Real-time crop health monitoring

Annotating and labeling agriculture datasets to train your AI \ ML models for crop health and soil monitoring, pest detection, and yield prediction, livestock management, fructification detection, unwanted weeds detection to optimize agricultural practices.

The below use cases will help you understand how our Annotations will prove to be very useful:

• Monitoring Ripeness Levels
• Farming with Robotics
• 3D Field Monitoring
• Livestock Management
• Unwanted Plants Detection
• And many more

In the agricultural sector, industry experts including pathologists, horticulturalists, etc., annotate images. These images are usually collected from field robots and drones. We identify plants, pests, diseases, livestock, and more from the images and videos. In such a way the algorithms recognize them automatically.

Apart from detecting crop types, we also use image annotation to help computer vision models check and monitor the health of all crops. This is done through deep learning AI model.