Fleet IoT Sustainability Metrics

This dataset provides granular, time-stamped IoT sensor data for urban transport fleets, capturing vehicle activity, energy consumption, maintenance status, and ESG compliance metrics. Designed for small and medium businesses, it enables actionable insights to optimize routes, reduce carbon emissions, and improve sustainability reporting and regulatory compliance.

  • last updated 9 Dec 2025
  • by GoMask
The brief that made it

Optimizing fleet routes for reduced energy consumption and emissions

Sample rows

preview · 8 of 120 rows · all 22 columns
fleet_idstringmaintenance_statusstringesg_compliance_scorefloatincident_reportedbooleanvehicle_typestringvehicle_idstringregistration_platestringsensor_idstringtimestampdatetimelocation_latitudefloatlocation_longitudefloatdistance_travelled_kmfloatenergy_consumed_kwhfloatfuel_typestringcarbon_emissions_kgfloatlast_maintenance_datedatenext_maintenance_due_datedateroute_idstringroute_namestringincident_descriptionstringdriver_idstringdriver_namestring
FLEET_NYC_001ok68.8falsevanVAN_001_ANY-AB1234SENSOR_VAN_0012024-05-12T08:32:19Z40.7128-74.00624.714.5cng18.72024-04-152024-07-15NYC_DELIVERY_01Midtown Manhattan DeliveryblankDR_001_JJamal Carter
FLEET_SF_002ok91.7falsecarCAR_002_BCA-BC2345SENSOR_CAR_0022024-05-13T09:10:02Z37.7749-122.419412.41.5hybrid0.32024-05-012024-11-01SF_COMMUTE_02Downtown SF CommuteblankDR_002_LLily Nguyen
FLEET_LON_003completed99.1falsee-bikeEBIKE_003_CLDN-E3456SENSOR_EBIKE_0032024-05-13T11:55:21Z51.5074-0.12786.21.3electric0.012024-05-102024-08-10LON_DELIVERY_03Westminster Urban ParcelblankDR_003_AAlex Turner
FLEET_MUM_004due34.7truetruckTRUCK_004_DMH-TR4567SENSOR_TRUCK_0042024-05-12T18:40:32Z19.07672.8777518.3289.7diesel1720.62024-03-222024-06-22MUM_FREIGHT_04Eastern Corridor FreightBrake issue reportedDR_004_KKiran Desai
FLEET_SP_005in_progress24.2falsebusBUS_005_ESP-BU5678SENSOR_BUS_0052024-05-14T06:32:41Z-23.5505-46.6333342.6621.5diesel1438.92024-04-052024-09-05SP_TRANSIT_05Centro North Bus TransitblankDR_005_FFelipe Souza
FLEET_BER_006ok88.9falsecarCAR_006_FBER-C6789SENSOR_CAR_0062024-05-13T14:05:07Z52.5213.40517.31.8petrol1.52024-04-282024-10-28BER_COMMUTE_06Prenzlauer Berg CommuteblankDR_006_SSarah Becker
FLEET_SYD_007ok70.2falsevanVAN_007_GSY-VA7890SENSOR_VAN_0072024-05-13T22:16:49Z-33.8688151.209334.816.7petrol27.32024-05-032024-08-03SYD_DELIVERY_07CBD Delivery CircuitblankDR_007_MMegan Walsh
FLEET_DEL_008critical12.5truetruckTRUCK_008_HDL-TR8901SENSOR_TRUCK_0082024-05-14T02:21:11Z28.613977.209688.21065.3diesel2119.62024-02-172024-05-17blankblankEngine overheatedblankblank

What the 120 rows show

from the 120-row sample

Critical (maintenance status) stands out: mean esg_compliance_score is 6.6, against 69.6 for the rest.

  • 25%incident_reported = true
  • 72.8median esg_compliance_score
  • 5fuel types
  • 29.4median distance_travelled_km
  • 12.9median energy_consumed_kwh
  • 16.9median carbon_emissions_kg
Mean esg_compliance_score by maintenance_status120 rows
05010086.2ok64 rows31.2due17 rows31.3in_pro…10 rows68.4comple…17 rows6.6critic…12 rows
esg_compliance_score120 rows, in bands of 10
025501041611411016741050100esg_compliance_score →

Median 72.8, from 0.70 to 99.8.

vehicle_type120 rows · 5 values
  1. truck31
  2. van27
  3. car26
  4. e-bike22
  5. bus14
22 columns by typefrom the column list below
  • string 12
  • float 6
  • date 2
  • datetime 1
  • boolean 1

Columns

22 columns in four groups
blueprint · 22 columns
columntypedescriptionexample
Text 12 columns
fleet_idstringUnique identifier for the fleet or business entityFLEET_NYC_001
vehicle_idstringUnique identifier for each vehicle in the fleetuniqueVAN_001_A
vehicle_typestringType of vehicle (e.g., van, truck, e-bike, bus)6 valuesvan
registration_platestringOfficial vehicle registration plateuniqueNY-AB1234
sensor_idstringUnique identifier for the IoT sensor installed on the vehicleSENSOR_VAN_001
fuel_typestringType of fuel or energy source used by the vehicle6 valuescng
maintenance_statusstringCurrent maintenance status of the vehicleok · due · in_progress · completed · criticalok
route_idstringIdentifier for the route assigned to the vehicleoptionalNYC_DELIVERY_01
route_namestringHuman-readable name or description of the routeoptionalDowntown SF Commute
incident_descriptionstringDescription of the incident, if anyoptionalBrake issue reported
driver_idstringUnique identifier for the driver assigned to the vehicleoptionalDR_001_J
driver_namestringName of the driver assigned to the vehicleoptionalJamal Carter
Numbers 6 columns
location_latitudefloatLatitude coordinate of the vehicle at the time of data capture-90 to 9040.7128
location_longitudefloatLongitude coordinate of the vehicle at the time of data capture-180 to 180-74.006
distance_travelled_kmfloatDistance travelled by the vehicle since last reading, in kilometers0 or more24.7
energy_consumed_kwhfloatEnergy consumed by the vehicle since last reading, in kilowatt-hours0 or more14.5
carbon_emissions_kgfloatEstimated carbon emissions produced since last reading, in kilograms0 or more18.7
esg_compliance_scorefloatEnvironmental, Social, and Governance compliance score for the vehicle or route (0-100)0 to 100 · optional68.8
Dates and times 3 columns
timestampdatetimeDate and time when the sensor data was recorded2024-05-12T08:32:19Z
last_maintenance_datedateDate of the last completed maintenance for the vehicleoptional2024-04-15
next_maintenance_due_datedateScheduled date for the next maintenanceoptional2024-07-15
True or false 1 column
incident_reportedbooleanIndicates if any incident (accident, breakdown, etc.) was reported during this activityoptionalfalse

Use it for

  • incident repor…25%30 of 120 rowsmean esg compliance s…86.2ok31.2due31.3in_p…68.4comp…

    A transportation dashboard

    The incident_reported rate, esg_compliance_score by maintenance_status and a breakdown of vehicle_type. Excel, Power BI or Tableau.

  • Why do the 12 critical rows have a mean esg_compliance_score of 6.6?

    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 fleets with vehicle_id, vehicle_type and registration_plate to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 22 columns, your size and your rules. See 20 rows before you pay.

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This dataset120 rows22 columns
Yours1,000 rows22 columnslocation_latitude: UK only

blueprint · fleet-iot-sustainability-metrics

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 22 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 vehicle entry must include IoT sensor readings for location, energy consumption, and maintenance status.
  • All trips must record start/end timestamps and calculated emissions values.
  • Maintenance events are only valid if scheduled within recommended intervals (based on usage hours).
  • Daily route efficiency scores must be calculated for fleet optimization.
  • ESG impact ratings must be updated monthly per vehicle based on cumulative data.
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
fleet-iot-sustainability-metrics

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