Wildlife Monitoring

Wildlife monitoring uses camera traps, drones, acoustic recorders, underwater sensors, and animal movement data to observe species and ecosystems with less manual effort. Common approaches include computer vision for detection, counting, tracking, and individual re-identification, alongside machine learning for call detection and multimodal analysis. Researchers also develop edge systems, active-learning workflows, and ecological benchmarks to make monitoring practical in remote settings and useful for scientific inference. Major challenges include scarce labels for rare species, performance shifts across sites and seasons, and balancing useful observations with animal disturbance.