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Heimdall

Heimdall is an open-source platform for real-time localization of radio sources on amateur bands (2m/70cm), leveraging data from geographically distributed WebSDR receivers. The project uses microservices architecture (Python, RabbitMQ, PostgreSQL/TimescaleDB, Kubernetes) with ML-based triangulation and uncertainty estimation.

Install / Use

/learn @fulgidus/Heimdall
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

🎯 Heimdall - Real-Time Radio Source Localization

AI-powered platform for locating radio transmissions using distributed WebSDR receivers.

heimdall.png

License: CC Non-Commercial Status: In Development Community: Amateur Radio

CI Tests Python Quality TypeScript Quality Security Scan E2E Tests Integration Tests

Coverage


⚡ Quick Facts

  • Accuracy: ±30m (68% confidence)
  • Latency: <500ms processing
  • Network: 7 distributed WebSDR receivers (Italian 2m/70cm bands)
  • Status: Phase 7 in progress (Frontend development)

🚀 Quick Start (5 minutes)

# Clone repository
git clone https://github.com/fulgidus/heimdall.git
cd heimdall

# Configure environment
cp .env.example .env

# Start all services (Docker required)
docker-compose up -d

# Verify health
make health-check

Done! Open http://localhost:3000

Full Installation Guide


🏗️ Architecture

| Component | Technology | Purpose | | ------------------ | --------------------------- | -------------------- | | Backend | Python (FastAPI + Celery) | Microservices | | ML Pipeline | PyTorch Lightning + MLflow | Training & Inference | | Frontend | React + TypeScript + Mapbox | Web UI | | Storage | PostgreSQL + TimescaleDB | Time-series data | | Queue | RabbitMQ | Task orchestration | | Object Storage | MinIO (S3-compatible) | IQ data & models | | Deployment | Kubernetes + Helm | Production |

Architecture Deep-Dive


📚 Documentation

Getting Started:

Reference:

Project:

Full Documentation Index


📊 Development Status

Phase Progress (6/11 complete):

Phases 0-6: Infrastructure, Services, ML Pipeline, Inference
🟡 Phase 7: Frontend (In Progress)
Phases 8-10: Kubernetes, QA, Release

Detailed Roadmap

Performance Metrics (validated in Phase 4):

  • API latency: 52ms average (P95: 52.81ms)
  • Concurrent capacity: 50 simultaneous tasks
  • Success rate: 100%
  • Container memory: 100-300MB per service

Performance Report


🌍 Use Cases

Amateur Radio:

  • DX station localization
  • Interference source tracking
  • Contest verification

Emergency Services:

  • Search and rescue beacon location
  • First responder coordination

Research:

  • Radio propagation studies
  • Spectrum management
  • Educational demonstrations

🧪 Testing

# Backend tests
make test

# Frontend tests
cd frontend && pnpm test

# E2E tests (real backend integration)
./scripts/run-e2e-tests.sh

Coverage: >80% across all services
E2E Tests: 42 tests, 100% real HTTP calls

Testing Guide


🤝 Contributing

We welcome contributions! See Contributing Guidelines for details.

Quick Steps:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes with tests
  4. Submit a pull request

Development Setup


📜 License

CC Non-Commercial - Developed by fulgidus for the amateur radio community.

See LICENSE for full details.


💬 Support


🌟 Mission

Heimdall's mission is to democratize radio source localization, making it accessible to everyone while advancing radio science and emergency communications.

We believe that radio waves belong to everyone, and everyone should have the tools to understand and explore them.


Ready to see the invisible?Start Your Journey

Related Skills

View on GitHub
GitHub Stars6
CategoryData
Updated4mo ago
Forks0

Languages

HTML

Security Score

67/100

Audited on Nov 17, 2025

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