Sensing Reliability Degradation Associated with Cattle Activity in Smart Barns: A Recovery Framework Using Behavioral Context

Smart barns rely on vision, wireless, and environmental sensing systems for continuous livestock monitoring, but sensing reliability may vary with cattle behavioral context. This study investigates the associations between herd-level behavioral contexts and multimodal sensing degradation and proposes a context-aware recovery framework using a Sensing Reliability Degradation Index (SRDI). Data collected from 12 cattle in a single semi-open barn over 14 days were organized into 2016 non-overlapping ten-minute windows and classified into five contexts: Normal, Feeding, Moving, Resting, and Crowding. Feeding and Crowding were associated with increased visual occlusion and wireless degradation, whereas Moving exhibited greater tracking instability. Mean SRDI before recovery ranged from 0.19 in Resting to 0.69 in Crowding. In an offline evaluation, the proposed framework increased data completeness from 92.4% to 97.1%, detection continuity from 84.6% to 91.8%, and packet delivery ratio from 93.1% to 97.6%, while reducing mean transmission delay from 176 to 134 ms. Mean SRDI decreased from 0.32 to 0.23, representing a relative reduction of 28.1%. Compared with a context-independent adaptive baseline, SRDI decreased from 0.28 to 0.23. Independent manual validation of behavioral context labels yielded an accuracy of 89.3% and a macro-averaged F1-score of 0.88. Statistical and robustness analyses further supported the reported differences under the evaluated conditions. These findings suggest that behavioral context can provide useful supplementary information for sensing reliability assessment and recovery selection. However, the single-barn observational dataset, shared vision-derived inputs, and offline log-based evaluation limit causal interpretation and generalizability. Future work should validate the framework using multi-site studies and prospective real-time deployment.