Real Estate
23 columns
72 rows
8 formats

Smart Building Energy Optimization Log

This dataset provides detailed, timestamped logs of energy usage, optimization actions, and sustainability outcomes for smart buildings. It enables operators and analysts to track operational efficiency, evaluate the impact of optimization strategies, monitor predictive maintenance, and support ESG reporting. The comprehensive structure supports advanced analytics for energy management and sustainability initiatives across real estate portfolios.

last updated 31 Jan 2026
by GoMask

The brief that made it

Operational efficiency analysis and benchmarking across building portfolios

Sample rows

preview · 8 of 72 rows · all 23 columns

log_idstring	energy_usage_typestring	predicted_savings_kwhfloat	maintenance_flagboolean	optimization_actionstring	building_idstring	building_namestring	address_streetstring	address_citystring	address_statestring	address_postal_codestring	address_countrystring	zonestring	timestampdatetime	energy_usage_kwhfloat	action_resultstring	actual_savings_kwhfloat	co2_emissions_kgfloat	esg_scorefloat	maintenance_typestring	operator_idstring	operator_namestring	notesstring
LOG-0001-A	electricity	23.2	false	HVAC adjustment	BLDG-101	TechWorks Tower	120 Innovation Blvd	San Francisco	CA	94107	USA	Floor 5 - West Wing	2024-05-01T09:30:00	235.6	success	21.8	94.5	87.3	blank	OP-0023	GreenOps System	Routine seasonal optimization
LOG-0002-A	lighting	12.3	false	Lighting schedule	BLDG-102	EnergyHub Plaza	22 Battery St	San Francisco	CA	94111	USA	Lobby	2024-05-01T10:12:00	110.9	partial	9.6	41.7	79.6	blank	OP-0012	BrightControl	Lights dimmed after 8pm
LOG-0003-A	cooling	31.5	true	Predictive maintenance	BLDG-101	TechWorks Tower	120 Innovation Blvd	San Francisco	CA	94107	USA	Floor 8 - Server Room	2024-05-01T11:24:00	329.1	scheduled	0	132.7	88.9	HVAC filter replacement	OP-0027	FacilityAI	Maintenance scheduled for next week
LOG-0004-A	heating	15.7	false	Heating schedule	BLDG-103	EcoSpace Center	500 Green St	Oakland	CA	94607	USA	Floor 2 - East Wing	2024-05-02T08:55:00	185.3	success	15.3	62.1	92.4	blank	OP-0018	HeatMaster Pro	Heating reduced after 6pm
LOG-0005-A	lighting	9.1	false	Lighting schedule	BLDG-104	Skyline Campus	300 Market St	San Jose	CA	95113	USA	Conference Hall	2024-05-02T12:40:00	78.8	success	8.7	28.5	81.2	blank	OP-0030	BrightControl	Conference event lighting reduced after event
LOG-0006-A	electricity	blank	false	blank	BLDG-105	Renewal Point	200 Solar Drive	Sacramento	CA	95814	USA	Floor 3 - North	2024-05-02T15:17:00	99.2	not_applicable	blank	39.3	84.7	blank	blank	blank	No action taken
LOG-0007-A	cooling	19.8	false	Chiller optimization	BLDG-104	Skyline Campus	300 Market St	San Jose	CA	95113	USA	Floor 7 - South	2024-05-02T16:23:00	140.4	success	18.2	52.7	78.9	blank	OP-0042	CoolSys	Chiller setpoint reduced for off-peak hours
LOG-0008-A	heating	7.7	true	Predictive maintenance	BLDG-105	Renewal Point	200 Solar Drive	Sacramento	CA	95814	USA	Floor 3 - South	2024-05-03T09:12:00	66.9	success	7.9	25.1	90.3	Boiler tune-up	OP-0027	FacilityAI	Boiler serviced, reduced energy spike
LOG-0009-A	electricity	17.5	false	Load balancing	BLDG-102	EnergyHub Plaza	22 Battery St	San Francisco	CA	94111	USA	Floor 2 - West	2024-05-03T10:45:00	180.1	success	16.9	70.2	85.5	blank	OP-0035	GridSmart	Load shifted to off-peak hours
LOG-0010-A	lighting	blank	false	blank	BLDG-103	EcoSpace Center	500 Green St	Oakland	CA	94607	USA	Floor 1 - Reception	2024-05-03T11:02:00	95.6	not_applicable	blank	36.6	94.1	blank	blank	blank	No optimization scheduled
LOG-0011-A	cooling	10.5	true	Predictive maintenance	BLDG-106	Fusion Park	700 Future Rd	Mountain View	CA	94043	USA	Floor 2 - Central	2024-05-03T14:33:00	120.7	success	11	45.9	83.8	Chiller inspection	OP-0027	FacilityAI	Chiller compressor replaced
LOG-0012-A	heating	6.9	false	Heating schedule	BLDG-106	Fusion Park	700 Future Rd	Mountain View	CA	94043	USA	Floor 1 - North Wing	2024-05-03T17:10:00	58.2	success	7.1	20.8	80.5	blank	OP-0018	HeatMaster Pro	Heating reduced after business hours
LOG-0013-A	electricity	15.3	false	Load balancing	BLDG-107	Helios Plaza	15 Solar Ave	Sunnyvale	CA	94086	USA	Floor 3 - West	2024-05-03T19:42:00	160.1	success	15	63.1	88.2	blank	OP-0035	GridSmart	Load shifted to solar hours
LOG-0014-A	lighting	10.2	false	Lighting schedule	BLDG-107	Helios Plaza	15 Solar Ave	Sunnyvale	CA	94086	USA	Floor 1 - South	2024-05-04T09:24:00	92.5	success	9.9	36.2	85.7	blank	OP-0030	BrightControl	LEDs dimmed for daylight hours
LOG-0015-A	electricity	blank	false	blank	BLDG-108	Vertex Center	400 Tech Lane	Palo Alto	CA	94301	USA	Floor 2 - East	2024-05-04T11:02:00	210.6	not_applicable	blank	84.2	81.9	blank	blank	blank	No optimization scheduled
LOG-0016-A	lighting	8.1	false	Lighting schedule	BLDG-108	Vertex Center	400 Tech Lane	Palo Alto	CA	94301	USA	Floor 1 - Reception	2024-05-04T13:38:00	85.4	success	7.7	34.5	83.3	blank	OP-0030	BrightControl	Reception lighting reduced after 7pm
LOG-0017-A	cooling	blank	false	blank	BLDG-109	Quantum Point	425 Infinity Dr	Berkeley	CA	94704	USA	Floor 6 - South	2024-05-04T15:20:00	136.7	not_applicable	blank	52.1	80.6	blank	blank	blank	No optimization performed
LOG-0018-A	heating	11.7	false	Heating schedule	BLDG-109	Quantum Point	425 Infinity Dr	Berkeley	CA	94704	USA	Floor 2 - East	2024-05-05T09:09:00	105.2	success	11.2	40.1	86.7	blank	OP-0018	HeatMaster Pro	Heating adjusted for weekend hours
LOG-0019-A	electricity	13.1	false	HVAC adjustment	BLDG-110	Optima Center	600 Optic Way	San Mateo	CA	94401	USA	Floor 4 - North	2024-05-05T11:45:00	128.9	partial	10.9	50.7	82.5	blank	OP-0023	GreenOps System	HVAC fan speed reduced
LOG-0020-A	lighting	blank	false	blank	BLDG-110	Optima Center	600 Optic Way	San Mateo	CA	94401	USA	Floor 1 - Lobby	2024-05-05T14:30:00	76.8	not_applicable	blank	30.2	84.2	blank	blank	blank	No optimization scheduled

What the 72 rows show

from the 72-row sample

Lighting (energy usage type) stands out: mean predicted_savings_kwh is 8.1, against 13.3 for the rest.

24%maintenance_flag = true
10.5median predicted_savings_kwh
5action results
12address states
119.4median energy_usage_kwh
9.6median actual_savings_kwh

Mean predicted_savings_kwh by energy_usage_type57 rows

predicted_savings_kwh57 rows, in bands of 5

Median 10.5, from 4.2 to 31.5.

optimization_action57 rows with a value · 15 left blank

HVAC adjustment10
Predictive maintenance10
Lighting schedule8
Heating setpoint change5
Heating schedule4
Load balancing4
HVAC filter replacement4
Chiller optimization3
Pump schedule revision3
Lighting repair3

23 columns by typefrom the column list below

string 16
float 5
datetime 1
boolean 1

Columns

23 columns in four groups

blueprint · 23 columns
column	type	description	example
Text 16 columns
`log_id`	string	Unique identifier for each energy optimization log entryunique	LOG-0001-A
`building_id`	string	Unique identifier for the building where the log was recorded	BLDG-101
`building_name`	string	Name of the building	TechWorks Tower
`address_street`	string	Street address of the buildingoptional	120 Innovation Blvd
`address_city`	string	City where the building is locatedoptional	San Francisco
`address_state`	string	State or region where the building is located12 states · optional	CA
`address_postal_code`	string	Postal code of the building's addressoptional	94107
`address_country`	string	Country where the building is locatedoptional	USA
`zone`	string	Specific zone or area within the building (e.g., floor, wing, room)optional	Floor 5 - West Wing
`energy_usage_type`	string	Type of energy usage measured (e.g., electricity, heating, cooling, lighting)electricity · heating · cooling · lighting · other	electricity
`optimization_action`	string	Type of optimization action performed (e.g., HVAC adjustment, lighting schedule, predictive maintenance)12 actions · optional	HVAC adjustment
`action_result`	string	Outcome of the optimization action (e.g., success, failure, partial, scheduled)success · failure · partial · scheduled · not_applicable · optional	success
`maintenance_type`	string	Type of maintenance action triggered (e.g., HVAC filter replacement, lighting repair)9 types · optional	HVAC filter replacement
`operator_id`	string	Unique identifier for the operator or system responsible for the optimization actionoptional	OP-0023
`operator_name`	string	Name of the operator or system responsible for the optimization actionoptional	GreenOps System
`notes`	string	Additional notes or comments related to the log entryoptional	Lights dimmed after 8pm
Numbers 5 columns
`energy_usage_kwh`	float	Total energy consumed in kilowatt-hours during the logged period0 or more	235.6
`predicted_savings_kwh`	float	Predicted energy savings in kilowatt-hours as a result of the optimization action0 or more · optional	23.2
`actual_savings_kwh`	float	Actual measured energy savings in kilowatt-hours after the optimization action0 or more · optional	21.8
`co2_emissions_kg`	float	CO2 emissions in kilograms associated with the energy usage during the logged period0 or more · optional	94.5
`esg_score`	float	Environmental, Social, and Governance (ESG) score for the building at the time of the log (0-100 scale)0 to 100 · optional	87.3
Dates and times 1 column
`timestamp`	datetime	Date and time when the energy usage and optimization action were logged	2024-05-01T09:30:00
True or false 1 column
`maintenance_flag`	boolean	Indicates if predictive maintenance was triggered as part of the optimization actionoptional	false

Use it for

A real estate dashboard
The maintenance_flag rate, predicted_savings_kwh by energy_usage_type and a breakdown of optimization_action. Excel, Power BI or Tableau.
Why do the 11 lighting rows have a mean predicted_savings_kwh of 8.1?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs72
LOG-0001-A23.2electric…
LOG-0003-A31.5cooling
LOG-0008-A7.7heating
A software demo
Believable logs with building_id, building_name and address_street to fill a screen in front of a buyer.

This dataset72 rows23 columns

Yours10,000 rows23 columnsaddress_street: UK only

blueprint · smart-building-energy-optimization-log

Behind this dataset

Same schema. As many rows as you need.

These 72 rows came out of a blueprint — 23 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 one building's daily energy optimization event
Optimization strategies must be logged with a timestamp and action type
Energy usage before and after intervention is recorded in kWh
Sustainability score calculated based on reduction percentage and local grid mix
Anomalies in energy consumption trigger a flag for review

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: smart-building-energy-optimization-log

What should your data show?

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Sample rows

What the 72 rows show

Columns

Use it for

A real estate dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Real Estate

What should your data show?