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Network Optimization Agent

Very High Ready

5G/LTE capacity planning with digital twin simulation.

5G/LTE network capacity planning with AI-driven anomaly detection, self-healing automation, traffic prediction, and cell tower load balancing using digital twin simulation of network topology. IoT Hub ingests telemetry from cell towers, Stream Analytics detects anomalies in real time, OpenAI generates optimization recommendations, Digital Twins simulates network topology changes, and Cosmos DB stores network state and historical performance data.

Architecture Pattern

Network optimization pipeline: tower telemetry ingestion - anomaly detection - traffic prediction - digital twin simulation - self-healing automation

Azure Services

Azure IoT HubAzure Stream AnalyticsAzure OpenAIAzure Digital TwinsAzure Cosmos DB

DevKit (.github Agentic OS)

  • agent.md — root orchestrator with builder→reviewer→tuner handoffs
  • 3 agents — Network Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
  • 3 skills — deploy (214 lines), evaluate (105 lines), tune (271 lines)
  • 4 prompts — /deploy, /test, /review, /evaluate with agent routing
  • .vscode/mcp.json — FrootAI MCP with OpenAI + IoT Hub inputs + envFile

TuneKit (AI Config)

  • config/openai.json - network analysis and optimization prompts
  • config/network.json - prediction horizons, anomaly sensitivity, healing triggers
  • config/guardrails.json - latency thresholds, coverage minimums
  • evaluation/eval.py - Prediction accuracy >90%, Self-healing success >95%

Tuning Parameters

Traffic prediction horizonAnomaly detection sensitivitySelf-healing trigger rulesLoad balancing weightsCapacity planning window

Estimated Cost

Dev/Test

$150-350/mo

Production

$5K-15K/mo