Skip to main content

resq_mcp.pdie.models

PDIE domain models for the ResQ MCP server.

annotations

datetime

Literal

BaseModel

Field

VulnerabilityMap Objects

class VulnerabilityMap(BaseModel)
Static vulnerability assessment data for a geographic sector. Part of PDIE (Predictive Disaster Intelligence Engine) system. Contains precomputed risk factors, infrastructure data, and population metrics used for predictive disaster modeling and resource allocation. Attributes:
  • sector_id - Sector identifier this map applies to.
  • population_density - Human population density category.
  • critical_infrastructure - List of critical facilities (e.g., “hospital”, “power-substation”).
  • flood_risk - Flood vulnerability score (0.0 to 1.0).
  • fire_risk - Fire vulnerability score (0.0 to 1.0).
  • last_updated - UTC timestamp of last data update (auto-generated).
Notes: Risk scores are precomputed from historical data, terrain analysis, and infrastructure density. Updated periodically via GIS integration.

sector_id

population_density

critical_infrastructure

flood_risk

fire_risk

last_updated

PreAlert Objects

class PreAlert(BaseModel)
Probabilistic disaster forecast from LSTM/GNN predictive models. Part of PDIE system. Generated by machine learning models that analyze weather patterns, sensor data, and historical trends to predict potential disasters before they occur. Enables proactive resource positioning. Attributes:
  • alert_id - Unique alert identifier (e.g., “PRE-A1B2C3D4”).
  • sector_id - Target sector for the prediction.
  • predicted_disaster_type - Expected disaster type (e.g., “wildfire”, “flood”).
  • probability - Forecast confidence (0.0 to 1.0).
  • forecast_horizon_hours - Time until predicted event (hours from now).
  • vulnerability_context - Associated sector vulnerability data.
  • generated_at - UTC timestamp of forecast generation (auto-generated).
Example:
alert = PreAlert( … alert_id=“PRE-123ABC”, … sector_id=“Sector-1”, … predicted_disaster_type=“wildfire”, … probability=0.85, … forecast_horizon_hours=12, … vulnerability_context=vuln_map … )

alert_id

sector_id

predicted_disaster_type

probability

forecast_horizon_hours

vulnerability_context

generated_at