Overview
An automated egg production monitoring system for goose farms using deep learning-based object detection to track and analyze egg production patterns.
Features
- Real-time Detection: YOLO-based egg detection and counting
- Production Analysis: Daily and weekly production statistics
- Automated Reporting: Generate production reports
- Historical Tracking: Monitor production trends over time
Tech Stack
- Backend: C# (.NET Framework)
- AI/ML: Python, YOLO (You Only Look Once)
- Computer Vision: OpenCV
- Data Storage: SQL Server
Publication
This work was published at IEEE conference:
- Title: Egg Production Analysis System for Goose Farms
- Conference: IEEE International Conference on Applied System Innovation
- Year: 2019
- View Paper
Technical Implementation
Object Detection Pipeline
- Video feed capture from farm cameras
- Frame preprocessing and enhancement
- YOLO model inference for egg detection
- Post-processing and counting
- Data aggregation and storage
Model Training
- Custom YOLO model trained on goose egg dataset
- Data augmentation for various lighting conditions
- Fine-tuned for farm environment specifics
Results
- 95%+ detection accuracy
- Real-time processing capability
- Reduced manual counting labor by 80%
- Improved production record accuracy