🚒 Arcadia · Emergency Dispatch System

Real-time geospatial dispatch system for emergency units Built for firefighters, ambulances, and police — low latency, high availability, event-driven.

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🌐 Live Demo

Service	URL
Frontend Dashboard	https://arcadia-dispatch-f1cb589rz-kelvinw918s-projects.vercel.app
Backend API	https://arcadia-backend-bj5m.onrender.com
API Health	https://arcadia-backend-bj5m.onrender.com/api/health
API Analytics	https://arcadia-backend-bj5m.onrender.com/api/analytics
API Units	https://arcadia-backend-bj5m.onrender.com/api/units

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🎯 Problem & Solution

Emergency dispatch systems in many regions still rely on radio or manual coordination. Arcadia solves this by:

• 📡 Real-time telemetry from field units (GPS coordinates, status, ETA)
• 🗺️ Geospatial analytics for optimal unit assignment (closest, fastest route)
• 🔄 Event-driven architecture for horizontal scalability
• 📊 Live visualization via interactive map interface

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🛠 Tech Stack

Layer	Technology	Purpose
Producer	Python + aiokafka	Simulates unit telemetry events
Streaming	Redpanda (Kafka-compatible)	Event bus, high throughput ingestion
Orchestrator	Python + H3 + PostGIS	AI-driven unit assignment
Backend API	Go + pgxpool	High-performance API, geospatial processing
Database	PostgreSQL + PostGIS	Spatial queries, centroids, distances
Frontend	Leaflet.js + Tailwind CSS	Real-time map rendering
Orchestration	Docker Compose	Multi-service local development
Deployment	Render + Vercel	Cloud-native hosting

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🏗️ Architecture

┌─────────────────┐ ┌──────────────┐ ┌─────────────────┐ ┌──────────────┐ │ Stress Producer │────▶│ Redpanda │────▶│ Orchestrator │────▶│ Redpanda │ │ (Python) │ │ (Topic: │ │ (Python) │ │ (Topic: │ │ Generates │ │ raw- │ │ - Triage │ │ dispatched- │ │ incidents │ │ incidents) │ │ - H3 Asign. │ │ orders) │ └─────────────────┘ └──────────────┘ └─────────────────┘ └──────┬───────┘ │ ▼ ┌─────────────────┐ ┌──────────────┐ ┌─────────────────┐ ┌──────────────┐ │ Frontend │────▶│ Backend │◀────│ Persistence │────▶│ PostgreSQL │ │ (Leaflet) │ │ Go │ │ Worker │ │ + PostGIS │ │ Map & Stats │ │ API REST │ │ (Python) │ │ Database │ └─────────────────┘ └──────────────┘ └─────────────────┘ └──────────────┘

Data Flow:

1. Stress Producer generates simulated emergency incidents
2. Redpanda streams events to the orchestrator
3. Orchestrator processes with H3 geospatial indexing and assigns units
4. Persistence Worker saves dispatched orders to PostgreSQL
5. Go Backend exposes data via REST API
6. Frontend visualizes units and analytics in real-time

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🚀 Quick Start

Prerequisites

• Docker Desktop
• Go 1.21+
• Python 3.11+
• PostgreSQL 16+ with PostGIS

Run it (5 minutes)

# 1. Clone
git clone [https://github.com/KelvinW918/arcadia-dispatch.git](https://github.com/KelvinW918/arcadia-dispatch.git)
cd arcadia-dispatch

# 2. Start infrastructure (Postgres + Redpanda)
docker-compose up -d

# 3. Run migrations
python init_timescale.py

# 4. Run backend
cd backend-go
go run main.go

# 5. Run orchestrator (in another terminal)
cd ..
python agent_orchestrator.py

# 6. Run persistence worker (in another terminal)
python persistence_worker.py

# 7. Run stress producer (in another terminal)
python stress_producer.py

# 8. Open frontend
# Open frontend/index.html in your browser or use Live Server

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## 📊 Sample Queries (PostGIS)

-- Find nearest unit to an incident (within 5km)
SELECT unit_id, coordinates, status,
       ST_Distance(coordinates, ST_SetSRID(ST_MakePoint(-66.9, 10.5), 4326)) as distance
FROM units
WHERE ST_DWithin(coordinates, ST_SetSRID(ST_MakePoint(-66.9, 10.5), 4326), 5000)
ORDER BY distance ASC
LIMIT 1;

-- Cluster active units by sector
SELECT ST_ClusterKMeans(coordinates, 4) as cluster_id,
       COUNT(*) as units_count
FROM units

-- Get unit analytics
SELECT 
    assigned_resource_id,
    COUNT(*) as total_despachos,
    ROUND(AVG(eta_minutes)::numeric, 2) as eta_promedio,
    ST_AsText(ST_Centroid(ST_Collect(route_geom))) as centroide
FROM dispatched_orders_history
GROUP BY assigned_resource_id;
WHERE status = 'active'
GROUP BY cluster_id;

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## 📈 Performance Characteristics
Metric              	                 Value
Event throughput	       ~10,000 events/sec (Redpanda)
API latency (p95)	       < 50ms
Spatial query time	       < 10ms (with PostGIS indexing)
Concurrent units supported	5,000+
ETA calculation	       < 5ms per unit

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## 🔮 Roadmap
- WebSocket support for real-time frontend updates
-Route calculation using pgRouting
-Historical trip replay & analytics
-Mobile app for field units
-Kafka Streams for real-time ETA prediction
-Ollama/LLM integration for semantic triage
-Multi-region deployment support

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## 👤 Author
Kelvin W.
Systems Engineer · Product Architect

https://img.shields.io/badge/GitHub-KelvinW918-181717?style=for-the-badge&logo=github
https://img.shields.io/badge/LinkedIn-KelvinW918-0077B5?style=for-the-badge&logo=linkedin

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## 📄 License
MIT — free for use, modification, and distribution.

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