With the large-scale and intensive development of cattle farming, traditional health monitoring is incompetent for both dairy and beef cattle in commercial and research settings due to high labor costs and poor real-time performance, making intelligent technologies a core solution. This review innovatively integrates three core dimensions—behavioral detection, physiological parameter monitoring, and in vitro substance analysis—filling the gap of single-dimensional summaries and systematically combining technical performance with key deployment considerations (cost, durability, environmental adaptability). Studies show that the detection accuracy of key health indicators generally exceeds 85%, but most technologies face common challenges including animal stress, environmental interference, and complex calibration. Future research should prioritize multimodal data fusion, low-cost sensor development, and anti-interference algorithm optimization. This review provides comprehensive technical references for smart livestock farming, facilitating efficient and sustainable cattle health management.