| | 1 | [[TOC(Other/Summer/2022/Beehive/*, depth=1, heading=Agricultural Monitoring of Beehive Health)]] |
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| | 3 | = Agricultural Monitoring of Beehive Health = |
| | 4 | **WINLAB Summer Internship 2022** |
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| | 6 | **Group Members:** Joel Paley, Fairuz Zahin, Izabela Bigos, Sarah Marty |
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| | 8 | == Project Objective == |
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| | 10 | The project uses a combination of computer vision (CV), machine learning, and long range low energy wireless communication to monitor bee health. |
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| | 12 | Recently honeybees have been suffering a decline, manifested as colony collapse disorder (CCD). This project seeks to quantify hive health to get advanced warnings of hive decline before CCD strikes by monitoring hive activity at the entrance. In this project, you will place a camera with a small single board computer that uses computer vision to count the number of bee entrances and exits, as well as the number of guard bees. These counts will be sent back in real time to a cloud server using a long range, low power LoRA radio. Depending on the season, these counts are a good indicator is a hive is growing, shrinking, or under attack. The SBC and LoRA radio will be powered by a solar cell and battery. |
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| | 14 | Additionally, machine learning can be used to identify hive invaders, such as hornets and yellowjackets. |
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