Abstract: Cow intelligent monitoring is an important link in large-scale dairy farming. Video analysis has the advantages of contactless, low-cost, and intelligent analysis, and has become a hot spot in the research of intelligent identification technology of large-scale dairy cows. Dairy cow target detection, target tracking, and the technologies of individual and behavior recognition are of great significance for large-scale dairy cow supervision. Lighting, day and night alternations, fence occlusion and mutual occlusion caused by large number of cows in complex breeding environment are serious factors affecting the intelligent monitoring of large-scale dairy cows. This paper summarized the depth models and practical application commonly used in cow intelligent monitoring. The problems and challenges faced in the current research were put forward. The analysis result showed that the attention mechanism and hybrid convolution were effective methods to improve the recognition accuracy of the model, and the lightweight modules were conducive to reducing the complexity and computation of the model. The factors that affected the current research to be practical were computational complexity, universality and accuracy. It is necessary to conduct specific analyses based on the dairy farming environment and the condition of dairy cows to continuously meet the needs of large-scale farming while applying this technology.