ASAS-NANP SYMPOSIUM: MATHEMATICAL MODELING IN ANIMAL NUTRITION: Harnessing Real-Time Data and Digital Twins for Precision Livestock Farming.

Journal: Journal of animal science
Published Date:

Abstract

The increasing population and urbanization have intensified livestock production, raising concerns about sustainability, animal welfare, and disease transmission. There is a need to improve the sustainability of animal production. Precision Livestock Farming (PLF) emerges as a promising solution, utilizing sensors, Internet of Things (IoT), and data analytics to enhance animal management. Digital twins create virtual replicas of physical entities such as animals, buildings, and overall farm operations. This paper highlights the transformative potential of PLF and digital twin technology. The integration of real-time data with digital twins represents a frontier of technological innovation with the potential to transform PLF. The future of PLF looks promising with advancements in artificial intelligence (AI), machine learning (ML), blockchain, and augmented reality, which are expected to drive further innovations and enhance the capabilities of digital twins. In this review, we provide a brief overview of the current state-of-the-art developments in the field of precision livestock agriculture and highlight the potential for digital twin technologies to transform the agricultural sector.

Authors

  • Tami M Brown-Brandl
    Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska 68583, USA.
  • Jian Tao
    Visual Computing & Computational Media, College of Performance, Visualization & Fine Arts, Texas A&M University, College Station, Texas.

Keywords

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