# Accident Sample

Accident hazards including industrial incidents, transportation accidents, explosions, fires, and other non-intentional events detected by AI for Humanity, PDC Global's generative AI and NLP technology. These hazards track significant accidents worldwide, providing casualty data, severity scoring, and geographic context for each event.

## Accident-Specific Properties

### Incident Data

The `incident.properties` object for accident hazards contains data from AI for Humanity. These properties describe the nature of the accident, its casualties, severity, and geographic scope.

**Key incident properties for accident hazards include:**

* `Incident_Type` - Type of incident (e.g., "Accident")
* `Total_Fatalities` / `Total_Wounded` - Total casualty counts
* `Civilian_Fatalities` / `Civilian_Wounded` - Civilian casualty counts
* `Police_Military_Fatalities` / `Police_Military_Wounded` - Security force casualty counts
* `Terrorist_Insurgent_Fatalities` / `Terrorist_Insurgent_Wounded` - Insurgent casualty counts (typically 0 for accidents)
* `Incident_Score` - Overall incident severity score
* `Casualty_Weight` / `Scope_Weight` / `Incident_Type_Weight` / `Total_Weight` - Scoring components used to determine hazard priority
* `Incident_Severity` - Severity classification ("H" for high, "M" for medium, "L" for low)
* `Scope_of_Incident` - Geographic scope (e.g., "Local", "Township", "Regional")
* `Country_Name` / `Province_District_Town` - Location details
* `Event_Summary` - AI-generated summary of the incident
* `sourceName` / `Source` - News source that reported the event
* `sourceResourceLocations` - JSON array of source article URLs
* `casualties` - JSON string with killed/injured breakdown
* `bufferSize` - Buffer distance in meters for exposure geometry (e.g., 2000 for local accidents)
* `rawMessage` - Full text of the source news article

### Features

Geopolitical hazards include features with `featureType` values of:

* **INCIDENT**: Point geometry at the incident location with casualty and event details
* **SMART\_ALERT**: Alert boundary polygon defining the hazard alert area

### Exposure Areas

Accident hazards use 3 exposure levels based on distance buffers:

* **Level 1**: Moderate exposure (1-2km buffer)
* **Level 2**: Strong exposure (0.5-1km buffer)
* **Level 3**: Severe exposure (0-0.5km buffer)

The buffer size is determined by the `bufferSize` property in the incident (in meters). For accident hazards, this is typically 2,000 meters (2km), reflecting the localized impact zone of industrial and transportation incidents. Note that the buffer size varies depending on the scale of the accident.

## Sample Response

```json
{
  "name": [
    {
      "locale": "en",
      "value": "Accident (Industrial Incident) - Mandya, Karnataka, India"
    }
  ],
  "description": [
    {
      "locale": "en",
      "value": "An accident was reported in Mandya, Karnataka, India on February 15, 2026.  Preliminary reports indicate 5 total victims comprised of 2 fatalities and 3 wounded.\n\nEvent Summary*:\n\u2022 Accident (Industrial Incident) has been reported in Mandya, Karnataka, India.\n\u2022 Reports indicate that at least 5 people have been affected: 2 fat..."
    }
  ],
  "severity": "INFORMATION",
  "category": "EVENT",
  "incident": {
    "uuid": "4017ef97-86c4-46b9-8211-738e0e3572e7",
    "type": "ACCIDENT",
    "sourceId": 2000,
    "sourceRecordId": "7f73298f-3090-4434-ad1a-e7797aa90007",
    "properties": {
      "Terrorist_Insurgent_Fatalities": 0,
      "Total_Wounded": 3,
      "Civilian_Fatalities": 0,
      "type": "ACTUAL",
      "Incident_Type": "Accident",
      "reportDate": "2026-02-15T14:56:37Z",
      "Incident_Type_Weight": 1,
      "action": "NEW_EVENT",
      "Terrorist_Insurgent_Wounded": 0,
      "Incident_Duration": 1,
      "Created_Time": "2026-02-15T17:41:28Z",
      "casualties": "{\"killed\":{\"total\":2},\"injured\":{\"total\":3}}",
      "scopeOfIncident": "Local",
      "name": "Accident (Industrial Incident) - Mandya, Karnataka, India",
      "Police_Military_Wounded": 0,
      "status": "NEW",
      "eventDate": "2026-02-15T12:00:00Z",
      "roles": "PUBLIC",
      "locationDescription": "Mandya, Karnataka, India",
      "Incident_Score": 41.0,
      "sourceResourceLocations": "[...]",
      "Civilian_Wounded": 0,
      "Event_Summary": "\u2022 Accident (Industrial Incident) has been reported in Mandya, Karnataka, India...",
      "Scope_Weight": 1,
      "rawMessage": "[news article text truncated for brevity]",
      "Source": "lokmattimes.com",
      "Incident_Severity": "H",
      "featureType": "INCIDENT",
      "Casualty_Weight": 40.0,
      "event": "Accident",
      "Country_Name": "India",
      "Total_Weight": 41.0,
      "Province_District_Town": "Mandya, Karnataka",
      "Total_Fatalities": 2,
      "Scope_of_Incident": "Local",
      "Police_Military_Fatalities": 0,
      "sourceName": "lokmattimes.com",
      "bufferSize": 2000,
      "..."
    }
  },
  "uuid": "51752a6e-a5d5-4fa6-ab40-55ab096065f0",
  "comment": null,
  "createdAt": 1771177307,
  "relatedHazards": [],
  "longitude": 76.89515,
  "latitude": 12.52182,
  "version": 2,
  "alertGeometry": {
    "type": "FeatureCollection",
    "features": [
      {
        "type": "Feature",
        "geometry": {
          "type": "Polygon",
          "coordinates": [...]
        },
        "properties": null
      }
    ]
  },
  "features": {
    "features": [
      {
        "id": null,
        "type": "Feature",
        "properties": {
          "severity": "LIMITED",
          "featureType": "INCIDENT",
          "name": "Accident (Industrial Incident) - Mandya, Karnataka, India",
          "casualties": {
            "killed": { "total": 2 },
            "injured": { "total": 3 }
          },
          "scopeOfIncident": "Local",
          "locationDescription": "Mandya, Karnataka, India",
          "..."
        },
        "geometry": {
          "coordinates": [76.89515, 12.52182],
          "type": "Point"
        }
      },
      {
        "id": null,
        "type": "Feature",
        "properties": {
          "severity": "LIMITED",
          "featureType": "SMART_ALERT"
        },
        "geometry": {
          "coordinates": [...],
          "type": "Polygon"
        }
      }
    ],
    "type": "FeatureCollection"
  },
  "exposureAreas": {
    "features": [
      {
        "id": "1",
        "type": "Feature",
        "properties": {
          "exposureLevel": 1
        },
        "geometry": {
          "type": "Polygon",
          "coordinates": [...]
        },
        "sourceId": null
      },
      {
        "id": "2",
        "type": "Feature",
        "properties": {
          "exposureLevel": 2
        },
        "geometry": {
          "type": "Polygon",
          "coordinates": [...]
        },
        "sourceId": null
      },
      {
        "id": "3",
        "type": "Feature",
        "properties": {
          "exposureLevel": 3
        },
        "geometry": {
          "type": "Polygon",
          "coordinates": [...]
        },
        "sourceId": null
      }
    ],
    "type": "FeatureCollection"
  },
  "exposureAssessment": {
    "population": 43000.0,
    "capital": 901007800.0,
    "exposureLevels": [
      {
        "level": "1",
        "data": {
          "population": 30400.0,
          "capital": 901007800.0,
          "foodNeedsUnit": "CAL",
          "foodNeeds": 13965000.0,
          "waterNeedsUnit": "liter",
          "waterNeeds": 19950.0,
          "wasteNeedsUnit": "100 liter",
          "wasteNeeds": 665.0,
          "shelterNeedsUnit": "sq meters",
          "shelterNeeds": 22942.5
        },
        "exposureDescription": "Moderate (1-2km)"
      },
      {
        "level": "2",
        "data": {
          "population": 9650.0,
          "capital": 0.0,
          "foodNeedsUnit": "CAL",
          "foodNeeds": 4431000.0,
          "waterNeedsUnit": "liter",
          "waterNeeds": 6330.0,
          "wasteNeedsUnit": "100 liter",
          "wasteNeeds": 211.0,
          "shelterNeedsUnit": "sq meters",
          "shelterNeeds": 7279.5
        },
        "exposureDescription": "Strong (0.5-1km)"
      },
      {
        "level": "3",
        "data": {
          "population": 2950.0,
          "capital": 0.0,
          "foodNeedsUnit": "CAL",
          "foodNeeds": 1356600.0,
          "waterNeedsUnit": "liter",
          "waterNeeds": 1938.0,
          "wasteNeedsUnit": "100 liter",
          "wasteNeeds": 64.6,
          "shelterNeedsUnit": "sq meters",
          "shelterNeeds": 2228.7
        },
        "exposureDescription": "Severe (0-0.5km)"
      }
    ],
    "hazardUuid": "",
    "hazardType": "",
    "version": "",
    "timestamp": "1771177298070",
    "exposureDescription": "",
    "foodNeedsUnit": "CAL",
    "foodNeeds": 19761000.0,
    "waterNeedsUnit": "liter",
    "waterNeeds": 28230.0,
    "wasteNeedsUnit": "100 liter",
    "wasteNeeds": 941.0,
    "shelterNeedsUnit": "sq meters",
    "shelterNeeds": 32464.5
  },
  "type": "ACCIDENT",
  "creator": "RICHTER",
  "source": {
    "id": 2000,
    "name": "AI for Humanity",
    "longName": "AI for Humanity",
    "description": "TBD",
    "url": "https://www.pdc.org/artificial-intelligence/",
    "..."
  },
  "startedAt": 1771156800,
  "updatedAt": 1771177297,
  "endedAt": 1771329600
}
```

{% hint style="info" %}
Note: Coordinate arrays have been replaced with `[...]` for brevity. In actual API responses, these properties contain complete GeoJSON coordinate arrays. Additionally, `incident.properties`, `source`, and feature details have been truncated with `"..."` to show only key fields.
{% endhint %}


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