IDEAS home Printed from https://ideas.repec.org/h/spr/prochp/978-3-031-56603-5_21.html
   My bibliography  Save this book chapter

An Expert System Model for Animal Welfare for Bovine Cattle Dehydration Risk Detection Using Precision Livestock Farming

In: Smart and Secure Embedded and Mobile Systems

Author

Listed:
  • Silvia Molina

    (University, National of San Luis
    University National of La Plata)

  • Emilio Luque

    (University, Autonoma of Barcelona)

  • Dolores Rexachs

    (University, Autonoma of Barcelona)

Abstract

The preservation of Animal Welfare improves bovine production, in particular, the detection of animal’s dehydration risk is fundamental, it avoids in extreme cases loss of these. This article presents a model of rule-based expert system to detect the bovine’s dehydration risk in cattle farm with extensive production systems. This system is based on Internet of Things (IoT) dispositives sensor measurements, these devices are part of the Precision Livestock Farming and they are in the animal’s environment inclusive put on/in them and information from monitoring ecosystems available in the cloud.

Suggested Citation

  • Silvia Molina & Emilio Luque & Dolores Rexachs, 2024. "An Expert System Model for Animal Welfare for Bovine Cattle Dehydration Risk Detection Using Precision Livestock Farming," Progress in IS, in: Jorge Marx Gómez & Anael Elikana Sam & Devotha Godfrey Nyambo (ed.), Smart and Secure Embedded and Mobile Systems, pages 241-250, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-56603-5_21
    DOI: 10.1007/978-3-031-56603-5_21
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:prochp:978-3-031-56603-5_21. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.