Bee Health

Research on bee health is intensely focused on developing automated monitoring systems to address the alarming decline in bee populations. Current efforts leverage computer vision, employing convolutional neural networks (like ResNet-50 and YOLOv7) and multimodal neural networks, integrating audio and visual data to assess beehive health parameters such as bee counts, pollen collection, Varroa mite infestation, and overall colony strength. These advancements offer non-invasive, efficient, and data-driven approaches for early disease detection and improved hive management, ultimately contributing to more effective bee conservation strategies.