Real Estate
19 columns
120 rows
8 formats

Real Estate IoT Sensors Efficiency Logs

This dataset provides detailed operational efficiency logs for IoT sensors deployed in commercial buildings, including sensor status, energy consumption, maintenance needs, and ESG relevance. It enables facilities managers to monitor device performance, prioritize maintenance, and optimize energy usage for sustainability and cost savings across real estate portfolios.

last updated 14 Dec 2025
by GoMask

The brief that made it

Identifying underperforming sensors for targeted maintenance

Sample rows

preview · 8 of 120 rows · all 19 columns

log_idstring	sensor_typestring	energy_consumptionfloat	maintenance_requiredboolean	address_citystring	sensor_idstring	building_idstring	building_namestring	address_streetstring	address_statestring	address_postal_codestring	address_countrystring	sensor_locationstring	timestampdatetime	operational_statusstring	efficiency_scorefloat	last_maintenance_datedate	esg_flagboolean	notesstring
LOG001-A01	temperature	0.22	false	New York	SEN-1001	BLD-001	Green Tower	123 Main St	NY	10001	USA	Lobby	2024-04-17T09:15:00	active	0.92	2024-02-28	true	Sensor operating within normal parameters.
LOG002-B19	occupancy	0.15	false	Los Angeles	SEN-1002	BLD-002	Sunset Plaza	456 Elm Ave	CA	90024	USA	Conference Room 4B	2024-04-17T10:30:00	active	0.89	2024-03-02	false	Occupancy sensor shows accurate readings.
LOG003-C22	air_quality	0.45	true	San Francisco	SEN-1011	BLD-003	Bayview Business Center	789 Bay St	CA	94109	USA	Server Room	2024-04-18T13:45:00	maintenance	0.38	2024-04-09	true	CO2 levels exceeded recommended threshold.
LOG004-D10	energy_meter	0.52	false	Chicago	SEN-1022	BLD-004	Windham Industrial	1012 Industrial Rd	IL	60616	USA	Mechanical Room	2024-04-19T08:10:00	active	0.82	2024-03-17	false	Energy consumption trending down past 30 days.
LOG005-E07	humidity	0.19	false	Toronto	SEN-1030	BLD-005	Maple Residences	611 Maple Ave	ON	M5J2N8	Canada	Basement Storage	2024-04-19T14:30:00	active	0.95	2024-02-25	true	Humidity levels remain stable.
LOG006-F12	motion	0.36	true	Houston	SEN-1031	BLD-006	Metro Mall	800 Commerce St	TX	77002	USA	Parking Garage Level 2	2024-04-20T11:05:00	faulty	0.41	2024-04-14	false	False positives detected, sensor requires recalibration.
LOG007-G16	temperature	0.25	false	Seattle	SEN-1042	BLD-007	Tech Campus West	1401 Innovation Blvd	WA	98101	USA	East Wing Hallway	2024-04-21T09:45:00	active	0.79	2024-03-02	true	Temperature readings consistent.
LOG008-H04	humidity	0.28	false	Boston	SEN-1043	BLD-008	Central School	900 School Rd	MA	02115	USA	Cafeteria	2024-04-21T12:20:00	active	0.86	2024-03-19	false	Humidity sensor calibrated after minor drift.
LOG009-I25	motion	0.53	true	Washington	SEN-1044	BLD-009	Federal Building	1200 Capitol Ave	DC	20001	USA	Main Entrance	2024-04-22T08:50:00	maintenance	0.21	2024-04-18	true	Inspection following sensor outage.
LOG010-J06	air_quality	0.18	false	Atlanta	SEN-1055	BLD-010	Parkside Offices	200 Park Rd	GA	30309	USA	Reception	2024-04-22T13:15:00	active	0.9	2024-03-21	true	Air quality sensor recently replaced.
LOG011-K07	energy_meter	0.44	true	Detroit	SEN-1066	BLD-011	Eastside Factory	321 Factory Dr	MI	48226	USA	Boiler Room	2024-04-23T08:40:00	faulty	0.45	2024-04-17	false	Unstable readings detected.
LOG012-L15	occupancy	0.17	false	London	SEN-1077	BLD-012	Canary Wharf	15 Churchill Pl	ENG	E14 5RE	UK	Floor 3 West Wing	2024-04-23T11:10:00	active	0.87	2024-03-14	true	Sensor utilization matches expected values.
LOG013-M09	temperature	0.2	false	Miami	SEN-1078	BLD-013	Sunrise Plaza	22 Sunrise Blvd	FL	33132	USA	Penthouse	2024-04-24T08:30:00	active	0.94	2024-02-28	false	Temperature sensor recalibrated after seasonal change.
LOG014-N11	humidity	0.23	false	San Diego	SEN-1079	BLD-014	Oceanview Residences	777 Ocean Ave	CA	92101	USA	Pool Area	2024-04-24T12:25:00	active	0.97	2024-03-05	true	Stable humidity readings after filter replacement.
LOG015-O13	motion	0.21	false	Cambridge	SEN-1080	BLD-015	Campus North	1300 University Rd	MA	02139	USA	Dormitory Hallway	2024-04-25T09:55:00	active	0.81	2024-03-11	false	Motion sensor replaced, no false triggers.
LOG016-P14	energy_meter	0.59	false	Dallas	SEN-1081	BLD-016	Silverstone Mall	500 Market St	TX	75201	USA	Electrical Closet	2024-04-25T14:05:00	active	0.74	2024-03-24	true	Energy savings after lighting retrofit.
LOG017-Q02	occupancy	0.13	false	Denver	SEN-1082	BLD-017	Skyline Center	400 Skyline Dr	CO	80202	USA	Executive Office	2024-04-26T08:15:00	active	0.85	2024-03-17	false	Occupancy sensor tested, meets standards.
LOG018-R01	air_quality	0.12	false	Paris	SEN-1093	BLD-018	blank	blank	IDF	75008	France	Lobby Entrance	2024-04-26T14:30:00	active	0.95	2024-03-09	true	Testing new sensor installation.
LOG019-S03	other	5	false	Shenzhen	SEN-1094	BLD-019	Shenzhen Tech Hub	88 Tech St	GD	518000	China	R&D Lab	2024-04-27T11:00:00	active	0.99	2024-01-27	true	Outlier: unusually high energy consumption.
LOG020-T18	humidity	0.11	false	Berlin	SEN-1095	BLD-020	Berlin City Offices	200 Mitte Str	BE	10115	Germany	Reception	2024-04-27T14:40:00	active	0.93	2024-03-01	false	Sensor passed all calibration checks.

What the 120 rows show

from the 120-row sample

Other (sensor type) stands out: mean energy_consumption is 2.0, against 0.29 for the rest.

25%maintenance_required = true
0.23median energy_consumption
5operational statuses
10address countries
28address states
0.84median efficiency_score

Mean energy_consumption by sensor_type120 rows

energy_consumption120 rows, in bands of 0.5

Median 0.23, from 0.0 to 5.0.

address_city120 rows · top 10 of 34 values

Seattle9
Toronto8
Berlin7
Chicago6
London6
Vancouver6
Shanghai6
Detroit5
Paris5
Johannesburg5

19 columns by typefrom the column list below

string 13
float 2
date 1
datetime 1
boolean 2

Columns

19 columns in four groups

blueprint · 19 columns
column	type	description	example
Text 13 columns
`log_id`	string	Unique identifier for each sensor efficiency log entryunique	LOG001-A01
`sensor_id`	string	Unique identifier for the IoT sensor device	SEN-1001
`building_id`	string	Unique identifier for the building where the sensor is installed	BLD-001
`building_name`	string	Name of the buildingoptional	Green Tower
`address_street`	string	Street address of the buildingoptional	123 Main St
`address_city`	string	City where the building is locatedoptional	New York
`address_state`	string	State or region where the building is locatedoptional	NY
`address_postal_code`	string	Postal code of the building addressoptional	10001
`address_country`	string	Country where the building is located10 countries · optional	USA
`sensor_type`	string	Type of IoT sensor (e.g., temperature, occupancy, air quality)7 values	temperature
`sensor_location`	string	Specific location or area within the building where the sensor is installedoptional	Lobby
`operational_status`	string	Current operational status of the sensoractive · inactive · faulty · maintenance · decommissioned	active
`notes`	string	Additional comments or observations related to the sensor or log entryoptional	Sensor operating within n…
Numbers 2 columns
`efficiency_score`	float	Calculated efficiency score for the sensor (0.0 to 1.0, where 1.0 is optimal)0 to 1	0.92
`energy_consumption`	float	Energy consumed by the sensor during the log period (in kWh)0 or more · optional	0.22
Dates and times 2 columns
`timestamp`	datetime	Date and time when the efficiency log was recorded	2024-04-17T09:15:00
`last_maintenance_date`	date	Date of the last maintenance performed on the sensoroptional	2024-02-28
True or false 2 columns
`maintenance_required`	boolean	Indicates if the sensor requires maintenance based on efficiency or status	false
`esg_flag`	boolean	Indicates if the sensor's performance impacts ESG (Environmental, Social, Governance) reportingoptional	true

Use it for

A real estate dashboard
The maintenance_required rate, energy_consumption by sensor_type and a breakdown of address_city. Excel, Power BI or Tableau.
Why do the 10 other rows have a mean energy_consumption of 2.0?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs120
LOG001-A010.22temperat…
LOG003-C220.45air_qual…
LOG006-F120.36motion
A software demo
Believable logs with sensor_id, building_id and building_name to fill a screen in front of a buyer.

This dataset120 rows19 columns

Yours1,000 rows19 columnsaddress_street: UK only

blueprint · real-estate-iot-sensors-efficiency-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 sensor record includes type, location, uptime percentage, and average daily readings
Flag sensors with uptime below 95% for maintenance review
Aggregate energy consumption per building for weekly analysis
Correlate sensor efficiency with building occupancy rates
Include error codes for malfunctioning sensors

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: real-estate-iot-sensors-efficiency-logs

What should your data show?

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Sample rows

What the 120 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?