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Volver a Proyectos

Drone GeoAnalysis

Turning drone footage into actionable intelligence

LLMs YOLOv11 Geospatial Drones Flask LangGraph

Arquitectura

Natural Language -> LLM Mission Planner -> GPS Waypoints + Actions -> Drone Execution -> Video Feed -> YOLO Detection -> Geo Correlation -> Change Detection

Descripcion

The operator describes a mission in natural language. The LLM (Groq/Llama or OpenAI) generates GPS waypoints, altitudes, actions, and safety constraints. The drone executes the mission while streaming video processed by YOLO for real-time object detection and geographic change analysis.

Features: Mission Control with satellite map (Mapbox) and real-time telemetry, YOLOv11 object detection on drone imagery, geographic triangulation and correlation, 52 planned ISR operations, Parrot ANAFI full drone control via Olympe SDK, multi-LLM support (Groq, OpenAI, Docker local), GeoJSON cartography with POIs and security boundaries, LangGraph ReAct agent for querying analysis results.

107 tests with 95.3% success rate. Clean layered architecture: controllers, services, models, hardware abstraction. Factory pattern, Flask blueprints, rate limiting, CORS.

Stack Tecnologico

Capa Tecnologia
Backend Flask + Waitress (production WSGI)
LLM Groq (Llama 4 Scout) / OpenAI / Docker Model Runner
Object Detection YOLOv11 (Ultralytics 8.3) + PyTorch 2.5
Drone SDK Parrot Olympe 7.7.5 (ANAFI)
Maps Leaflet + Mapbox (satellite tiles)
Agent LangGraph ReAct (mission planning + Q&A)
Geo GeoJSON, triangulation, correlation
Deploy Docker Compose (4GB limit, health checks)

Video Demo