Abstract: In the process of dairy cow farming,gait abnormalities can be observed in the early stages of various diseases such as limb and hoof problems,postpartum weakness and more. As an early indicator of dairy cows' health status,gait abnormalities not only signal changes in individual cows' health but also impact their welfare,production performance and breeding efficiency,ultimately leading to greater economic losses for farms. This paper delved into the mechanisms that gave rise to gait abnormalities in dairy cows and based on this understanding, emphasized the positive significance of smart health management systems for dairy cows in enabling early individual disease diagnosis through the detection of gait abnormalities. Leveraging intelligent sensors,multimodal data algorithmic models,and high-performance edge-cloud computing capabilities,these systems provide novel disease warning and health assessment tools for dairy farms. The goal of this system is to establish a modern dairy farming system that integrates comprehensive vital sign monitoring,intelligent analysisand precise auxiliary diagnosis,thereby overcoming the limitations of traditional manual diagnostic techniques and ensuring objective,comprehensive,accurate,and timely disease detection in dairy cows. Clinical case studies indicate that, after implementing a smart health management system for dairy cows, farms experience 3~4 times increase in the number of diseases detected compared to manual methods, with detection occurring 7~30 days earlier. The application of this system effectively enhances herd health,reduces sunk costs,and boosts economic efficiency.

Key words: smart farming, artificial intelligence, big data, dairy cow disease early warning, gait abnormalities