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Endpoint

POST /api/log
Create a maintenance log entry to record operator activities. Events are stored in InfluxDB and serve as ground-truth labels for supervised machine learning.

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Request Body

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asset_id
string
required
Asset identifier (e.g., “Motor-01”). Must be 1-100 characters.
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event_type
string
required
Maintenance event classification. Allowed values:Preventive Maintenance:
  • PREVENTIVE_LUBRICATION - Scheduled lubrication activities
  • PREVENTIVE_CLEANING - Scheduled cleaning activities
  • PREVENTIVE_INSPECTION - Scheduled inspection activities
Corrective Maintenance:
  • CORRECTIVE_BEARING_REPLACEMENT - Repair/replacement of bearings
  • CORRECTIVE_ALIGNMENT - Alignment corrections
  • CORRECTIVE_ELECTRICAL - Electrical repairs
Status Changes:
  • STATUS_CALIBRATION - System calibration events
  • STATUS_RESTART - System restart events
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severity
string
required
Event severity level. Allowed values:
  • LOW - Minor maintenance or routine activities
  • MEDIUM - Standard maintenance requiring attention
  • HIGH - Urgent repairs or significant issues
  • CRITICAL - Emergency situations requiring immediate action
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description
string
required
Human-readable description of the maintenance activity. Must be 1-1000 characters. Include relevant details such as part numbers, observations, and actions taken.
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timestamp
datetime
Event timestamp in ISO 8601 format with UTC timezone (e.g., “2026-01-31T10:30:00Z”). If not provided, defaults to the current server time. Allows backdating for historical entries.

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Response

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event_id
string
Unique identifier (UUID v4) for this log entry
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asset_id
string
Asset that was logged
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event_type
string
Type of maintenance event that was recorded
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severity
string
Severity level of the event
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timestamp
datetime
Timestamp of the event (UTC)
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message
string
Confirmation message indicating successful log creation

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Use Cases

  • Ground-Truth Labeling: Record maintenance events that can be correlated with sensor data for supervised ML training
  • Bearing Replacement Tracking: Log bearing replacements to correlate with vibration anomalies detected in sensor data
  • Lubrication Monitoring: Record lubrication events to track maintenance effectiveness over time
  • Failure Analysis: Document electrical repairs and other corrective actions for failure pattern analysis

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ML Integration

Maintenance logs stored via this endpoint can be queried alongside sensor data to:
  • Train supervised models that predict failure modes based on sensor patterns
  • Identify early warning indicators in sensor data before failures occur
  • Validate anomaly detection algorithms against real-world maintenance events
  • Build predictive maintenance models with labeled training data

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Example Request

curl -X POST "http://localhost:8000/api/log" \
  -H "Content-Type: application/json" \
  -d '{
    "asset_id": "Motor-01",
    "event_type": "CORRECTIVE_BEARING_REPLACEMENT",
    "severity": "HIGH",
    "description": "Replaced main bearing due to excessive vibration. Part #SKF-6205-2RS.",
    "timestamp": "2026-01-31T10:30:00Z"
  }'

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Example Response

{
  "event_id": "a1b2c3d4-e5f6-4a7b-8c9d-0e1f2a3b4c5d",
  "asset_id": "Motor-01",
  "event_type": "CORRECTIVE_BEARING_REPLACEMENT",
  "severity": "HIGH",
  "timestamp": "2026-01-31T10:30:00Z",
  "message": "Log entry created successfully for Motor-01"
}

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Error Responses

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422 Validation Error

Returned when the request body fails validation. 
{
  "detail": [
    {
      "loc": ["body", "event_type"],
      "msg": "Input should be 'PREVENTIVE_LUBRICATION', 'PREVENTIVE_CLEANING', 'PREVENTIVE_INSPECTION', 'CORRECTIVE_BEARING_REPLACEMENT', 'CORRECTIVE_ALIGNMENT', 'CORRECTIVE_ELECTRICAL', 'STATUS_CALIBRATION' or 'STATUS_RESTART'",
      "type": "enum"
    }
  ]
}

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500 Internal Server Error

Returned when the database write fails or an unexpected error occurs. 
{
  "detail": "Failed to persist log entry to database"
}

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