This article reviews the impact of artificial intelligence (AI) and machine learning (ML) on modern livestock farming, focusing on monitoring animal welfare and detecting thermal stress in cattle. It highlights digital technologies such as smart sensors and the Internet of Things (IoT), which enable continuous and non-invasive monitoring. Articles from indexed journals since 2020 were analyzed using keywords related to stress and precision livestock farming. Findings indicate that algorithms like Random Forest and XGBoost show high accuracy in predicting health conditions, with one study reporting 89.3% accuracy in detecting thermal stress. Despite promising advancements, the need to improve model accuracy and data integration for effective implementation is emphasized. Overall, AI and sensor technologies provide advanced tools for managing stress in livestock, enhancing animal welfare and productivity in the industry.
Rivera et al. (Thu,) studied this question.