• Energy
  • 19 columns
  • 120 rows
  • 8 formats

Urban Building IoT Energy Logs

This dataset contains granular energy consumption logs from IoT sensors in urban commercial buildings, including building and sensor metadata, timestamped readings, and estimated CO2 emissions. It enables smart city planners and engineers to analyze energy patterns, detect inefficiencies, and prioritize sustainability upgrades for emission reduction. The dataset supports actionable insights for optimizing urban infrastructure and advancing sustainability goals.

  • last updated 25 Nov 2025
  • by GoMask
The brief that made it

Energy efficiency analysis for urban commercial buildings

Sample rows

preview · 8 of 120 rows · all 19 columns
log_idstringsensor_typestringfloor_area_sqmfloatis_anomalybooleanaddress_citystringbuilding_idstringbuilding_namestringaddress_streetstringaddress_statestringaddress_postal_codestringaddress_countrystringsensor_idstringsensor_locationstringtimestampdatetimeenergy_consumption_kwhfloatpeak_load_kwfloatco2_emissions_kgfloatenergy_sourcestringbuilding_typestring
LOG0001electricity2450falseNew YorkBLD-A101Sunrise Center101 Main AveNY10001USASENS-0001Floor 2, Room 2042024-06-01T08:14:32Z34.612.315.8gridoffice
LOG0002water18200falseChicagoBLD-R205Market Plaza210 7th StIL60611USASENS-0002Basement, Water Panel2024-06-01T09:31:17Z0blank0gridretail
LOG0003hvac1200falseTorontoBLD-H110Lakeview Hotel502 Lakeshore DrONM5V2T6CanadaSENS-0003Floor 3, HVAC Zone2024-06-01T10:01:43Z41.113.218.7gridhotel
LOG0004electricity6100falseSan FranciscoBLD-O303EcoWorks Tower33 Green StCA94111USASENS-0004Floor 6, Server Room2024-06-01T11:19:08Z49.81523.6gridoffice
LOG0005water4100falseSydneyBLD-H201GoodHealth Center17 Wellness RdNSW2000AustraliaSENS-0005Ground Floor2024-06-01T12:42:55Z0.2blank0otherhospital
LOG0006gas25000falseLondonBLD-R311Central Mall884 Queen StLDNW1D3BJUKSENS-0006Service Corridor2024-06-01T13:59:02Z0.80.73.5gasretail
LOG0007hvac3200falseBostonBLD-O409NorthStar Offices45 Market StMA02109USASENS-0007Floor 4, HVAC Room2024-06-01T14:16:17Z12.76.49.2gridoffice
LOG0008other67000trueBerlinBLD-S504blank1200 Grand BlvdBE10115GermanySENS-0008blank2024-06-01T15:01:41Z2330.11250.21550otherother

What the 120 rows show

from the 120-row sample

Other (sensor type) stands out: mean floor_area_sqm is 52,984, against 6,031 for the rest.

  • 15%is_anomaly = true
  • 3,700median floor_area_sqm
  • 5energy sources
  • 5building types
  • 11address countries
  • 29address states
Mean floor_area_sqm by sensor_type120 rows
040k80k5,300electr…46 rows8,003water20 rows6,778gas16 rows5,371hvac27 rows52,984other11 rows
floor_area_sqm120 rows, in bands of 10k
050100931330308040k70kfloor_area_sqm →

Median 3,700, from 60 to 70,000.

address_city120 rows · top 10 of 36 values
  1. Toronto8
  2. Sydney8
  3. Chicago7
  4. London7
  5. Berlin6
  6. Melbourne6
  7. San Francisco5
  8. Boston5
  9. Vancouver5
  10. Los Angeles5
19 columns by typefrom the column list below
  • string 13
  • float 4
  • datetime 1
  • boolean 1

Columns

19 columns in four groups
blueprint · 19 columns
columntypedescriptionexample
Text 13 columns
log_idstringUnique identifier for each energy log entryuniqueLOG0001
building_idstringUnique identifier for the building where the sensor is deployedBLD-A101
building_namestringName of the buildingoptionalSunrise Center
address_streetstringStreet address of the buildingoptional101 Main Ave
address_citystringCity where the building is locatedNew York
address_statestringState or province where the building is locatedNY
address_postal_codestringPostal code of the buildingoptional10001
address_countrystringCountry where the building is located11 countriesUSA
sensor_idstringUnique identifier for the IoT sensorSENS-0001
sensor_typestringType of sensor (e.g., electricity, water, gas, HVAC)electricity · water · gas · hvac · otherelectricity
sensor_locationstringPhysical location of the sensor within the building (e.g., floor, room)optionalFloor 2, Room 204
energy_sourcestringPrimary energy source (e.g., grid, solar, wind, gas)grid · solar · wind · gas · other · optionalgrid
building_typestringType of commercial building (e.g., office, retail, hotel, hospital)office · retail · hotel · hospital · other · optionaloffice
Numbers 4 columns
energy_consumption_kwhfloatMeasured energy consumption in kilowatt-hours (kWh)0 or more34.6
peak_load_kwfloatPeak load measured in kilowatts (kW) during the logging period0 or more · optional12.3
co2_emissions_kgfloatEstimated CO2 emissions in kilograms for the logged energy consumption0 or more · optional15.8
floor_area_sqmfloatTotal floor area of the building in square meters0 or more · optional2450
Dates and times 1 column
timestampdatetimeDate and time when the energy consumption was recorded2024-06-01T08:14:32Z
True or false 1 column
is_anomalybooleanIndicates if the log entry is flagged as an anomaly (e.g., unusual consumption)optionalfalse

Use it for

  • is anomaly15%18 of 120 rowsmean floor area sqm b…5.3kelec…8kwater6.8kgas5.4khvac

    An energy dashboard

    The is_anomaly rate, floor_area_sqm by sensor_type and a breakdown of address_city. Excel, Power BI or Tableau.

  • Why do the 11 other rows have a mean floor_area_sqm of 52,984?

    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 building_id, building_name and address_street to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 19 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset120 rows19 columns
Yours1,000 rows19 columnsaddress_street: UK only

blueprint · urban-building-iot-energy-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 19 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 building-day combination.
  • Energy consumption values are collected hourly via certified IoT devices.
  • Sensor anomalies (e.g., missing readings) are flagged and require manual review.
  • Buildings must be registered with local smart infrastructure authorities.
  • Energy usage is normalized per square meter for cross-building analysis.
  • Only buildings with at least 90% sensor uptime per day are included.
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
urban-building-iot-energy-logs

More in Energy

Browse all
Also in EnergyMunicipal Building Energy Optimization MetricsGas Insulated Switchgear (GIS) Inspection and SF6 Leak DetectionNatural Gas Pipeline Receipt and Delivery PointsAll 1,967 datasets

What should your data show?

Preview 20 rows free
No signup. No card.