Animal Molecular Breeding 2024, Vol.14, No.2, 187-195 http://animalscipublisher.com/index.php/amb 188 2 Key Technologies in Precision Livestock Farming 2.1 Sensor technologies Sensor technologies are fundamental to precision livestock farming (PLF), enabling the continuous monitoring of various parameters related to animal health, behavior, and environmental conditions. Wearable sensors, for instance, can track eating habits, rumination, body temperature, and activity levels, providing critical data for early disease detection and overall animal management (Džermeikaitė et al., 2023). These sensors can be attached to or implanted in animals, offering real-time data that helps farmers make informed decisions to enhance productivity and animal welfare (Gagliardi et al., 2021). Additionally, sensors are used in aerial and satellite-based systems to measure pasture quality and quantity, further supporting efficient livestock management (Tedeschi et al., 2021). 2.2 Data analytics and artificial intelligence Data analytics and artificial intelligence (AI) play a crucial role in processing the vast amounts of data generated by sensor technologies. AI, particularly machine learning (ML), can analyze complex datasets to predict animal health issues, optimize feeding strategies, and improve overall farm management (Zhang et al., 2021). For example, ML models can predict fertility patterns and diagnose eating disorders in livestock using data collected from collar sensors (Liu et al., 2023). The integration of AI with traditional mechanistic models can lead to hybrid intelligent systems that enhance the sustainability and efficiency of livestock production (Sharma et al., 2021). 2.3 Internet of things (IoT) and connectivity The internet of things (IoT) is a key enabler of precision livestock farming, facilitating the seamless connection and communication between various devices and systems on the farm. IoT sensors provide precise information about animal health and environmental conditions, which can be remotely monitored and analyzed (Benjamin and Yik, 2019). For instance, IoT-enabled wearable devices can transmit data on animal behavior and physiological parameters, allowing for real-time monitoring and management (Monteiro et al., 2021). The integration of IoT with data analytics and AI further enhances the ability to make data-driven decisions, improving farm productivity and sustainability (Akhter and Sofi, 2021). 2.4 Robotics and automation Robotics and automation are transforming livestock farming by reducing the need for intensive manual labor and improving operational efficiency. Automated systems, such as milking robots and feeding machines, can perform repetitive tasks with high precision, ensuring consistent care and management of livestock. These technologies not only reduce labor costs but also enhance animal welfare by providing timely and accurate interventions. Additionally, the use of unmanned aerial vehicles (UAVs) and automated data collection systems enables farmers to monitor large areas and gather detailed information on animal health and environmental conditions. In summary, the integration of sensor technologies, data analytics and AI, IoT, and robotics and automation is driving significant advancements in precision livestock farming. These technologies collectively enhance the ability to monitor, manage, and optimize livestock production, contributing to improved productivity, sustainability, and animal welfare (Vaintrub et al., 2020). 3 Applications of Precision Livestock Farming 3.1 Health monitoring and disease prevention Precision livestock farming (PLF) technologies have significantly advanced the ability to monitor animal health and prevent diseases. These technologies include sensors, cameras, and microphones that enable continuous and real-time monitoring of livestock. For instance, wearable Internet of Things (W-IoT) devices can provide precise and dynamic health data, which is crucial for early disease detection and intervention (Zhang et al., 2021). Additionally, PLF systems can monitor animal behavior and physical conditions, allowing for timely responses to health issues, thereby improving overall animal welfare and reducing the need for antibiotics (Figure 1) (Vranken and Berckmans, 2017). The integration of these technologies into livestock farming not only enhances animal health but also contributes to the sustainability of farming practices by minimizing the environmental impact of disease outbreaks (Monteiro et al., 2021).
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