varroa mite detection
goal / problem solved | 🦀Infestation of Varroa mite |
---|---|
Status | Groomed |
billing plan | 2-essential |
verticality | vertical |
concept hierarchy path | apiary/hive/box/frame/frame-side/file |
Date | |
Priority | 20 |
estimate | 5 |
impact = priority % | 100 |
Tags | IoTMLbackendfrontend |
Why
Varroa mites are the biggest danger to colonies today
- they feed on larvae, pupae, adult honey bees
- they leave open wounds
- they consume fat body of a bee, making bees weak (immune response, energy storage, detoxification)
Suggested solution
- Datasets:
App integration
- Prepare the data. For this we need to cut regions from the original frame where we detect bees - see 🐝Worker bee detection
- use AI model like yolo, get weights to detect and count mites on individual bees
- return absolute number of mites found in an image
- add http API to this model
- integrate image-splitter with this model - it manages frame photos
- store result in DB (a db migration would be needed)
- display mite infection % per frame and per hive in web-app
- generate an alert beekeeper if its above some treshold after some period of time (blocked by another issue)
Related possible detections
- detect deformed wings virus that is spread by varroa
- detect parsitic mite syndrome - uncapped larvae caused by high mite infestation
- paralysis viruses (black-shiny immobile bees)
Solution
https://github.com/Gratheon/web-app/pull/70
https://github.com/Gratheon/image-splitter/pull/17
Problem currently
- roboflow costs too much
- has too strict limits for free tier
- prediction does not work well for frame photos, even if they are sliced in parts