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Precision Livestock Farming: Monitoring and Managing Animal Health
Abstract
Precision Livestock Farming (PLF) is an emerging approach that utilizes advanced technologies to monitor, manage, and optimize livestock production systems. This paper examines the application of sensor-based monitoring, data analytics, and automation technologies in livestock management, with a focus on improving animal health, welfare, and productivity. It explores the integration of sensors, such as RFID tags, accelerometers, and temperature probes, to collect real-time data on animal behavior, physiological parameters, and environmental conditions. The paper discusses the use of machine learning algorithms and decision support systems to analyze large volumes of sensor data, identify patterns, and detect early signs of disease, stress, or discomfort in livestock populations. It also explores the implementation of automated feeding, ventilation, and environmental control systems to optimize feed efficiency, reduce energy consumption, and minimize environmental impact. By leveraging PLF technologies, farmers can make data-driven decisions, enhance animal welfare, and improve the overall sustainability of livestock production.
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References
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