Designing sensor networks for leak detection in water pipeline systems

Rachel Cardell-Oliver, Verity Scott, Thomas Chapman, J. Morgan, A. Simpson

    Research output: Chapter in Book/Conference paperConference paperpeer-review

    7 Citations (Scopus)

    Abstract

    © 2015 IEEE. Undetected leaks in water distribution networks are a significant problem both economically and environmentally. Across Australia 12% of water is estimated to be lost through leaks and the annual cost to water utilities worldwide is US14 billion. A sensor network that measures water flow in the pipes can be used to predict the location and size of leaks. Recent advances in sensor technology and lower costs mean that large scale sensor networks may soon be an economic choice for solving the leak detection problem. This paper presents a sensor network design method that generates human-readable rules for leak detection. Additionally, for a given network and range of operating scenarios, it discovers the best locations for flow sensors. The method is demonstrated to make acceptably accurate predictions under real-world conditions of uncertain measurements. It also allows trade-offs to be made between minimising the costs of installing and maintaining sensors and maximising prediction accuracy. For example, in some cases sufficiently accurate predictions can be made using sensors on only half the pipes.
    Original languageEnglish
    Title of host publication2015 IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015
    Place of PublicationUnited States
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1-6
    ISBN (Electronic)9781479980543
    ISBN (Print)9781479980550
    DOIs
    Publication statusPublished - 2015
    Event10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015 - Singapore, Singapore
    Duration: 7 Apr 20159 Apr 2015

    Conference

    Conference10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2015
    Country/TerritorySingapore
    CitySingapore
    Period7/04/159/04/15

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