A deployable LoRa-based end-to-end monitoring architecture for commercial beef cattle barns under limited-connectivity conditions

Reliable barn environmental monitoring is essential for animal welfare, heat-load assessment, ventilation management, and data-driven decision-making in commercial beef cattle production. However, many beef cattle farms are located in areas with limited network connectivity, making it difficult to obtain continuous multi-parameter records that are ultimately available for practical management use. This study developed and field-validated a deployable LoRa-based end-to-end monitoring architecture for commercial beef cattle barns under limited-connectivity conditions. The architecture integrates private LoRa wireless backhaul, gateway Wi-Fi uplink, and a self-hosted server to support the acquisition, transmission, ingestion, storage, and visualization of air temperature, relative humidity, temperature–humidity index (THI), wind speed, illuminance, carbon dioxide, and ammonia. Field validation was conducted in two representative commercial beef cattle barn scenarios: a winter enclosed barn and a summer open-sided barn. Server-side data-ingestion timestamps were used to evaluate the practical availability of field data for management-oriented monitoring by quantifying arrival period, arrival jitter, and effective packet reception rate (PRR). During two consecutive weeks of operation, the server-observed arrival period remained close to the configured 60 s reporting cycle, the median absolute arrival jitter was 1 s in both scenarios, and the mean node-level effective PRR exceeded 98%. Representative monitoring records further captured interpretable changes in thermal conditions, ventilation-related variables, and air-quality indicators under real operating conditions. These results indicate that the proposed architecture can provide stable and interpretable environmental records for commercial beef cattle barns under limited-connectivity conditions. The study also highlights server-side end-to-end data availability as a practical criterion for evaluating whether field monitoring data are usable for production-oriented management decisions.