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Machine Learning Applications in Livestock Management
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Author(s): Sachinn Sharma (Manav Rachna International Institute of Research and Studies, India), Himanshu Maurya (Manav Rachna International Institute of Research and Studies, India), Kanay Sharma (Manav Rachna International Institute of Research and Studies, India)and Vishal Kumar (Manav Rachna International Institute of Research and Studies, India)
Copyright: 2026
Pages: 18
Source title:
AI Innovations for Transforming Food Production
Source Author(s)/Editor(s): Pawan Whig (Vivekanada Institute of Professional Studies, India)and Ahmed Elngar (Beni-Suef University, Egypt)
DOI: 10.4018/979-8-3373-0842-5.ch009
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Abstract
The integration of machine learning (ML) into livestock management is revolutionizing the way animal farming is conducted, offering data-driven solutions to enhance productivity, animal health, and resource efficiency. This chapter explores the applications of ML techniques in various aspects of livestock management, including disease detection, behavior monitoring, feed optimization, reproductive management, and environmental control. By analyzing real-time data from sensors, cameras, and wearable devices, ML models can provide early warnings for health issues, automate routine tasks, and support informed decision-making. The chapter also addresses challenges such as data quality, model interpretability, and integration with existing farm systems, while highlighting case studies and emerging trends that illustrate the transformative potential of ML in modern animal husbandry.
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