STRATUM PROTOCOL is a production-grade, sovereign-ready AI platform for real-time urban decision intelligence, infrastructure resilience modeling, and cascading failure prediction at national scale.
A multi-layer AI infrastructure platform capable of:
- Real-time Multi-Source Urban Data Ingestion - Streaming telemetry from IoT, traffic, weather, social
- Cross-Domain Infrastructure Dependency Modeling - Multi-layer graph representation
- Cascading Failure Prediction - GNN-based stress propagation simulation
- Citizen Behavior Simulation - Agent-based evacuation & mobility modeling
- Economic Impact Modeling - GDP, ROI, insurance risk quantification
- Autonomous Policy Simulation - Monte Carlo optimization with multi-objective tradeoffs
- Cryptographically Verifiable Urban Decision Ledger - Immutable AI decision records
- Federated Cross-City Learning - Privacy-preserving global intelligence
- Sovereign AI Governance & Compliance - Explainability, bias detection, audit trails
- Cyber-Physical Defense Modeling - Adversarial attack cascade simulation
- Autonomous Infrastructure Orchestration - Traffic, energy, emergency dispatch optimization
- Long-Term Urban Evolution Forecasting - 5-30 year climate & infrastructure stress projection
- Immersive Digital Twin Visualization - 3D real-time stress heatmaps & VR-ready interface
Microservices Architecture | Event-Driven | Zero-Trust Security | Multi-Cloud Deployable
| Module | Purpose | Tech Stack |
|---|---|---|
| Data Ingestion Service | Real-time streaming, edge ingestion, validation | Kafka, TimescaleDB, FastAPI |
| Urban Knowledge Graph Service | Multi-layer infrastructure graph | Neo4j, PyTorch Geometric |
| State Estimation Engine | Bayesian inference, stress scoring | PyTorch, Ray |
| Cascading Failure Simulation | Multi-hop failure propagation | GNN, RL, Monte Carlo |
| Citizen Behavior Simulation | Agent-based modeling | Mesa, Ray RLlib |
| Policy Simulation & Optimization | Multi-objective optimization | Optuna, NSGA-II |
| Economic Intelligence Engine | GDP impact, ROI, risk scoring | Pandas, NumPy, SciPy |
| Urban Decision Ledger | Cryptographic audit trail | PostgreSQL, Merkle Trees |
| Federated Intelligence Module | Privacy-preserving learning | Flower, PySyft |
| Sovereign AI Governance | Explainability, bias detection | SHAP, Fairlearn |
| Cyber-Physical Defense | Adversarial detection | PyTorch, ART |
| Autonomous Orchestration | Infrastructure action engine | FastAPI, Redis |
| Long-Term Evolution Simulator | 5-30 year forecasting | Prophet, ARIMA, LSTM |
| Digital Twin Visualization | 3D city interface | React, Three.js, Deck.gl |
| Self-Learning Adaptive Engine | Continuous improvement | MLflow, Ray Tune |
┌─────────────────────────────────────────────────────────────────────┐
│ STRATUM PROTOCOL PLATFORM │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ IoT Data │───▶│ Ingestion │───▶│ Knowledge │ │
│ │ Streams │ │ Service │ │ Graph │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │ │ │
│ ▼ ▼ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ State Estimation & Risk Scoring │ │
│ └──────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───────────────┼───────────────┐ │
│ ▼ ▼ ▼ │
│ ┌────────────────┐ ┌────────────┐ ┌─────────────────┐ │
│ │ Cascading │ │ Citizen │ │ Policy │ │
│ │ Failure │ │ Behavior │ │ Simulation │ │
│ │ Simulation │ │ Simulation │ │ & Optimization │ │
│ └────────────────┘ └────────────┘ └─────────────────┘ │
│ │ │ │ │
│ └───────────────┼───────────────┘ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ Urban Decision Ledger (Immutable) │ │
│ └──────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───────────────┼───────────────┐ │
│ ▼ ▼ ▼ │
│ ┌────────────────┐ ┌────────────┐ ┌─────────────────┐ │
│ │ Federated │ │ Sovereign │ │ Cyber-Physical │ │
│ │ Intelligence │ │ AI │ │ Defense │ │
│ │ Module │ │ Governance │ │ Engine │ │
│ └────────────────┘ └────────────┘ └─────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ Autonomous Infrastructure Orchestration │ │
│ └──────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───────────────┼───────────────┐ │
│ ▼ ▼ ▼ │
│ ┌────────────────┐ ┌────────────┐ ┌─────────────────┐ │
│ │ Long-Term │ │ Digital │ │ Self-Learning │ │
│ │ Evolution │ │ Twin │ │ Adaptive │ │
│ │ Simulator │ │Visualization│ │ Engine │ │
│ └────────────────┘ └────────────┘ └─────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────┘
- Docker 24.0+ (Docker Desktop for macOS)
- Kubernetes 1.28+ (Enable in Docker Desktop Settings)
- Python 3.11+
- Node.js 20+
- 8GB RAM minimum (32GB recommended)
- 20GB free disk space
- NVIDIA GPU (optional, for accelerated training)
1. Start Docker Desktop:
# Open Docker Desktop application
open /Applications/Docker.app
# Wait for green indicator in menu bar
# Verify Docker is running:
docker ps2. Enable Kubernetes in Docker Desktop:
- Open Docker Desktop Settings (⚙️)
- Go to Kubernetes tab
- Check ☑️ Enable Kubernetes
- Click Apply & Restart
- Wait 2-3 minutes for Kubernetes to start
- Verify:
kubectl cluster-info
# Clone repository
git clone https://github.com/your-org/stratum-protocol.git
cd stratum-protocol
# Copy environment configuration
cp .env.example .env
# Start infrastructure services (databases, Kafka, etc.)
docker-compose -f infrastructure/docker-compose.yml up -d
# Wait 30 seconds for databases to initialize
sleep 30
# Create Kubernetes namespace and secrets
kubectl create namespace stratum-protocol
kubectl create secret generic stratum-secrets \
--from-env-file=.env \
--namespace=stratum-protocol
# Deploy to Kubernetes
kubectl apply -f k8s/config/
kubectl apply -f k8s/databases/
kubectl apply -f k8s/services/
kubectl apply -f k8s/monitoring/
kubectl apply -f k8s/ingress/
# Wait for pods to be ready (2-3 minutes)
kubectl get pods -n stratum-protocol -w
# Port forward frontend (in new terminal)
kubectl port-forward svc/frontend 3000:3000 -n stratum-protocol
# Access platform
open http://localhost:3000# Deploy everything automatically
./scripts/deploy.sh productionIf you see errors like:
- "Cannot connect to Docker daemon" → Start Docker Desktop
- "connection refused localhost:8080" → Enable Kubernetes in Docker Desktop
- "Services not responding" → Wait longer or check pod status
See detailed troubleshooting: TROUBLESHOOTING.md
See step-by-step guide: QUICKSTART.md
# Copy environment template
cp .env.example .env
# Configure secrets
kubectl create secret generic stratum-secrets \
--from-env-file=.env \
--namespace=stratum-protocolstratum-protocol/
├── services/ # Microservices
│ ├── data-ingestion/ # Real-time data streaming
│ ├── knowledge-graph/ # Urban graph database
│ ├── state-estimation/ # Bayesian inference
│ ├── cascading-failure/ # Failure simulation
│ ├── citizen-behavior/ # Agent-based modeling
│ ├── policy-simulation/ # Optimization engine
│ ├── economic-intelligence/ # GDP & ROI modeling
│ ├── decision-ledger/ # Cryptographic audit trail
│ ├── federated-intelligence/ # Privacy-preserving learning
│ ├── sovereign-governance/ # AI compliance & explainability
│ ├── cyber-defense/ # Adversarial detection
│ ├── autonomous-orchestration/ # Infrastructure control
│ ├── evolution-simulator/ # Long-term forecasting
│ ├── digital-twin/ # 3D visualization
│ └── adaptive-engine/ # Self-learning loop
├── shared/ # Shared libraries
│ ├── auth/ # Authentication & authorization
│ ├── messaging/ # Event bus abstraction
│ ├── monitoring/ # Observability
│ └── models/ # Shared data models
├── infrastructure/ # Infrastructure as code
│ ├── docker-compose.yml # Local development
│ ├── terraform/ # Cloud provisioning
│ └── helm/ # Kubernetes charts
├── k8s/ # Kubernetes manifests
│ ├── services/ # Service deployments
│ ├── config/ # ConfigMaps & Secrets
│ └── ingress/ # API Gateway
├── frontend/ # React dashboard
│ ├── src/
│ │ ├── components/
│ │ ├── visualizations/ # Three.js 3D views
│ │ └── dashboard/
│ └── public/
├── docs/ # Documentation
│ ├── architecture/ # System design
│ ├── api/ # API specifications
│ ├── deployment/ # Deployment guides
│ └── security/ # Security architecture
├── scripts/ # Automation scripts
│ ├── deploy.sh # Deployment automation
│ ├── test.sh # Integration tests
│ └── migrate.sh # Database migrations
├── tests/ # Integration tests
│ ├── e2e/ # End-to-end tests
│ └── load/ # Load testing
└── .github/ # CI/CD workflows
└── workflows/
- Zero-Trust Network: All inter-service communication encrypted (mTLS)
- RBAC: Role-based access control with fine-grained permissions
- OAuth2 + JWT: Secure authentication and authorization
- Data Encryption: At-rest (AES-256) and in-transit (TLS 1.3)
- Audit Logging: Comprehensive audit trails in Decision Ledger
- Vulnerability Scanning: Automated container scanning in CI/CD
- Secrets Management: Kubernetes secrets + HashiCorp Vault integration
All services expose REST + gRPC APIs with OpenAPI 3.0 specifications.
Core Endpoints:
POST /api/v1/ingest/stream- Real-time data ingestionGET /api/v1/graph/infrastructure- Query knowledge graphPOST /api/v1/simulate/cascade- Run failure simulationPOST /api/v1/policy/optimize- Policy optimizationGET /api/v1/ledger/decisions- Query decision historyPOST /api/v1/orchestrate/action- Execute infrastructure actionGET /api/v1/twin/visualization- Digital twin state
# Unit tests
pytest services/*/tests/
# Integration tests
pytest tests/integration/
# Load testing
locust -f tests/load/locustfile.py
# End-to-end tests
npm run test:e2e- Metrics: Prometheus + Grafana dashboards
- Logging: ELK Stack (Elasticsearch, Logstash, Kibana)
- Tracing: Jaeger distributed tracing
- Alerting: PagerDuty integration
- Health Checks: Kubernetes liveness/readiness probes
Supports deployment on:
- AWS: EKS, RDS, S3, CloudWatch
- Azure: AKS, Cosmos DB, Blob Storage
- GCP: GKE, Cloud SQL, Cloud Storage
- On-Premises: OpenStack, VMware
- ✅ Core data ingestion pipeline
- ✅ Knowledge graph infrastructure
- ✅ Basic cascading failure simulation
- ✅ Decision ledger implementation
- ✅ Initial digital twin visualization
- 🔄 Advanced citizen behavior modeling
- 🔄 Multi-objective policy optimization
- 🔄 Federated learning infrastructure
- 🔄 Cyber-physical defense engine
- 🔄 Autonomous orchestration v1
- 📋 Long-term evolution forecasting
- 📋 Advanced economic impact modeling
- 📋 VR/AR digital twin interface
- 📋 Multi-city federated deployment
- 📋 Full sovereign AI governance
- 📋 National-scale deployment
- 📋 Real-time crisis response system
- 📋 Advanced self-learning capabilities
- 📋 International standards compliance
- 📋 Commercial SaaS offering
MIT License - See LICENSE for details
See CONTRIBUTING.md for development guidelines.
- Project Lead: [Your Organization]
- Email: contact@stratum-protocol.io
- Documentation: https://docs.stratum-protocol.io
- Status: https://status.stratum-protocol.io
Built for sovereign nations, resilient cities, and the future of urban intelligence.