๐ Credits
Here we list all volunteers that have helped us. Consider this as a hall of fame
Engineeringโ
| Person name | Focus |
|---|---|
| Aleksei Prokopov | Worked on digital scales IoT device (hardware) |
| Vjatลกeslav Kekลกin | Published on our whitepaper (research) |
| Kurban Ramazanov | Helped with UI/UX, designing prototypes to imporove web-app experience |
| Alonso Solis | participated in andmetorm hackathon, worked on UI design and FE components |
| Adrian Ala | participated in andmetorm hackathon, worked on UX flow and pitching |
| Ahmed Daoudi | Helped with telemetry-api, building initial service version in express/nodejs |
| Muhammad Zain Shakeel | Helped with 3D model of the robotic beehive |
| Natalia Kinash | Participated in the hackathon where she helped Reinis Indans with satellite imagery processing |
| Reinis Indans | Participated in a hackathon where he did most of the heavy work on data collection and model training for satellite pollination sub-project - satellite-pollination-map microservice |
Machine Learning Research - University of Tartuโ
Students from University of Tartu Machine Learning course (MTAT.03.227), taught by Dmytro Fishman, Associate Professor, who contributed production-ready AI models for bee and hornet detection
| Person name | Focus | Impact |
|---|---|---|
| Kreete Kuusk | Bee type detection (T30) | YOLOv8 model training, manual dataset review and quality assurance, team coordination |
| Danni Zhang | Bee type detection (T30) | YOLOv10 model training, data preprocessing with image tiling, copy-paste augmentation for class balancing |
| Jasper Luik | Bee type detection (T30) | Dataset search on Roboflow, RT-DETR model exploration, initial YOLOv10 training on balanced/unbalanced data |
| Rasmus Mirma | Bee type detection (T30) | YOLOv12 model training, dataset preparation from Mississippi State University, model visualization on images and videos |
| Albert Unn | Hornet detection (T14) | Model development, created YOLOv8-nano achieving 96.7% precision for hornet detection at hive entrance |
| Kadi-Liis Kivi | Hornet detection (T14) | Data labeling and preprocessing for hornet detection dataset (~1250 images) |
| Karen Roht | Hornet detection (T14) | Model architecture research and training, comparative analysis of detection models |
| Otto Kase | Hornet detection (T14) | Dataset creation and augmentation, specialized in data pipeline development |
| Norman Tolmats | Multi-class bee detection (T41) | Auto-annotation pipeline, generated 30k+ labeled images, led YOLO-based detection experiments |
| Mihkel Kulu | Multi-class bee detection (T41) | Dataset evaluation, model iteration and validation for real-time bee classification |
| Joonas Tiitson | Multi-class bee detection (T41) | Built initial YOLO pipeline using Roboflow dataset, evaluated alternative architectures like RT-DETR |
| Markus Kivime | Multi-class bee detection (T41) | Manual annotation of validation dataset, quality assurance for model evaluation |
Testingโ
| Person name | Focus |
|---|---|
| Arina Turgeneva | Helped with extensive web-app testing |
| Maria Lutsiv | helped with web-app testing |
| Anastassia Tsalko | helped with web-app testing |
| Andrei Kuzmin | helped with web-app testing |
| Vladislav Tjagunovitลก | helped with web-app testing |
Product Ideasโ
| Person name | Focus |
|---|---|
| Artjom Shestajev | product development ideas |
| Roop Runjan Khan | participated in andmetorm hackathon |
| Aleksei Boris | Participated in 2 hackathons and helped with pitching |
| Olena Stoliarova | participated in a Climathon hackathon, helping with pitching |
**Thank you all!