Home // SENSORCOMM 2019, The Thirteenth International Conference on Sensor Technologies and Applications // View article
Authors:
Valery Nkemeni
Fabien Mieyeville
Jacques Verdier
Pierre Tsafack
Keywords: distributed computing; wireless sensor networks; distributed Kalman filter; water pipeline monitoring; non-intrusive sensors
Abstract:
Wireless Sensor Networks (WSN) have found a wide range of applications in monitoring, with most deployments done in a centralized fashion. This results in high energy consumption and latency, as such centralized schemes are characterized by periodic long-distance transmissions. In this work, we demonstrate the benefits of trading off transmission for computation. We propose a solution where local and distributed computing are used to improve the accuracy of anomaly detection in physical systems without the need for long distance transmissions to some central base station. We practically demonstrate this in detecting leaks on a water pipeline testbed, since water losses via leaks is a major problem in most developing countries, including Cameroon. Unlike other works for leak detection in water pipelines available in literature, we build a low-cost sensor node, which is feasible for deployment in developing countries from cheap of-the-shelf commercial elements. The accuracy of the measured vibrations on the surface of pipes is improved using a distributed Kalman filter, where every node independently computes the optimal state estimate used for leak detection by running a local Kalman filter to obtain an accurate local estimate from local measurements and also fusing it with those of its close neighbors. Results show that the distributed Kalman filter improves the reliability of leak detection.
Pages: 13 to 20
Copyright: Copyright (c) IARIA, 2019
Publication date: October 27, 2019
Published in: conference
ISSN: 2308-4405
ISBN: 978-1-61208-744-3
Location: Nice, France
Dates: from October 27, 2019 to October 31, 2019