Operational Intelligence
Farm Wildlife Alerts
Species calls for farm wildlife, with false-alert exposure reported next to accuracy.
About the Project
In development: a research-stage system that identifies which animal is entering a farm plot, built on pretrained wildlife detectors and classifiers. Each benchmark run scores every species on its own and reports how often a non-target animal would wake the farmer, next to accuracy. The night-time head, the alert logic and the field hardware are still being designed.
Technical Overview
Data Sources
- Public wildlife photographs and camera-trap archive images
- Labelled detection-dataset crops
- Negative-class images: livestock, dogs, people, empty frames
- Night-time infrared frames (limited)
ML / NLP Stack
- Pretrained wildlife detector and species classifier, benchmarked per species
- Background-subtraction motion detection
- Per-image alert-exposure reporting
Key Challenges
- Night imagery is scarce in public archives
- Look-alike animals in darkness (cattle and nilgai)
- Keeping false alerts low enough that a farmer keeps the system on
- Labels that do not match the animal in frame
Interested in this solution?
Let's discuss how we can adapt this approach for your business.
Get in Touch