ABSTRACT
This chapter embarks on a transformative exploration into the application of AI and IoT technologies in revolutionizing livestock management. The chapter unfolds with a comprehensive introduction, setting the stage for a groundbreaking machine learning odyssey reshaping the livestock monitoring landscape. Central to this narrative is the pivotal role of data collection mechanisms and sensor technologies in livestock monitoring. The chapter delves into the intricacies of these systems, highlighting their significance in capturing real-time data critical for monitoring livestock health and productivity.
Machine learning takes the forefront in livestock health monitoring, unveiling its potential in predictive analytics to foresee and prevent health-related issues. By leveraging predictive models and data analytics, this technology empowers farmers to proactively address health concerns, ultimately enhancing livestock productivity and well-being. Moreover, the chapter navigates through a spectrum of applications, encompassing environmental monitoring and resource optimization. It explores various facets, such as the identification of animals through automated systems, the utilization of weighing automation technologies, and environmental conditions monitoring in sheds and aquaculture environments.
Livestock behavior analysis emerges as a cornerstone, showcasing how AI-powered algorithms decode crucial behavioral patterns. From observing drinking and feeding habits to analyzing activity, movement, posture, feces identification, temperature analysis for heat stress monitoring, and even interpreting vocalizations, these insights deepen our understanding of animal welfare and enable prompt intervention when required. Additionally, the chapter elucidates the significance of monitoring pasture, enhancing hatcheries, and tracking embryo development. Each aspect showcases the transformative potential of machine learning and IoT technologies in reshaping the livestock industry.
