Animal Monitoring

Animal monitoring research focuses on developing automated systems for observing and analyzing animal behavior and health, primarily to improve livestock farming and wildlife conservation. Current efforts leverage computer vision, employing deep learning architectures like MobileNet SSD and transformers, alongside multimodal frameworks integrating object detection, segmentation, and pose estimation, to analyze video and image data from various sources, including drones and on-animal sensors. These advancements enable non-invasive, large-scale monitoring for early disease detection, improved welfare assessment, and optimized resource management, impacting both agricultural efficiency and ecological research. Federated learning approaches are also being explored to address data privacy and energy constraints in remote monitoring scenarios.