Traditional livestock sorting systems are inefficient and overly simplistic, relying primarily on weight to classify animals. This approach overlooks critical factors such as age, gender, developmental progress, and health status, leading to poor sorting accuracy, inefficiencies, and increased labour costs.
Core Features
- Image-Based Data Collection: Livestock images are captured upon entering a detection area, extracting vital information like breed, physical traits, and health status.
- Comprehensive Analysis: Real-time and historical weight data are analysed to evaluate growth trends and development status.
- Automated Sorting: Animals are classified based on multiple factors, including health and development, and directed to appropriate sorting areas using automated gates and guidance systems.
Inventive Step
Unlike conventional systems, this invention employs advanced image processing and machine learning to analyse various livestock attributes beyond weight, such as health indicators (e.g., body condition, skin abnormalities). It integrates these insights with weight trends to deliver a more nuanced and accurate sorting process.
Tangible Benefits
- Efficiency Gains: Fully automated operations reduce manual labour and human error.
- Enhanced Animal Welfare: Early detection of health issues allows for timely interventions, promoting better livestock care.
- Improved Accuracy: Sorting tailored to individual animal needs enhances productivity and management.
Broader Impact
This system sets a new benchmark for automation in animal husbandry, addressing industry challenges like labour shortages and zoonotic disease risks. By enabling precise and humane livestock management, it contributes to sustainable farming practices and improved food production efficiency globally.