A SMART FARM MANAGEMENT APPLICATION USING YOLOv11
As agriculture modernizes, integrating artificial intelligence (AI), image processing, and object recognition into farm management systems has become essential, especially in livestock farming, where traditional methods fall short. This paper introduces a smart farm application using the YOLOv11 mod...
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| Главные авторы: | , , , , , |
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| Формат: | Conference paper |
| Язык: | Vietnamese |
| Опубликовано: |
2025
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| Предметы: | |
| Online-ссылка: | https://scholar.dlu.edu.vn/handle/123456789/4938 |
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| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
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| Итог: | As agriculture modernizes, integrating artificial intelligence (AI), image processing, and object recognition into farm management systems has become essential, especially in livestock farming, where traditional methods fall short. This paper introduces a smart farm application using the YOLOv11 model for real-time object detection to enhance livestock monitoring and control. The system, built with Python (backend), ReactJS (frontend), NodeJS, and Capacitor for mobile deployment, detects anomalies such as abnormal animal behavior or unauthorized access. It tracks individual animals' data and supports resource planning, disease monitoring, and intelligent reporting. Designed for small to medium-sized farms, the application improves productivity, security, and sustainability by aligning with the digital transformation of agriculture. |
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