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Machine learning-assisted self-powered ear tag for animal welfare.

Xiaoyu Su1,2, Peidi Fan1, Ying Liu1

  • 1Laboratory of Agricultural Information Intelligent Sensing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, PR China.

Nature Communications
|June 2, 2026
PubMed
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This summary is machine-generated.

A new self-powered ear tag uses machine learning to continuously monitor animal metabolic health and ion balance in livestock. This technology accurately identifies welfare states, improving precision animal farming.

Area of Science:

  • Animal Science
  • Biomedical Engineering
  • Sensor Technology

Background:

  • Metabolic health is vital for animal welfare, but intensive farming practices often lead to nutritional imbalances and metabolic dysregulation.
  • Identifying metabolically abnormal animals in large-scale production settings is difficult.
  • Continuous, real-time monitoring is needed for effective livestock health management.

Purpose of the Study:

  • To develop a machine learning-assisted, self-powered ear tag for continuous monitoring of ion homeostasis in livestock.
  • To enable large-scale, energy-autonomous deployment for precision livestock health and welfare management.

Main Methods:

  • A hybrid energy harvesting module (triboelectric nanogenerator and solar cell) powers the ear tag for autonomous operation.

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  • A microneedle-based biosensing module performs minimally invasive, time-resolved monitoring of interstitial fluid pH, K+, and Ca2+.
  • A machine learning pipeline decodes multi-ionic marker dynamics to classify animal welfare states.

    • Main Results:

    • The self-powered ear tag achieved over 95% average classification accuracy in distinguishing five distinct welfare-related states.
    • Validation using leave-one-animal-out cross-validation across 5399 sampling windows from three independent animals confirmed robust performance.
    • The system demonstrated energy-autonomous operation through an optimized duty-cycled strategy.

    Conclusions:

    • The developed self-powered ear tag offers a scalable technological solution for next-generation precision livestock health monitoring.
    • This technology bridges energy autonomy with intelligent metabolic profiling, enhancing animal welfare management in intensive farming.
    • Continuous, multi-ionic monitoring provides a powerful tool for early detection of metabolic dysregulation and welfare issues.