Beehive Operation Behavior Recognition Dataset

Current challenges in the agricultural industry include declining bee populations and low efficiency in beekeeping. Traditional monitoring methods rely on manual observation, which is inefficient and prone to errors. Existing solutions show significant deficiencies in real-time capability and accuracy, failing to meet modern agriculture's demands for intelligence and automation. This dataset aims to support the automatic detection and recognition of bee behaviors to help beekeepers improve management efficiency and make scientific decisions through high-quality image data. Data is collected using high-resolution cameras under natural lighting conditions, capturing bee activities inside and outside the hive to ensure data authenticity and diversity. For quality control, multiple rounds of annotation and expert reviews are employed to ensure consistency and accuracy of data annotations. The data is stored in JPEG format and organized in a structured manner for easy subsequent processing and application.