Connected Vehicle Sensor Health Logs

This dataset provides detailed, time-stamped health logs for IoT sensors installed in connected vehicles, including operational status, error codes, anomaly detection, maintenance history, and location data. It enables fleet managers and smart city operators to monitor sensor reliability, schedule maintenance, and detect issues proactively, improving transportation safety and efficiency.

  • last updated 8 Jan 2026
  • by GoMask
The brief that made it

Proactive sensor maintenance scheduling for fleet vehicles

Sample rows

preview · 8 of 120 rows · all 24 columns
log_idstringstatusstringuptime_secondsintegeranomaly_detectedbooleanfleet_idstringvehicle_idstringsensor_idstringsensor_typestringsensor_locationstringtimestampdatetimeerror_codestringerror_descriptionstringlast_maintenance_datedatenext_maintenance_duedateanomaly_typestringsensor_firmware_versionstringvehicle_makestringvehicle_modelstringvehicle_yearintegercitystringstatestringcountrystringlatitudefloatlongitudefloat
LOG-1A2B3C4Doperational1263000falseFL-BlueSkyVH-A1234SEN-GPS-0001GPSdashboard2024-04-15T09:22:11Zblankblank2024-01-152024-10-15nonev1.4.2FordExplorer2020San FranciscoCAUSA37.7749-122.4194
LOG-9E8F7G6Hdegraded864000trueFL-RedLineVH-B5678SEN-CAM-0022camerawindshield2024-05-02T17:45:33ZCAM-DRIFTCamera calibration drift detected.2024-02-052024-08-05hardware_faultv2.1.1-betaToyotaHighlander2019HoustonTXUSA29.7604-95.3698
LOG-4J5K6L7Moperational1485900falseblankVH-C9012SEN-ACC-0010accelerometercentral console2024-03-18T11:12:59Zblankblank2023-12-182024-09-18nonev3.0.0BMWX52022MunichBavariaGermany48.135111.582
LOG-8N9O0P1Qoperational1536000falseblankVH-D3456SEN-TEMP-0007temperaturerear cabin2024-02-11T13:59:44Zblankblank2023-11-112024-08-11nonev1.0.0-hotfixHondaPilot2021SydneyNSWAustralia-33.8688151.2093
LOG-2R3S4T5Uoffline0trueFL-EdgeCasesVH-E7890SEN-HUM-0033humiditytrunk2024-06-07T21:05:22ZHUM-OFFLINESensor not responding.2024-03-072024-12-07communication_failurev2.3.4MazdaCX-52023Cape TownWestern CapeSouth Africa-33.924918.4241
LOG-6V7W8X9Yoperational2115000falseblankVH-F2345SEN-PRS-0044pressurefront left tire2024-01-29T07:36:15Zblankblank2023-10-292024-07-29nonev2.2.2MercedesGLC2018LondonEnglandUK51.5074-0.1278
LOG-0Z1A2B3Cmaintenance5000falseFL-BlueSkyVH-G6789SEN-GPS-0045GPSroof2024-03-04T14:51:10ZMNT-GPS-CHKScheduled GPS check.2024-03-042024-09-04nonev2.5.1ChevroletTahoe2021Los AngelesCAUSA34.0522-118.2437
LOG-4D5E6F7Gerror2trueblankVH-H0123SEN-CAM-0056camerarearview mirror2024-04-21T05:27:48ZCAM-ERR-404Camera hardware failure.2023-11-212024-10-21hardware_faultv3.1.0AudiQ72017BerlinBerlinGermany52.5213.405

What the 120 rows show

from the 120-row sample

Operational status stands out: mean uptime_seconds is 1,501,893, against 109,578 for the rest.

  • 43%anomaly_detected = true
  • 99,000median uptime_seconds
  • 5anomaly types
  • 6sensor types
  • 22countries
  • 36sensor locations
Mean uptime_seconds by status116 rows
01M2M1.5Moperat…49 rows351.2kdegrad…19 rows0.0offline11 rows33,488mainte…20 rows1.1error17 rows
uptime_seconds116 rows, in bands of 250k
030606023949139701.3M2.3Muptime_seconds →

Median 99,000, from 0 to 2,115,000.

fleet_id64 rows with a value · 56 left blank
  1. FL-BlueSky15
  2. FL-RedLine12
  3. FL-EdgeCases11
  4. FL-GreenFleet6
  5. FL-NorthStar6
  6. FL-SilverArrow3
  7. FL-OasisFleet1
  8. FL-EuroTransit1
  9. FL-PacificStar1
  10. FL-IndiaMetro1
24 columns by typefrom the column list below
  • string 16
  • integer 2
  • float 2
  • date 2
  • datetime 1
  • boolean 1

Columns

24 columns in four groups
blueprint · 24 columns
columntypedescriptionexample
Text 16 columns
log_idstringUnique identifier for each sensor health log entry.uniqueLOG-1A2B3C4D
vehicle_idstringUnique identifier for the connected vehicle.VH-A1234
fleet_idstringIdentifier for the fleet to which the vehicle belongs.optionalFL-BlueSky
sensor_idstringUnique identifier for the IoT sensor within the vehicle.SEN-GPS-0001
sensor_typestringType of sensor (e.g., GPS, accelerometer, temperature, camera).7 valuesGPS
sensor_locationstringPhysical location of the sensor within the vehicle (e.g., front bumper, dashboard).optionaldashboard
statusstringOperational status of the sensor at the time of logging.operational · degraded · offline · maintenance · erroroperational
error_codestringError code reported by the sensor, if any.optionalCAM-DRIFT
error_descriptionstringDetailed description of the error or anomaly detected.optionalSensor not responding.
anomaly_typestringType of anomaly detected (e.g., outlier, communication failure, hardware fault).6 values · optionalnone
sensor_firmware_versionstringFirmware version currently running on the sensor.optionalv1.4.2
vehicle_makestringManufacturer of the vehicle.optionalFord
vehicle_modelstringModel of the vehicle.optionalExplorer
citystringCity where the vehicle was located at the time of logging.optionalSan Francisco
statestringState or province where the vehicle was located at the time of logging.optionalCA
countrystringCountry where the vehicle was located at the time of logging.optionalUSA
Numbers 4 columns
uptime_secondsintegerTotal number of seconds the sensor has been operational since last reset.0 or more · optional1263000
vehicle_yearintegerYear the vehicle was manufactured.1,980 to 2,100 · optional2020
latitudefloatLatitude coordinate of the vehicle at the time of logging.-90 to 90 · optional37.7749
longitudefloatLongitude coordinate of the vehicle at the time of logging.-180 to 180 · optional-122.4194
Dates and times 3 columns
timestampdatetimeDate and time when the sensor health log was recorded.2024-04-15T09:22:11Z
last_maintenance_datedateDate when the sensor last underwent maintenance.optional2024-01-15
next_maintenance_duedateScheduled date for the sensor's next maintenance.optional2024-10-15
True or false 1 column
anomaly_detectedbooleanIndicates whether an anomaly was detected in sensor readings.false

Use it for

  • anomaly detect…43%51 of 120 rowsmean uptime seconds b…1.5Moper…351.2kdegr…0.0offl…33.5kmain…

    A transportation dashboard

    The anomaly_detected rate, uptime_seconds by status and a breakdown of fleet_id. Excel, Power BI or Tableau.

  • Why do the 49 operational rows have a mean uptime_seconds of 1,501,893?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable logs with vehicle_id, fleet_id and sensor_id to fill a screen in front of a buyer.

Not quite right?

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This dataset120 rows24 columns
Yours1,000 rows24 columnssensor_location: UK only

blueprint · connected-vehicle-sensor-health-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 24 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row represents a unique vehicle-sensor event.
  • Sensor status must be one of: operational, degraded, offline.
  • Event timestamps are recorded in UTC format.
  • Severity scores assigned based on pre-defined fault codes.
  • Vehicle ID and sensor type are required fields.
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
connected-vehicle-sensor-health-logs

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