Energy
21 columns
120 rows
8 formats

Smart Facility Energy Sensor Logs

This dataset contains detailed, time-stamped energy consumption logs from IoT sensors across diverse real estate properties. Each record links energy usage, power demand, and estimated emissions to specific sensors and locations, enabling granular analysis for facility management, sustainability tracking, and smart building optimization. The dataset is ideal for benchmarking, anomaly detection, and supporting ESG and smart city initiatives.

last updated 5 Dec 2025
by GoMask

The brief that made it

Building energy efficiency benchmarking and optimization

Sample rows

preview · 8 of 120 rows · all 21 columns

log_idstring	property_typestring	energy_consumed_kwhfloat	is_anomalyboolean	address_statestring	property_idstring	property_namestring	address_streetstring	address_citystring	address_postal_codestring	address_countrystring	sensor_idstring	sensor_typestring	sensor_locationstring	timestampdatetime	interval_minutesinteger	power_peak_kwfloat	power_average_kwfloat	co2_emissions_kgfloat	sensor_statusstring	notesstring
LOG0001	office	320.52	false	IL	PROP01	Main Office Tower	100 Main St	Chicago	60601	USA	SENS-1001	electricity_meter	Floor 1, Utility Room	2024-06-01T08:15:00Z	60	38.2	28.5	185.1	active	Routine morning reading.
LOG0002	residential	3.41	false	OH	PROP02	Riverside Apartments	245 Riverside Dr	Cincinnati	45202	USA	SENS-1002	gas_meter	Basement Utility	2024-06-01T07:45:00Z	30	1.2	0.7	1.3	active	Normal usage overnight.
LOG0003	retail	6.7	false	TX	PROP03	West End Mall	500 Commerce Ave	Dallas	75201	USA	SENS-1003	lighting_sensor	Atrium, Level 2	2024-06-01T09:00:00Z	60	2.9	2.2	3.2	active	Customer traffic increasing.
LOG0004	industrial	97.56	false	IN	PROP04	Blue Steel Plant	1200 Steel Rd	Gary	46402	USA	SENS-1004	HVAC_sensor	Main Factory Floor	2024-06-01T08:45:00Z	120	21.7	16.2	52.4	active	HVAC running at scheduled level.
LOG0005	mixed-use	0.42	false	NC	PROP05	Creekside Mixed Center	800 Creekside Blvd	Charlotte	28201	USA	SENS-1005	water_meter	Parking Garage Level B	2024-06-01T09:15:00Z	15	0	0	0.2	active	Low water use overnight.
LOG0006	residential	0.21	false	CO	PROP06	Sunset View Homes	733 Sunset Ave	Denver	80203	USA	SENS-1006	water_meter	Laundry Room	2024-06-01T07:35:00Z	15	0	0	0.1	active	Laundry cycle completed.
LOG0007	office	225.13	false	CA	PROP07	Innovation Hub	350 Tech Park Dr	San Jose	95134	USA	SENS-1007	electricity_meter	Server Room	2024-06-01T08:30:00Z	60	41.3	33.7	128.8	active	Server backup in progress.
LOG0008	office	11.4	false	MN	PROP08	Maple Grove Offices	41 Maple Ave	Minneapolis	55401	USA	SENS-1008	lighting_sensor	Lobby	2024-06-01T08:00:00Z	30	3.5	2.8	5.9	active	Lobby lights on for opening.
LOG0009	industrial	72.64	false	PA	PROP09	Southside Depot	1819 Depot St	Pittsburgh	15222	USA	SENS-1009	HVAC_sensor	Receiving Area	2024-06-01T09:30:00Z	120	16.3	12.8	41.7	active	Temperature regulation normal.
LOG0010	retail	0.67	false	CA	PROP10	East Bay Plaza	200 Bay St	Oakland	94607	USA	SENS-1010	water_meter	Restroom 1	2024-06-01T10:00:00Z	15	0	0	0.3	active	Restroom cleaned.
LOG0011	office	175.67	false	TX	PROP11	City Tower	550 City Center	Houston	77002	USA	SENS-1011	electricity_meter	Floor 14, Panel Room	2024-06-01T08:45:00Z	60	34.8	26.9	97.2	active	Elevator peak usage.
LOG0012	residential	1.12	false	FL	PROP12	Edgewater Condos	88 Edgewater Rd	Miami	33132	USA	SENS-1012	gas_meter	Roof Utility	2024-06-01T06:30:00Z	30	0.5	0.3	0.5	active	Early morning cooking.
LOG0013	retail	9.4	false	PA	PROP13	Central Market	301 Market St	Philadelphia	19106	USA	SENS-1013	electricity_meter	Main Hall	2024-06-01T09:00:00Z	30	2.1	1.5	4.8	active	Opening day spike.
LOG0014	industrial	240.86	false	MI	PROP14	Ironworks Industrial	5400 Iron Blvd	Detroit	48226	USA	SENS-1014	electricity_meter	Machinery Bay 1	2024-06-01T09:00:00Z	60	44.9	38.3	134.7	active	Production ramp up.
LOG0015	mixed-use	1.15	false	CA	PROP15	Harbor Point	95 Harbor Blvd	San Francisco	94107	USA	SENS-1015	water_meter	Retail Level 1	2024-06-01T10:30:00Z	15	0	0	0.5	active	Morning cleaning.
LOG0016	residential	0.28	false	WA	PROP16	Parkside Residences	722 Parkside Ln	Seattle	98109	USA	SENS-1016	water_meter	Lobby Restroom	2024-06-01T07:10:00Z	15	0	0	0.1	active	Routine check.
LOG0017	office	135.26	false	MA	PROP17	Northgate Offices	880 Northgate Dr	Boston	02108	USA	SENS-1017	electricity_meter	Conference Room	2024-06-01T08:00:00Z	60	22.9	18.6	72.1	active	Meeting scheduled.
LOG0018	industrial	89.37	false	OH	PROP18	Greenfield Plant	2100 Greenfield Rd	Cleveland	44115	USA	SENS-1018	HVAC_sensor	Zone 3	2024-06-01T09:45:00Z	120	18.2	14.1	47.6	active	HVAC cycle completed.
LOG0019	retail	8.6	false	MO	PROP19	Central Plaza	400 Central Ave	St Louis	63101	USA	SENS-1019	lighting_sensor	Mall Entrance	2024-06-01T08:15:00Z	30	3.8	2.5	3.6	active	Opening lights on.
LOG0020	other	9999.99	true	blank	PROP20	Sunrise Research Center	blank	blank	blank	USA	SENS-1020	other	blank	2024-06-01T06:00:00Z	1440	9999.99	9999.99	9999.99	error	Extreme outlier detected. Sensor likely malfunctioning.

What the 120 rows show

from the 120-row sample

Other (property type) stands out: 13 of its 13 rows have is_anomaly = true, against 4 of 107 for the rest.

14%is_anomaly = true
9.2median energy_consumed_kwh
4sensor statuses
6sensor types
30median interval_minutes
2.9median power_peak_kw

Is anomaly rate by property_typeis_anomaly = true

energy_consumed_kwh120 rows, in bands of 1,000

Median 9.2, from 0.0 to 10,000.

address_state107 rows with a value · 13 left blank

CA15
OH11
TX6
FL5
MO5
WI5
IL4
NC4
CO4
MN4

21 columns by typefrom the column list below

string 14
integer 1
float 4
datetime 1
boolean 1

Columns

21 columns in four groups

blueprint · 21 columns
column	type	description	example
Text 14 columns
`log_id`	string	Unique identifier for each energy sensor log entryunique	LOG0001
`property_id`	string	Unique identifier for the real estate property where the sensor is installed	PROP01
`property_name`	string	Name or label of the property (e.g., 'Main Office Tower')optional	Main Office Tower
`property_type`	string	Type of property (e.g., office, residential, retail, industrial)6 values · optional	office
`address_street`	string	Street address of the propertyoptional	100 Main St
`address_city`	string	City where the property is locatedoptional	Chicago
`address_state`	string	State or region of the property locationoptional	IL
`address_postal_code`	string	Postal or ZIP code of the propertyoptional	60601
`address_country`	string	Country where the property is locatedoptional	USA
`sensor_id`	string	Unique identifier for the IoT energy sensor device	SENS-1001
`sensor_type`	string	Type of sensor (e.g., electricity_meter, gas_meter, water_meter, HVAC_sensor, lighting_sensor)6 values	electricity_meter
`sensor_location`	string	Specific location of the sensor within the property (e.g., 'Floor 2, Room 201')optional	Floor 1, Utility Room
`sensor_status`	string	Status of the sensor at the time of logging (e.g., active, inactive, error, maintenance)active · inactive · error · maintenance · unknown · optional	active
`notes`	string	Optional field for additional comments or notes about the log entryoptional	Routine morning reading.
Numbers 5 columns
`energy_consumed_kwh`	float	Amount of energy consumed during the logging interval, measured in kilowatt-hours (kWh)0 or more	320.52
`interval_minutes`	integer	Duration of the logging interval in minutes (e.g., 15 for 15-minute intervals)1 or more	60
`power_peak_kw`	float	Peak power demand recorded during the interval, in kilowatts (kW)0 or more · optional	38.2
`power_average_kw`	float	Average power demand during the interval, in kilowatts (kW)0 or more · optional	28.5
`co2_emissions_kg`	float	Estimated CO2 emissions for the interval, in kilograms (kg), based on local energy mix0 or more · optional	185.1
Dates and times 1 column
`timestamp`	datetime	Date and time when the sensor reading was recorded (ISO 8601 format, UTC recommended)	2024-06-01T08:15:00Z
True or false 1 column
`is_anomaly`	boolean	Flag indicating whether the sensor reading is considered anomalous or outside expected rangeoptional	false

Use it for

An energy dashboard
The is_anomaly rate, energy_consumed_kwh by property_type and a breakdown of address_state. Excel, Power BI or Tableau.
Why do 17 of 120 rows have is_anomaly = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs120
LOG0001320.52office
LOG00209999.99other
LOG00280other
A software demo
Believable logs with property_id, property_name and property_type to fill a screen in front of a buyer.

This dataset120 rows21 columns

Yours1,000 rows21 columnsaddress_street: UK only

blueprint · smart-facility-energy-sensor-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 21 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 reflects an hourly energy reading from a unique sensor.
Sensor locations are mapped to property zones (e.g., lobby, HVAC room, data center).
Energy readings flagged if exceeding pre-set efficiency thresholds.
Compliance status included for local building energy regulations.
Sensor downtime events are logged and categorized (maintenance, outage).

Rows1,000 rows10,000 rows100,000 rows1,000,000 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: smart-facility-energy-sensor-logs

What should your data show?

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Sample rows

What the 120 rows show

Columns

Use it for

An energy dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Energy

What should your data show?