This project leverages advanced deep learning and machine learning techniques to revolutionize agriculture and livestock sectors. Using the YOLOv8 model for real-time livestock counting, it reduces errors and enhances efficiency. Traditional animal counting methods are time-consuming and error-prone, especially in large farms, leading to high labor costs.
The project includes a Flask web application, enabling easy interaction with the deep learning model. Flask provides a user-friendly interface for performing animal counts, allowing flexible management from anywhere.
BarnEye AI, not only improves efficiency but also enhances animal welfare and management. Accurate data-driven decisions help maintain animal health and reduce operational costs. This project represents a significant step towards digital transformation in agriculture, with potential for future applications and sustainability.
For a detailed overview of the project, please view our Canva Presentation.
https://drive.google.com/drive/folders/1xXggrBlf8VvEZJ5qbTQS3GdWFzgg9Ptt?usp=drive_link