Articles

Precision Livestock Farming (PLF) is a rapidly evolving management strategy for livestock that brings together engineering, animal science, information technology and artificial intelligence (AI) to enable continuous, automated and personalized management of livestock. Instead of relying on traditional herd management, PLF uses wearable sensors and biosensors, computer vision, the Internet of Things (IoT), and robotics and machine learning algorithms to provide real-time data on animal health, behavior, reproduction, productivity and environmental conditions. These technologies help to detect disease early, monitor animals' reproductive status, assess their welfare status and also aid in management of feed and water – all of which enhance production efficiency with fewer labour hours, less environmental impact and fewer antimicrobials. In the dairy and livestock sectors, the implementation of PLF has been gaining momentum due to rising global awareness about food security, climate change, antimicrobial resistance, and animal welfare. Still, even with great technological advances, the implementation has been limited in many developing nations due to the cost of investments, lack of digital infrastructure, lack of interoperability between technologies, and lack of technical expertise. The potential for further advancements in precision livestock management and more sustainable and resilient animal production systems through integration of multimodal sensing, predictive analytics, edge computing and digital phenotyping is expected in the future. The scientific development of Precision Livestock Farming is summarized, its technological background and applications are discussed and opportunities and challenges for the future are pointed out, especially in the context of developing livestock production systems.