Honey Bee

Honey bee research currently focuses on developing automated monitoring systems to address population decline and threats to hive health. This involves employing computer vision techniques, particularly convolutional neural networks (like ResNet and YOLO variants), to analyze images and videos for bee counting, pollen monitoring, and Varroa mite detection, as well as using audio analysis and sensor data (temperature, humidity) to assess hive health and predict factors like winter mortality. These advancements leverage machine learning for improved accuracy and efficiency in beekeeping practices and environmental monitoring, ultimately contributing to better conservation efforts and sustainable agriculture. Furthermore, research is exploring the use of machine learning to predict honey production and analyze the toxicity of pesticides on bees.