Abstract

The demand for meat and dairy products is expected to rise significantly in the current demographic and economic growth context. Concurrently, various factors, including financial crises and reduced profitability, have decreased the number of livestock farms. Consequently, the livestock industry is undergoing intensification, with an increased number of cows per farm. This shift makes the management of animals increasingly complex. Amid these challenges, the society’s growing concern for animal health and welfare and the quality of consumed products underscores the importance of systems that aid in the individual and herd-level monitoring and control within livestock operations. In this scenario, precision livestock farming has become essential with the emergence of new sensors and technologies and the evolution of artificial intelligence. Against this backdrop, this paper reviews systems and techniques used in precision livestock farming to detect anomalies caused by reproductive processes and diseases in dairy and beef cattle. The article analyzes sensors and technologies employed, presents key studies conducted, and discusses the most commonly used artificial intelligence techniques in detecting prevalent anomalies.