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TrafficEnvironmentImpact

Entity Description​

The TrafficEnvironmentImpact entity describes the environmental impact of traffic conditions, specifically focusing on emissions like CO2 generated by vehicles on a road segment.

JSON Structure​

A typical TrafficEnvironmentImpact entity in NGSI-LD format looks like this:

{
  "id": "urn:ngsi-ld:TrafficEnvironmentImpact:001",
  "type": "TrafficEnvironmentImpact",
  "co2": {
    "type": "Property",
    "value": 120.5
  },
  "traffic": {
    "type": "Property",
    "value": [
      {
        "vehicleClass": "car",
        "refTrafficFlowObserved": "urn:ngsi-ld:TrafficFlowObserved:Flow-01"
      }
    ]
  },
  "refRoadSegment": {
    "type": "Relationship",
    "object": "urn:ngsi-ld:RoadSegment:Segment-A"
  },
  "dateObservedFrom": {
    "type": "Property",
    "value": "2023-10-01T08:00:00Z"
  },
  "dateObservedTo": {
    "type": "Property",
    "value": "2023-10-01T09:00:00Z"
  }
}

Key Fields​

  • id: Unique identifier for the entity.
  • type: Entity type, must be TrafficEnvironmentImpact.
  • co2: The measured or calculated CO2 emission concentration.
  • traffic: A list of traffic items, detailing vehicle classes and references to traffic flow observations.
  • refRoadSegment: A relationship link to the RoadSegment where this impact is measured.
  • dateObservedFrom / dateObservedTo: The time range for the observation.

Smart Data Models​

This data model is compliant with the Smart Data Models standard. It extends the standard model to include specific relationships like refRoadSegment for better context integration.

Application​

Data Validation​

Validation via openAPI/smartmodels.yaml ensures:

  • Structure: The traffic field must be an array of objects with valid vehicleClass and references.
  • Types: co2 must be a floating-point number.

Documentation​

For developers:

  • Backend: Provides a clear schema for calculating and storing environmental impact data derived from traffic simulations or sensors.
  • Frontend: Enables the visualization of "green" vs. "polluted" routes on a map by querying impacts linked to road segments.

Uniqueness & Linked Data​

  • Uniqueness: Terms like co2 and vehicleClass are semantically defined in the JSON-LD context (fiware:co2, fiware:vehicleClass).
  • Linked Data: The refRoadSegment connects environmental data directly to the physical infrastructure. This allows the system to answer questions like "Which road segments have the highest CO2 emissions during rush hour?"

Intelligent Query Support​

  • Impact Analysis: "Find all road segments where CO2 emissions exceeded 100 units in the last hour."
  • Cross-Domain Queries: Combine traffic flow data with environmental impact to optimize traffic light timings for reduced emissions.