Resumen
Efficiently managing temperature and humidity in a pig house is crucial for enhancing animal welfare. This research endeavors to develop an intelligent temperature and humidity control system grounded in a three-way decision and clustering algorithm. To establish and validate the effectiveness of this intelligent system, experiments were conducted to compare its performance against a naturally ventilated pig house without any control system. Additionally, comparisons were made with a threshold-based control system to evaluate the duration of temperature anomalies. The experimental findings demonstrate a substantial improvement in temperature regulation within the experimental pig house. Over a 24 h period, the minimum temperature increased by 4 °C, while the maximum temperature decreased by 8 °C, approaching the desired range. Moreover, the average air humidity decreased from 73.4% to 68.2%. In summary, this study presents a precision-driven intelligent control strategy for optimizing temperature and humidity management in pig housing facilities.