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Computer Science > Other Computer Science

arXiv:2411.10466 (cs)
[Submitted on 4 Nov 2024]

Title:IUMENTA: A generic framework for animal digital twins within
the Open Digital Twin Platform

Authors:Ali Youssef, Kristina Vodorezova, Yannick Aarts, Wisdom E. K.
Agbeti, Arjan P. Palstra, Edwin Foekema, Leonel Aguilar, Ricardo da
Silva Torres, Jascha Grubel
View a PDF of the paper titled IUMENTA: A generic framework for
animal digital twins within the Open Digital Twin Platform, by Ali
Youssef and 8 other authors
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    Abstract:IUMENTA (Latin for livestock) is an innovative software
    framework designed to construct and simulate digital twins of
    animals. By leveraging the powerful capability of the Open
    Digital Twin Platform (ODTP) alongside advanced software sensors,
    IUMENTA offers researchers a user-friendly tool to seamlessly
    develop adaptive digital replicas of animal-based processes. This
    framework establishes a dynamic ecosystem that integrates
    insights from diverse experiments, consequently enhancing our
    understanding of animal behavioural and physiological responses.
    Through real-time tracking of an animal's energy balance. IUMENTA
    provides valuable insights into metabolic rates, nutritional
    needs, emotional states, and overall well-being of animals. In
    this article, we explore the application of the IUMENTA framework
    in developing a digital twin focused on the animal's energy
    balance. IUMENTA includes the EnergyTag system, a
    state-of-the-art wearable software sensor, which facilitates
    real-time monitoring of energy expenditure, allowing for
    continuous updates and personalisation of the energy balance
    digital twin.

Comments: 9 pages, 7 figures, Submitted to PerCom 2025
Subjects: Other Computer Science (cs.OH)
Cite as:  arXiv:2411.10466 [cs.OH]
          (or arXiv:2411.10466v1 [cs.OH] for this version)
          https://doi.org/10.48550/arXiv.2411.10466
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Jascha Grubel [view email]
[v1] Mon, 4 Nov 2024 12:16:33 UTC (2,873 KB)
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