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Deep Learning and Computer Vision for Honey Bee Health Monitoring: A Systematic Survey and Future Directions

Honey bees are very important for the world's food supply and the health of ecosystems. Deep learning and computer vision techniques offer non-invasive ways to monitor honey bee health, count bees, detect mites like Varroa, and track behaviors. This systematic survey reviews current methods, datasets, and maps future research directions.

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Publication details

Authors
Shraddha Hajari, Smita Kasar
Organizations
🇮🇳 SSVPS's Bapusaheb Shivajirao Deore College of Engineering
Year
2026
Type
Journal

Relevancy to Gratheon

This systematic survey directly informs Gratheon's computer vision and machine learning roadmap. By summarizing current techniques and open datasets for Varroa detection, bee counting, and behavior tracking, it provides an evidence-based map of the most robust algorithms and architectures. Gratheon can utilize these insights to develop more accurate object-detection and tracking models for our hive entrance monitoring cameras.