consumption [2]. The issue of reliably identifying a leak signal in the midst of errors from a number of sources (commonly called noise) is a fundamental challenge of any leak detection system [33,76]

Objectives

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Conclusion