PARAMETERS FOR ASSESSING SHEEP WELFARE CONSIDERING MODERN APPROACHES IN THE CONTEXT OF ARTIFICIAL INTELLIGENCE AND PREDICTIVE ANALYTICS
DOI:
https://doi.org/10.37000/abbsl.2026.119.27Keywords:
sheep welfare, parameters, artificial intelligence, predictive analytics, precision livestock farming, One Health.Abstract
The article examines modern approaches to assessing sheep welfare using artificial intelligence (AI) and predictive analytics technologies. Traditional and innovative welfare assessment parameters are summarized, including behavioral, physiological, productive, and environmental indicators. The feasibility of integrating digital technologies, sensor systems, and machine learning algorithms to form an objective, continuous, and multifactorial assessment of animal status is substantiated. It has been established that the most promising approach is a multiparametric one that combines physiological, behavioral, environmental, and productive indicators. It is shown that the integration of Precision Livestock Farming (PLF) technologies, sensor systems, and machine learning algorithms enables continuous real-time monitoring and prediction of animal conditions. The need to develop digital AI-based models for sheep welfare assessment is justified.
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