Computer Vision and Machine Learning for Automated Monitoring of Native Social and Solitary Bees

Native social and solitary bees are crucial pollinators of native vegetation and crops, yet they are rarely monitored compared to honeybees. To address this gap, this thesis presents computer vision and machine learning systems for native bee monitoring. For social bees, we designed a system that tracks them at their hive entrances, allowing detailed analysis of their foraging behaviour over time. For solitary bees, we implemented facial recognition technology to accurately identify and count individual bees, facilitating precise monitoring. These automated, scalable digital tools advance the monitoring of native bees, enhancing our understanding of their behaviours.