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resq_mcp.dtsop.models

DTSOP domain models for the ResQ MCP server.

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annotations

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Literal

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BaseModel

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SimulationRequest Objects

class SimulationRequest(BaseModel)
Request for high-fidelity physics simulation in digital twin. Part of DTSOP system. Triggers physics-based simulation in Unity/Unreal Engine for accurate disaster propagation modeling and strategy validation. Attributes:
  • scenario_id - Unique scenario identifier for this simulation.
  • sector_id - Geographic sector to simulate.
  • disaster_type - Type of disaster to model (e.g., “flood”, “wildfire”).
  • parameters - Simulation parameters (e.g., {“wind_speed”: 15.5, “water_level”: 2.3}).
  • priority - Processing priority (standard queued, urgent fast-tracked).
Notes: Simulations run asynchronously. Monitor progress via the returned simulation ID and resource subscription (resq://simulations/{id}).

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scenario_id

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sector_id

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disaster_type

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parameters

e.g., wind_speed, water_level

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priority

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OptimizationStrategy Objects

class OptimizationStrategy(BaseModel)
Reinforcement learning-optimized deployment and evacuation strategy. Part of DTSOP system. Generated by RL agents trained on thousands of simulated disaster scenarios to optimize resource allocation and evacuation routing under various constraints. Attributes:
  • strategy_id - Unique strategy identifier (e.g., “STRAT-X1Y2Z3W4”).
  • related_alert_id - Pre-alert or incident ID this strategy addresses.
  • recommended_deployment - Mapping of drone types to recommended counts (e.g., {“surveillance”: 2, “payload”: 1}).
  • evacuation_routes - Ordered list of recommended evacuation routes.
  • estimated_success_rate - Predicted success probability (0.0 to 1.0) based on simulation outcomes.
  • simulation_proof_url - NeoFS/IPFS URL for simulation evidence and logs.
Notes: Success rate derived from Monte Carlo simulations across varying disaster intensities and communication scenarios.

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strategy_id

drone_type -> count

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evacuation_routes

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estimated_success_rate

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simulation_proof_url