Energy
26 columns
75 rows
8 formats

IoT Building Energy Anomaly Logs

This dataset logs detailed records of energy usage anomalies detected by IoT sensors across commercial buildings, including sensor metadata, anomaly characteristics, location details, and corrective actions. It enables facilities managers and ESG consultants to benchmark energy performance, identify inefficiencies, and investigate abnormal consumption patterns for smarter, more sustainable building operations.

last updated 30 Jan 2026
by GoMask

The brief that made it

Benchmarking building energy performance for sustainability reporting

Sample rows

preview · 8 of 75 rows · all 26 columns

anomaly_idstring	anomaly_severitystring	anomaly_duration_minutesfloat	building_idstring	building_namestring	building_street_addressstring	building_citystring	building_statestring	building_postal_codestring	building_countrystring	floor_numberinteger	zone_namestring	sensor_idstring	sensor_typestring	anomaly_typestring	anomaly_statusstring	detection_timestampdatetime	expected_energy_usage_kwhfloat	actual_energy_usage_kwhfloat	energy_deviation_kwhfloat	energy_deviation_percentfloat	root_cause_suspectedstring	corrective_action_takenstring	resolved_timestampdatetime	reported_bystring	notesstring
ANML-00001	high	37.2	BLDG-1101	Aurora Tower	245 Market St	San Francisco	CA	94105	USA	7	Lobby	SNSR-E-1001	electricity_meter	spike	open	2024-05-01T08:27:00	15.5	35.9	20.4	131.6	Lighting left on overnight	blank	blank	system	Unusually high usage detected during off-hours
ANML-00002	medium	19.8	BLDG-1101	Aurora Tower	245 Market St	San Francisco	CA	94105	USA	12	Conference Room	SNSR-T-1107	temperature_sensor	pattern_deviation	investigating	2024-05-02T13:10:00	9.2	12.1	2.9	31.5	Thermostat misconfiguration	blank	blank	J.Smith	blank
ANML-00003	low	8.5	BLDG-1102	Pacific Plaza	150 Pine Ave	Los Angeles	CA	90045	USA	3	Main Office	SNSR-O-2013	occupancy_sensor	drop	resolved	2024-05-04T09:23:00	7.6	4.1	-3.5	-46.1	Holiday closure	Confirmed closure, no action needed	2024-05-04T10:31:00	system	Pattern matches previous holiday
ANML-00004	critical	47.9	BLDG-1201	Harbor Point	2232 3rd St	Seattle	WA	98121	USA	0	Basement	SNSR-H-3002	hvac_sensor	equipment_failure	open	2024-04-28T18:42:00	10.8	1.5	-9.3	-86.1	HVAC malfunction	blank	blank	system	Immediate technician dispatch recommended
ANML-00005	medium	16.4	BLDG-1202	Lakeview Center	6102 Green Lake Dr	Seattle	WA	98103	USA	2	Reception	SNSR-E-1206	electricity_meter	spike	investigating	2024-05-05T17:15:00	8	18.7	10.7	133.8	Cleaning crew activity	blank	blank	M.Kim	Spike coincides with scheduled cleaning
ANML-00006	high	7	BLDG-1202	Lakeview Center	6102 Green Lake Dr	Seattle	WA	98103	USA	1	Break Room	SNSR-T-1211	temperature_sensor	outlier	dismissed	2024-05-06T10:03:00	5.3	8.7	3.4	64.2	Short-term heatwave	No action required	2024-05-06T11:00:00	system	blank
ANML-00007	critical	51.6	BLDG-1301	Canyon Corporate	3300 W 6th St	Denver	CO	80204	USA	5	Server Room	SNSR-E-1302	electricity_meter	spike	resolved	2024-05-07T02:20:00	22.7	49.2	26.5	116.8	Server hardware test	Test scheduled, anomaly expected	2024-05-07T03:15:00	A.Lopez	Planned spike for maintenance
ANML-00008	medium	22	BLDG-1301	Canyon Corporate	3300 W 6th St	Denver	CO	80204	USA	2	Cafeteria	SNSR-O-1315	occupancy_sensor	drop	open	2024-05-08T08:35:00	10.2	8	-2.2	-21.6	Unexpected early closure	blank	blank	system	blank
ANML-00009	critical	39.2	BLDG-1401	Sunrise Plaza	500 S Broadway	Austin	TX	78704	USA	14	Roof	SNSR-H-1402	hvac_sensor	equipment_failure	investigating	2024-05-09T14:57:00	16.9	2.4	-14.5	-85.8	HVAC compressor shutdown	blank	blank	system	Technician dispatched
ANML-00010	medium	27.7	BLDG-1402	Sunrise Plaza	500 S Broadway	Austin	TX	78704	USA	10	Conference Room	SNSR-T-1410	temperature_sensor	pattern_deviation	resolved	2024-05-10T11:41:00	9.7	13.5	3.8	39.2	Manual thermostat override	Settings returned to normal	2024-05-10T12:12:00	T.Martin	blank
ANML-00011	medium	15.9	BLDG-1501	Midtown Hub	3701 16th St	Chicago	IL	60608	USA	0	Parking Garage	SNSR-E-1512	electricity_meter	spike	resolved	2024-04-30T22:54:00	6.5	13.2	6.7	103.1	EV charging event	Review scheduled	2024-05-01T04:00:00	system	blank
ANML-00012	low	6.2	BLDG-1501	Midtown Hub	3701 16th St	Chicago	IL	60608	USA	1	Lobby	SNSR-O-1519	occupancy_sensor	drop	dismissed	2024-05-11T08:00:00	2.8	1.1	-1.7	-60.7	Sensor error	Sensor recalibration	2024-05-11T08:32:00	system	Short-term data gap
ANML-00013	high	44.4	BLDG-1601	Riverfront Offices	101 Riverside Dr	Portland	OR	97205	USA	6	Executive Office	SNSR-E-1603	electricity_meter	spike	open	2024-05-12T15:20:00	12.4	30.2	17.8	143.5	After-hours meeting	blank	blank	system	High usage outside normal schedule
ANML-00014	medium	31.8	BLDG-1601	Riverfront Offices	101 Riverside Dr	Portland	OR	97205	USA	8	Board Room	SNSR-T-1610	temperature_sensor	pattern_deviation	investigating	2024-05-13T10:44:00	11.3	14.9	3.6	31.9	Meeting extended	blank	blank	V.Nguyen	blank
ANML-00015	high	13.5	BLDG-1701	Vista Park	8000 Vista Ln	San Diego	CA	92101	USA	4	Gym	SNSR-O-1708	occupancy_sensor	outlier	resolved	2024-05-14T19:15:00	6.9	10.8	3.9	56.5	Large group event	Attendance confirmed	2024-05-14T20:00:00	system	Usage spike matches event schedule
ANML-00016	medium	10.7	BLDG-1701	Vista Park	8000 Vista Ln	San Diego	CA	92101	USA	1	Reception	SNSR-E-1711	electricity_meter	spike	open	2024-05-15T07:55:00	4.2	7.8	3.6	85.7	Unexpected visitor influx	blank	blank	system	blank
ANML-00017	low	9.1	BLDG-1702	Vista Park	8000 Vista Ln	San Diego	CA	92101	USA	2	Break Room	SNSR-T-1705	temperature_sensor	pattern_deviation	open	2024-05-15T13:42:00	3.7	4.5	0.8	21.6	Manual override	blank	blank	system	blank
ANML-00018	medium	18.2	BLDG-1801	Cityview Center	1200 Main St	Dallas	TX	75202	USA	11	Lobby	SNSR-O-1812	occupancy_sensor	drop	investigating	2024-05-16T10:50:00	8.3	5.6	-2.7	-32.5	Unexpected early closing	blank	blank	B.Reed	blank
ANML-00019	medium	21.1	BLDG-1802	Cityview Center	1200 Main St	Dallas	TX	75202	USA	8	Conference Room	SNSR-T-1808	temperature_sensor	pattern_deviation	open	2024-05-17T09:37:00	6.7	9.5	2.8	41.8	Meeting room overuse	blank	blank	system	blank
ANML-00020	high	12.3	BLDG-1901	Highland Center	302 Highland Ave	Phoenix	AZ	85014	USA	0	Lobby	SNSR-E-1902	electricity_meter	spike	resolved	2024-05-18T05:14:00	7.5	16.4	8.9	118.7	Lighting left on	Lights turned off	2024-05-18T06:00:00	system	blank

What the 75 rows show

from the 75-row sample

Critical (anomaly severity) stands out: mean anomaly_duration_minutes is 43.9, against 17.8 for the rest.

17.0median anomaly_duration_minutes
4anomaly statuses
5sensor types
6anomaly types
12reported_by values
14building states

Mean anomaly_duration_minutes by anomaly_severity75 rows

anomaly_duration_minutes75 rows, in bands of 10

Median 17.0, from 5.4 to 51.8.

building_id75 rows · top 10 of 33 values

BLDG_10510
BLDG_1109
BLDG_1119
BLDG_2079
BLDG-11012
BLDG-12022
BLDG-13012
BLDG-15012
BLDG-16012
BLDG-17012

26 columns by typefrom the column list below

string 18
integer 1
float 5
datetime 2

Columns

26 columns in three groups

blueprint · 26 columns
column	type	description	example
Text 18 columns
`anomaly_id`	string	Unique identifier for each detected energy anomaly eventunique	ANML-00001
`building_id`	string	Unique identifier for the building where the anomaly was detected	BLDG-1101
`building_name`	string	Name of the buildingoptional	Aurora Tower
`building_street_address`	string	Street address of the buildingoptional	245 Market St
`building_city`	string	City where the building is locatedoptional	San Francisco
`building_state`	string	State or province where the building is locatedoptional	CA
`building_postal_code`	string	Postal or ZIP code of the buildingoptional	94105
`building_country`	string	Country where the building is locatedoptional	USA
`zone_name`	string	Name or label of the building zone/area (e.g., 'Lobby', 'Conference Room')optional	Lobby
`sensor_id`	string	Unique identifier for the IoT sensor that detected the anomaly	SNSR-E-1001
`sensor_type`	string	Type of IoT sensor (e.g., 'electricity_meter', 'temperature_sensor', 'occupancy_sensor')5 values	electricity_meter
`anomaly_type`	string	Category of anomaly detected (e.g., 'spike', 'drop', 'pattern_deviation', 'equipment_failure')6 values	spike
`anomaly_severity`	string	Severity level of the anomaly (e.g., 'low', 'medium', 'high', 'critical')low · medium · high · critical	high
`anomaly_status`	string	Current status of the anomaly (e.g., 'open', 'investigating', 'resolved', 'dismissed')open · investigating · resolved · dismissed	open
`root_cause_suspected`	string	Suspected root cause of the anomaly (e.g., 'HVAC malfunction', 'occupancy spike', 'sensor error')optional	Holiday closure
`corrective_action_taken`	string	Description of any corrective action taken in response to the anomalyoptional	No action required
`reported_by`	string	Name or identifier of the person or system that reported or confirmed the anomaly12 values · optional	system
`notes`	string	Additional notes or comments regarding the anomalyoptional	Technician dispatched
Numbers 6 columns
`floor_number`	integer	Floor number within the building where the anomaly was detected0 or more · optional	7
`anomaly_duration_minutes`	float	Duration of the anomaly in minutes (if applicable)0 or more · optional	37.2
`expected_energy_usage_kwh`	float	Expected energy usage in kWh for the period in which the anomaly occurred0 or more · optional	15.5
`actual_energy_usage_kwh`	float	Actual measured energy usage in kWh during the anomaly period0 or more · optional	35.9
`energy_deviation_kwh`	float	Difference between actual and expected energy usage in kWhoptional	20.4
`energy_deviation_percent`	float	Percentage deviation from expected energy usage-100 to 1,000 · optional	131.6
Dates and times 2 columns
`detection_timestamp`	datetime	Date and time when the anomaly was detected	2024-05-01T08:27:00
`resolved_timestamp`	datetime	Date and time when the anomaly was resolved (if applicable)optional	2024-05-04T10:31:00

Use it for

An energy dashboard
Anomaly_duration_minutes by anomaly_severity and a breakdown of building_id. Excel, Power BI or Tableau.
Why do the 11 critical rows have a mean anomaly_duration_minutes of 43.9?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Anomalies75
ANML-0000137.2high
ANML-0000219.8medium
ANML-000038.5low
A software demo
Believable anomalies with building_id, building_name and building_street_address to fill a screen in front of a buyer.

This dataset75 rows26 columns

Yours10,000 rows26 columnsbuilding_street_address: UK only

blueprint · iot-building-energy-anomaly-logs

Behind this dataset

Same schema. As many rows as you need.

These 75 rows came out of a blueprint — 26 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 anomaly event detected by a sensor.
Includes timestamp, anomaly type, severity rating, affected zone, baseline consumption, and deviation value.
Only anomalies exceeding 10% deviation from baseline are recorded.
Events are tagged by likely cause (equipment fault, peak demand, unauthorized usage, etc.).
Sensor IDs and building IDs are anonymized for privacy compliance.
All entries must include a recommended action field.

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

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

What should your data show?

No signup. No card.

Sample rows

What the 75 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?