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Digital Farming: A Survey on IoT-based Cattle Monitoring Systems and Dashboards

Author

Listed:
  • El Moutaouakil, Khalid
  • Jdi, Hamza
  • Jabir, Brahim
  • Falih, Noureddine

Abstract

There is a steady increase in research on livestock monitoring systems that offer new ways to remotely track the health of the livestock, early predict the diseases that may affect them and intervene in the early stages to save the situation by monitoring the various vital biodata of the livestock, as well as monitoring their feeding and tracking their location to prevent any damage or rustling. In this context, this paper comes in order to highlight and discuss the most recently published articles that study the topic of cattle health monitoring and location tracking systems using advanced IoT sensors. In addition, the research provides a review of the most important software and dashboards available in the market that can be used for this purpose. The research constitutes a reference for researchers in this field and for those who wish to develop similar monitoring systems.

Suggested Citation

  • El Moutaouakil, Khalid & Jdi, Hamza & Jabir, Brahim & Falih, Noureddine, 2023. "Digital Farming: A Survey on IoT-based Cattle Monitoring Systems and Dashboards," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 15(2), June.
    • Handle: RePEc:ags:aolpei:337998
    DOI: 10.22004/ag.econ.337998
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    References listed on IDEAS

    as
    1. Jabir, Brahim & Falih, Noureddine & Sarih, Asmaa & Tannouche, Adil, 2021. "A Strategic Analytics Using Convolutional Neural Networks for Weed Identification in Sugar Beet Fields," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 13(1), March.
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