Application of Artificial Intelligence (AI) in Modern Pig Breeding

The development of artificial intelligence (AI) technologies in pig farming significantly supports herd management, animal health monitoring and optimization of the rearing environment. The paper reviews key solutions such as radio-frequency identification (RFID) sensors, vision systems, sound analysis, deep learning algorithms and intelligent microclimate control systems that support production efficiency. Studies show that computer vision systems achieve more than 90% efficiency in detecting lameness, enabling faster intervention and reducing health losses. AI models for estrus detection achieve more than 95% accuracy, improving insemination planning and increasing reproductive rates. Monitoring feed intake with AI can increase feeding efficiency by 15–20%, improving daily gains and reducing feed wastage. Sound analysis systems enable early detection of respiratory diseases, reducing mortality and increasing pig welfare. The use of intelligent microclimate control systems can automatically regulate temperature, humidity and air quality, reducing environmental stress and preventing disease. The introduction of big data (BD) and Internet of things (IoT) technologies, meanwhile, enables real-time analysis of large data sets to support precision livestock management. Despite the many benefits, the full implementation of AI in pig breeding still requires work on algorithm optimization, component sustainability and implementation costs. The integration of these solutions into precision farming sets the stage for modern and sustainable livestock production.