Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming
- PMID: 37335911
- PMCID: PMC10370899
- DOI: 10.1093/jas/skad206
Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming
Abstract
Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.
Keywords: Internet of Things; artificial intelligence; networking; precision livestock farming; sensors.
Plain language summary
Precision technologies are revolutionizing animal agriculture by enhancing the management of animal welfare and productivity. To fully realize the potential benefits of precision livestock farming (PLF), the development and application of digital technologies are needed to facilitate the responsible and sustainable intensification of livestock production over the next several decades. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring audibility in value chains while assuaging concerns associated with labor shortages. In this paper, we analyze the multilayered network of sensors, actuators, communication, and analytics currently in use in PLF. We analyze the various aspects of sensing, communication, networking, and intelligence on the farm leveraging dairy farms as an example system. We also discuss the potential implications of advancements in communication, robotics, and artificial intelligence on the security and welfare of animals.
© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Conflict of interest statement
The authors declare no real or perceived conflicts of interest.
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References
-
- Abecia, J. A., Pascual-Alonso M., Aguayo-Ulloa L. A., and Maria G. A.. . 2015. Comparison of several devices to measure body temperature in sheep. Prec. Livest. Farm. 09:221–229.
-
- Akhter, F., Siddiquei H. R., Alahi M. E. E., and Mukhopadhyay S. C.. . 2021. An IoT-enabled portable sensing system with MWCNTs/PDMS sensor for nitrate detection in water. Measurement. 178:109424. doi:10.1016/j.measurement.2021.109424. - DOI
-
- Alli, A. A., and Alam M. M.. . 2020. The fog cloud of things: a survey on concepts, architecture, standards, tools, and applications. Internet Things. 9:100177. doi:10.1016/j.iot.2020.100177. - DOI
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