Precision livestock farming in dairy production is advancing through biosensorbased monitoring that converts frequent, longitudinal measurements into actionable information to support animal-level decision-making under commercial conditions. This review summarizes biosensors for precision dairy farming with a systems perspective that connects sensing, data transfer, analytics, and visualization. Biosensors can be categorized by sensing locus as at-animal, near-animal, and from-animal to clarify practical tradeoffs among invasiveness, scalability, maintenance burden, and diagnostic specificity. The review also describes how information should progress from raw signals to interpretable indicators and decision-support outputs, emphasizing that farm value depends on reliable interpretation and timely intervention rather than on measurement alone. Key applications are synthesized across nutrition and feeding behavior, reproduction (including estrus and calving), health monitoring (such as mastitis, lameness, and metabolic disorders), welfare assessment, and environmental sustainability, highlighting where different modalities best support screening, early warning, and confirmatory detection. Finally, the review discusses on-farm barriers, including missing data, sensor drift, attachment stability, communication failures, and alert fatigue, and proposes future directions in standardization, interoperability, and artificial intelligence-enabled decision support to strengthen end-to-end system reliability, scalability, and economic sustainability under commercial conditions.
Lee et al. (Tue,) studied this question.