463 Cyber-Physical Systems with robots and AI for precision dairy farming

Abstract The emergence of precision livestock farming (PLF) offers a transformative lens through which to prioritize animal welfare. At the heart of this transformation lies the rumen, a complex microbial ecosystem within dairy cows responsible for converting feed into nutrients and impacting cow health, productivity, and environmental footprint. Despite its pivotal role, our understanding of the inner workings of the rumen remains limited due to a lack of real-time monitoring tools. My research leverages AI and robotics in PLF to address this gap, focusing on developing a closed-loop system for continuous, in-vivo rumen monitoring. This system employs cyber-physical systems (CPS) embedded with modular sensors and adaptive algorithms. These sensor modules, powered by AI-based data tracking, autonomously monitor rumen temperature, humidity, pressure, and methane concentration, enabling early detection of imbalances and prompt interventions to maintain optimal rumen health. A key innovation is the self-powered in-vivo robot capable of traversing the rumen’s stratified layers. Guided by AI-powered localization, this robot unlocks unparalleled access to new data, aiding in identifying specific regions associated with conditions like subacute ruminal acidosis (SARA) and methane production. This non-invasive approach eliminates the need for traditional cannulation, minimizing stress on the animal and opening new avenues for animal scientists. The impact of this research extends beyond individual cow health. By optimizing rumen function, we can improve feed efficiency, reduce methane emissions, and promote overall sustainability in dairy farming. Additionally, real-time data insights pave the way for precision nutrition, tailored interventions, and improved disease prevention, directly enhancing animal welfare. This novel approach to rumen monitoring represents a significant step towards realizing the full potential of PLF. By integrating AI and robotics, we can usher in a future where animal welfare and environmental sustainability go hand-in-hand, ultimately contributing to a more responsible and ethical dairy industry.

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Institutions

Publication Details

Journal
Journal of Animal Science
Published
2024-09-01
DOI
https://doi.org/10.1093/jas/skae234.340
Citations
5
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
1.74
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article

463 Cyber-Physical Systems with robots and AI for precision dairy farming

Upinder Kaur
5 citations
Journal of Animal Science
Food Supply Chain Traceability
1.74
article

463 Cyber-Physical Systems with robots and AI for precision dairy farming

Upinder Kaur
article en
5 citations

Abstract

Abstract The emergence of precision livestock farming (PLF) offers a transformative lens through which to prioritize animal welfare. At the heart of this transformation lies the rumen, a complex microbial ecosystem within dairy cows responsible for converting feed into nutrients and impacting cow health, productivity, and environmental footprint. Despite its pivotal role, our understanding of the inner workings of the rumen remains limited due to a lack of real-time monitoring tools. My research leverages AI and robotics in PLF to address this gap, focusing on developing a closed-loop system for continuous, in-vivo rumen monitoring. This system employs cyber-physical systems (CPS) embedded with modular sensors and adaptive algorithms. These sensor modules, powered by AI-based data tracking, autonomously monitor rumen temperature, humidity, pressure, and methane concentration, enabling early detection of imbalances and prompt interventions to maintain optimal rumen health. A key innovation is the self-powered in-vivo robot capable of traversing the rumen’s stratified layers. Guided by AI-powered localization, this robot unlocks unparalleled access to new data, aiding in identifying specific regions associated with conditions like subacute ruminal acidosis (SARA) and methane production. This non-invasive approach eliminates the need for traditional cannulation, minimizing stress on the animal and opening new avenues for animal scientists. The impact of this research extends beyond individual cow health. By optimizing rumen function, we can improve feed efficiency, reduce methane emissions, and promote overall sustainability in dairy farming. Additionally, real-time data insights pave the way for precision nutrition, tailored interventions, and improved disease prevention, directly enhancing animal welfare. This novel approach to rumen monitoring represents a significant step towards realizing the full potential of PLF. By integrating AI and robotics, we can usher in a future where animal welfare and environmental sustainability go hand-in-hand, ultimately contributing to a more responsible and ethical dairy industry.

Journal of Animal ScienceVol. 102(Supplement_3)
Purdue University West Lafayette (US)
Responsible consumption and production
Openalex Percentile: Top 16%
Food Supply Chain Traceability
1.74
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