Development and Validation of Data Acquisition System for Real-Time Thermal Environment Monitoring in Animal Facilities

In animal facilities, monitoring and controlling the thermal environment are essential in ensuring productivity and sustainability. However, many production units face challenges in implementing and maintaining effective thermal monitoring and control systems. Given the need for Smart Livestock Farming systems, this study aimed to develop and validate an easy-to-use, low-cost embedded system (ES_LC) for the real-time monitoring of dry-bulb air temperature (T_db, in °C) and relative humidity (RH, in %) in animal production facilities. The ES_LC consists of data collection/transmission modules and a server for Internet of Things (IoT) data storage. ES_LC modules and standard recording sensors (SRS) were installed in prototype animal facilities. Over 21 days, their performance was evaluated based on the Data Transmission Success Rate (DTSR, in %) and Data Transmission Interval (DTI, in minutes). Additionally, agreement between the ES_LC modules and the SRS was assessed using the daily mean root mean square error (RMSE) and mean relative error (RE) across different T_db and RH ranges. The ES_LC successfully collected and transmitted data to the cloud server, achieving an average DTSR of 94.04% and a predominant DTI of one minute. Regarding measurement agreement, distinct daily mean RMSE values were obtained for T_db (0.26–2.46 °C) and RH (4.37–16.20%). Furthermore, four sensor modules exhibited mean RE values below 3.00% across all T_db ranges, while all sensor modules showed progressively increasing mean RE values as RH levels rose. Consequently, calibration curves were established for each sensor module, achieving a high correlation between raw and corrected values (determination coefficient above 0.98). It was concluded that the ES_LC is a promising solution for thermal monitoring in animal facilities, enabling continuous and reliable data collection and transmission.