ML research project exploring smart ear tags for livestock health monitoring. Developing pregnancy prediction and health indexing models for agricultural operations.
Targeting 90%+ accuracy from day 7 post-conception using biosensor data and time-series ML models. Revolutionary early detection.
Real-time health monitoring through continuous vital sign tracking and behavioral pattern analysis. Predictive health scoring.
Dedicated ML pipelines for cattle, sheep, and goats. Species-specific models ensure maximum accuracy.
IoT hardware prototypes with biosensors for continuous monitoring. Edge ML processing for real-time insights.
Behavioral pattern analysis identifies anomalies before symptoms appear. Reduce vet costs and improve outcomes.
Mobile and web dashboard concepts for comprehensive farm operations. Automation research to reduce manual checks.