Gratheon Research connects academic literature, field datasets, machine learning models, and engineering experiments around digital beekeeping.
We focus on applied work around bee observability, colony health, computer vision, and automation. The most active product-facing research threads currently connect to Entrance Observer, robotic beehive, and AI features in our web app.
Research focus areas
Computer vision
Entrance traffic analysis, pollen and hornet detection, comb inspection, pose estimation, and behavior recognition.
Colony health
Varroa imaging, queenlessness signals, brood and comb analysis, pollination outcomes, and health-related observability.
IoT and observability
Hive scales, weather, acoustic sensing, remote telemetry, power constraints, and edge-device deployments.
Robotics and automation
Robotic comb mapping, biomimetic systems, and robotic-beehive experimentation linked to field monitoring.
Surveys and reviews
Landscape overviews of precision beekeeping, digital monitoring stacks, and machine learning methods.
Research papers index
Browse the full bibliography by year, topic, and product area without changing any existing paper URLs.
Highlighted papers and threads
COMB: Common Open Modular robotic platform for Bees
Recent open modular robotics work from University of Konstanz and Freie Universität Berlin.
Fanning behavior detection at the hive entrance
Object detection benchmark focused on behavior signals directly relevant to entrance monitoring systems.
Open-source varroa mite fall analysis
Practical vision tooling for colony-health workflows and varroa-related evaluation.
Continuous electronic beehive monitoring datasets
Reference data spanning audio, image, video, and weather signals for continuous hive observability.
Gratheon research assets
Gratheon datasets
Inspection photos, entrance videos, metrics, tracks, and external reference resources for experiments and benchmarking.
Gratheon models
Bee detection, queen detection, BeePose, and varroa-on-bee detection spanning browser inference, HTTP services, and edge experimentation.
Hacker projects
DIY, open hardware, and open-source systems for counters, scales, cameras, and telemetry that complement academic work.
Entrance Observer whitepaper
A direct technical entry point into Gratheon’s own monitoring work and collaboration discussions.
Recent collaboration signals
University of Tartu student teams
Production-ready AI work around bee type detection, hornet detection, and multi-class entrance monitoring.
TalTech / VIDRIK collaboration
Applied research and engineering exchange, including a joint white paper preprint.
Bachelor research support
Support for academic work focused on digital beekeeping solutions and practical system design.
Open to collaboration
We are open to working with researchers, universities, and applied engineering teams focused on bee health, observability, and machine learning.