IDEAS home Printed from https://ideas.repec.org/a/epw/ejeng0/v8y2023i5id63078.html

A LoRaWAN-based IoT System for Leakage Detection in Pipelines

Author

Listed:
  • Olaide Agbolade

    (Federal University of Technology, Nigeria)

  • Oyindamola Olanrewaju

    (Federal University of Technology, Nigeria)

  • Samson Oyetunji

    (Federal University of Technology, Nigeria)

  • Josiah Babatola

    (Federal University of Technology, Nigeria)

Abstract

Leakages in a pipeline are an important problem due to the potential economic and environmental hazard they present. In this study, we proposed a LoRaWAN-based approach for detecting and localizing leakages in pipelines. Our study includes an experimental setup that simulates a pipeline network with pressure and flow rate sensors attached. The flow rate and pressure data were transmitted through LoRaWAN to a receiver, which in turn uploads the data to a cloud server using a cellular network. The receiver compares the flow rate reading from all the monitoring nodes attached to the pipeline network. If flow rate reading from successive nodes presents a percentage variation of more than 1.5%, a leak is confirmed to have taken place. The flow rate readings can also be used to localize the leak. The resolution of the leak detection is dependent on the number of monitoring nodes on the pipeline network. In our study, the pressure readings were found to be insufficient to provide reliable evidence of leakages. In our specific situation, due to the relatively short length of the experimental pipeline network, a pressure drop of up to 38.2% was recorded between successive nodes with an overall pressure loss of 62%, making pressure data unsuitable for leak detection in the short pipeline network.

Suggested Citation

  • Olaide Agbolade & Oyindamola Olanrewaju & Samson Oyetunji & Josiah Babatola, 2023. "A LoRaWAN-based IoT System for Leakage Detection in Pipelines," European Journal of Engineering and Technology Research, European Open Science, vol. 8(5), pages 36-42, September.
  • Handle: RePEc:epw:ejeng0:v:8:y:2023:i:5:id:63078
    DOI: 10.24018/ejeng.2023.8.5.3078
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejeng/article/view/63078
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejeng/article/download/63078/12956
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejeng.2023.8.5.3078?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejeng0:v:8:y:2023:i:5:id:63078. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejeng .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.