Emerging technologies in precision livestock husbandry for livestock health management: A literature review.

Abstract

Precision livestock farming represents a key technological alternative to address the health, production, and environmental challenges of the beef cattle sector. This systematic review analyzes the use of emerging technologies, both hardware and software, focused on cattle health management. The PRISMA methodology and the Parsifal tool were applied to identify, select and evaluate studies published between 2020 and 2025, related to sensors, communication systems, artificial intelligence algorithms and digital platforms. The results show that technologies such as biometric sensors, GPS devices, thermal cameras and IoT communication networks have improved early disease detection, behavioral monitoring and livestock welfare. Likewise, the high performance of artificial intelligence models such as CNN, LSTM, SVM and Random Forest in the prediction of physiological events is highlighted, with efficiencies above 95%. Although significant benefits in efficiency and sustainability are observed, barriers related to technological adoption, connectivity and costs are identified. Finally, the development of scalable and adaptable solutions to diverse rural contexts is proposed as a future line, thus consolidating precision livestock farming as a key model for the sustainability of the livestock sector.