Aerial Intelligence Labs

Real-World Vision AI Deployments

Advanced computer vision systems solving real agricultural challenges. From crop health monitoring to infrastructure inspection—production-grade solutions deployed today.

Featured Deployments

Vision AI systems in active use across agricultural and industrial sectors

Vision-Language Model Object Detection

Crop Health Monitoring

Autonomous drone system detecting disease, stress, and growth patterns. Qwen2.5-VL provides semantic understanding while YOLO26 delivers 44 FPS real-time detection.

Disease detection with 97% accuracy
Yield prediction via multimodal analysis
Automated anomaly alerts
Multi-field fleet management
Production Ready
YOLO26 SAM 2.1

Livestock Tracking

Real-time tracking system for herd management. YOLO26 NMS-free detection with SAM2's memory mechanism for occlusion handling.

43% faster CPU inference
Occlusion-aware tracking
Behavior pattern analysis
Integration with ear-tag systems
Beta Testing
VLM Reasoning Edge Detection

Wildfire Detection

Early warning system using VLM scene reasoning. Detects smoke, perimeter anomalies, and triggers alerts before fire spreads.

<2 second detection latency
Multi-sensor data fusion
Predictive fire spread modeling
Satellite+drone verification
Concept Prototype
YOLO26 Custom SAM

Infrastructure Inspection

Automated inspection for bridges, pipelines, and agricultural structures. Custom SAM prompts trained on specific infrastructure defects.

Crack and fracture detection
Structural integrity analysis
Automated reporting system
Regulatory compliance checks
Enterprise Deployment
SAM3D Cloud API

Terrain Mapping

3D terrain reconstruction from drone footage. SAM3D processes camera+LiDAR streams for elevation mapping.

Multi-modal sensor fusion
Real-time reconstruction
Precision elevation modeling
Integration with farm planning
Research Phase