AI Training Data for Agritech
Providing AI enterprises with high-quality training data to empower agriculture in managing land, livestock, and farms more effectively through IoT, sensors, location systems, robotics, and artificial intelligence.
Smarter Data Annotation Solutions for AI-Driven Agriculture
Annotating and labeling agricultural AI data to build ML models for crop health and soil monitoring, livestock management, fruiting detection, weed identification, and more.
Data Annotation for Advancing Agricultural AI
2D Bounding Box Annotation for Precision Crop Detection
Perception models simplify crop detection by leveraging 2D bounding boxes. With high-quality training data, AI can be deployed to distinguish crops from weeds and identify unwanted grass for efficient management.
Polyline Annotation for Accurate Crop Lane Classification in Large Farms
Polyline annotation with splines enables precise classification and characterization of agricultural objects. These techniques help build AI systems capable of detecting crop diseases, analyzing irrigation patterns, and predicting harvest times across large farms.
3D Point Cloud for LiDARs Sensing
Using 3D Point Cloud to enhance LiDAR sensors’ 3D image-sensing capabilities to help autonomous vehicles understand their surroundings, create accurate maps of objects placed on the premises, and detect other objects’/vehicles’ movements for risk-free autonomous driving
Polygon for Irregular Shapes Detection
Get experts on hand to draw precise polygons around oddly shaped objects. This way, computer vision can allow automated vehicles to recognize all visible objects on the road, including motorcycles, bicycles, cars, animals, etc., to promote safe driving avoiding collisions.
AI Use Cases in Agriculture
Artificial intelligence is transforming agriculture by supporting healthier yields, effective pest control, and precise monitoring of soil and crops. Explore popular use cases of AI in agriculture to see how it contributes to smarter, more sustainable farming.
The following use cases can provide you with more insight into how our data annotation & labeling expertise can benefit your autonomous driving initiatives:
3D Field Mapping
Drone and satellite data can generate 3D field maps that provide agronomists with accurate estimates of crop yields and pricing.
Livestock Management
Leverage training data to develop machine learning models that accurately track livestock movements, enhance management, and support animal welfare.
Crop Yield Prediction
Using our training data, AI and machine learning can power drones and real-time sensors to enhance accuracy in crop yield prediction.
Intelligent Spraying
Leverage our expertise in computer vision training data to build machines and models that detect and prevent crop disorders through intelligent spraying.
Crop Health & Soil Monitoring
AI simplifies farm operations and delivers precise crop health insights by analyzing soil chemicals and nutritional values.
Monitoring Fructify/Ripeness Levels
Image annotation supports the development of AI models that analyze fruit and vegetable health, as well as ripeness levels, enabling intelligent grading and sorting.
Precision Farming with Robotics
AI-driven precision farming detects plant diseases early, controls pests, and identifies nutrient deficiencies to improve farm productivity.
Detect Unwanted Plants
Boost yields with custom training data—powering agricultural robots to detect and remove weeds effectively.
Crop Feeding & Harvesting
Use AI models trained on our data to automate harvesting and forecast optimal harvest windows based on irrigation patterns and nutrient schedules.
Count on Us for Agritech AI Data
Coral Mountain Data provides high-quality training data to power AI solutions in agriculture, from crop health monitoring and livestock management to plant fructification detection and beyond. Our AI data practices follow a strong ethical framework, ensuring GDPR and CCPA compliance, certification standards, fair pay, and a commitment to diversity and inclusion.
