Emergency Dispatch Center
- Oren Halpern
- Dec 23, 2025
- 1 min read
Excited to share the development of an innovative system for real-time rescue team management and routing, integrating advanced AI technologies with geographic mapping.
🤖 Large Language Model (LLM) Integration
The system uses Semantic Kernel and Azure OpenAI to enable natural language control over all operational aspects:
• Creating emergency incidents through textual description ("drowning people at Tel-Aviv Gordon beach")
• Automatic rescue team assignment based on capabilities and urgency
• Address-to-coordinate conversion using Azure Maps Geocoding
• Full support for Hebrew and English
🗺️ Advanced Mapping and Route Planning
• Ground Routes: Optimal routing based on OpenStreetMap road network, accounting for No-Drive zones (military areas, emergency zones)
• Aerial Routes: Flight path planning for drones and helicopters using A* and RRT* algorithms, including No-Fly zone avoidance
• 3D terrain visualization with DEM (Digital Elevation Model) layers
🎯 Core Capabilities
âś… Automatic detection and classification of emergency incidents (fires, floods, injuries)
âś… Dynamic prioritization by urgency and distance
âś… Multi-purpose rescue fleet management: ambulances, fire fighters, police, drones
âś… Real-time arrival time calculation and route visualization
âś… Color-coded snackbar notifications for status updates (green/yellow/red)
🛠️ Technology Stack
C# .NET | Blazor | Azure OpenAI | Semantic Kernel | MapLibre GL | Azure Maps | OpenStreetMap | MudBlazor
The system is built as a full web application, with a responsive user interface and RTL language support.
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