Play 58
Digital Twin Agent
Very High✅ Ready
Physical system simulation with predictive modeling and anomaly detection.
AI-powered digital twin platform for physical system simulation, predictive modeling, and real-time anomaly detection. Integrates Azure IoT Hub telemetry with Azure Digital Twins for state management and OpenAI agents for natural language scenario testing. Covers manufacturing, energy, and infrastructure domains with optimization recommendations and what-if analysis.
Architecture Pattern
IoT-driven digital twin: AI agent overlay for predictive analysis and optimization
Azure Services
Azure IoT HubAzure Digital TwinsAzure OpenAIAzure FunctionsCosmos DB
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — Digital Twin Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (225 lines), evaluate (125 lines), tune (160 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with ADT URL + OpenAI key inputs + envFile
TuneKit (AI Config)
- config/openai.json — anomaly detection, prediction config
- config/guardrails.json — alert thresholds, simulation bounds
- evaluation/eval.py — Prediction accuracy >85%, Anomaly F1 >0.80
Tuning Parameters
Anomaly detection sensitivityPrediction horizon hoursSimulation fidelity levelTelemetry sampling rateOptimization convergence threshold
Estimated Cost
Dev/Test
$100–160/mo
Production
$3K–8K/mo