Smart Building Occupancy Analytics
This dataset provides detailed, timestamped occupancy and utilization readings from smart sensors deployed across zones in commercial buildings. It enables granular analysis of space usage, energy consumption, and ESG compliance at the building, floor, and zone levels, supporting data-driven decisions for facilities management, energy optimization, and workplace planning.
Sample rows
preview · 8 of 96 rows · all 18 columns| record_idstring | occupancy_statusstring | utilization_percentagefloat | esg_compliance_flagboolean | zone_typestring | timestampdatetime | building_idstring | building_namestring | floor_numberinteger | zone_idstring | sensor_idstring | sensor_typestring | occupancy_countinteger | zone_capacityinteger | energy_consumption_kwfloat | sensor_health_statusstring | latitudefloat | longitudefloat |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rec-00001 | occupied | 70 | true | meeting_room | 2024-06-10T08:15:00Z | BLDG-A1 | Centennial Tower | 3 | Z-301 | SN-301-MR-001 | PIR | 7 | 10 | 2.3 | active | 37.7749 | -122.4194 |
| rec-00002 | occupied | 60 | true | lobby | 2024-06-10T09:00:00Z | BLDG-B2 | Greenfield Plaza | 0 | Z-LB-01 | SN-LB-01-02 | camera | 12 | 20 | 4.7 | active | 34.0522 | -118.2437 |
| rec-00003 | occupied | 86.4 | true | open_office | 2024-06-10T10:20:00Z | BLDG-C3 | Tech Hub North | 5 | Z-501 | SN-501-OF-01 | CO2 | 38 | 44 | 16.5 | active | 40.7128 | -74.006 |
| rec-00004 | occupied | 100 | true | private_office | 2024-06-10T11:10:00Z | BLDG-A1 | Centennial Tower | 2 | Z-201 | SN-201-PO-03 | badge | 1 | 1 | 0.4 | active | 37.7751 | -122.4192 |
| rec-00005 | unoccupied | 0 | true | restroom | 2024-06-10T12:32:00Z | BLDG-B2 | Greenfield Plaza | 1 | Z-101 | SN-101-RM-01 | PIR | 0 | 6 | 0.9 | active | 34.0523 | -118.2438 |
| rec-00006 | occupied | 44 | true | cafeteria | 2024-06-10T08:47:00Z | BLDG-C3 | Tech Hub North | 7 | Z-701 | SN-701-CF-02 | camera | 22 | 50 | 9.2 | active | 40.7132 | -74.0058 |
| rec-00007 | occupied | 77.5 | true | open_office | 2024-06-10T09:38:00Z | BLDG-A1 | Centennial Tower | 3 | Z-302 | SN-302-OF-02 | desk | 31 | 40 | 12.4 | active | 37.7747 | -122.4196 |
| rec-00008 | occupied | 8 | false | corridor | 2024-06-10T10:54:00Z | BLDG-B2 | Greenfield Plaza | 2 | Z-202 | SN-202-CD-01 | PIR | 2 | 25 | 1.6 | active | 34.0525 | -118.2439 |
| rec-00009 | occupied | 66.7 | true | meeting_room | 2024-06-10T11:40:00Z | BLDG-C3 | Tech Hub North | 1 | Z-101 | SN-101-MR-01 | CO2 | 10 | 15 | 3.7 | active | 40.713 | -74.0062 |
| rec-00010 | occupied | 25 | false | lobby | 2024-06-10T10:01:00Z | BLDG-A1 | Centennial Tower | 0 | Z-LB-02 | SN-LB-02-01 | badge | 5 | 20 | 2.1 | active | 37.775 | -122.4195 |
| rec-00011 | occupied | 50 | true | restroom | 2024-06-10T11:17:00Z | BLDG-B2 | Greenfield Plaza | 2 | Z-203 | SN-203-RM-02 | PIR | 3 | 6 | 1.2 | active | 34.0526 | -118.244 |
| rec-00012 | occupied | 92 | true | open_office | 2024-06-10T12:23:00Z | BLDG-C3 | Tech Hub North | 8 | Z-801 | SN-801-OF-03 | desk | 46 | 50 | 18.7 | active | 40.7134 | -74.0061 |
| rec-00013 | occupied | 66 | true | cafeteria | 2024-06-10T09:19:00Z | BLDG-A1 | Centennial Tower | 4 | Z-401 | SN-401-CF-01 | CO2 | 33 | 50 | 11.5 | active | 37.7746 | -122.4198 |
| rec-00014 | unoccupied | 0 | true | corridor | 2024-06-10T08:25:00Z | BLDG-B2 | Greenfield Plaza | 1 | Z-102 | SN-102-CD-01 | PIR | 0 | 30 | 0.7 | active | 34.0527 | -118.2441 |
| rec-00015 | occupied | 100 | true | private_office | 2024-06-10T09:59:00Z | BLDG-C3 | Tech Hub North | 6 | Z-601 | SN-601-PO-04 | desk | 1 | 1 | 0.6 | active | 40.7135 | -74.0063 |
| rec-00016 | occupied | 40 | false | meeting_room | 2024-06-10T11:53:00Z | BLDG-A1 | Centennial Tower | 2 | Z-202 | SN-202-MR-02 | camera | 4 | 10 | 1.7 | active | 37.7748 | -122.4197 |
| rec-00017 | occupied | 92.5 | true | open_office | 2024-06-10T10:42:00Z | BLDG-B2 | Greenfield Plaza | 3 | Z-301 | SN-301-OF-04 | CO2 | 37 | 40 | 15.9 | active | 34.053 | -118.2442 |
| rec-00018 | occupied | 4 | false | corridor | 2024-06-10T08:55:00Z | BLDG-C3 | Tech Hub North | 7 | Z-702 | SN-702-CD-02 | PIR | 1 | 25 | 1.1 | active | 40.7136 | -74.0064 |
| rec-00019 | occupied | 97.5 | true | open_office | 2024-06-10T10:32:00Z | BLDG-A1 | Centennial Tower | 5 | Z-501 | SN-501-OF-05 | desk | 39 | 40 | 16.7 | active | 37.7745 | -122.4199 |
| rec-00020 | occupied | 82 | true | cafeteria | 2024-06-10T11:29:00Z | BLDG-B2 | Greenfield Plaza | 4 | Z-401 | SN-401-CF-03 | camera | 41 | 50 | 13.4 | active | 34.0531 | -118.2443 |
What the 96 rows show
from the 96-row sampleOccupied (occupancy status) stands out: mean utilization_
- 82%esg_
compliance_ flag = true - 65.0median utilization_
percentage - 5buildings
- 5building names
- 5sensor types
- 6.5median occupancy_
count
Median 65.0, from 0.0 to 100.0.
- string 9
- integer 3
- float 4
- datetime 1
- boolean 1
Columns
18 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 9 columns | |||
record_id | string | Unique identifier for each occupancy sensor reading recordunique | rec-00001 |
building_id | string | Unique identifier for the building where the sensor is located5 buildings | BLDG-A1 |
building_name | string | Human-readable name of the building5 names · optional | Centennial Tower |
zone_id | string | Unique identifier for the specific zone or area within a floor (e.g., conference room, open office) | Z-301 |
zone_type | string | Type of zone (e.g., meeting_room, open_office, restroom, corridor, lobby)8 values | meeting_room |
sensor_id | string | Unique identifier for the occupancy sensor device | SN-301-MR-001 |
sensor_type | string | Type of sensor (e.g., PIR, camera, desk, badge, CO2)6 values | PIR |
occupancy_status | string | Occupancy status as detected by the sensor (e.g., occupied, unoccupied, unknown)occupied · unoccupied · unknown | occupied |
sensor_health_status | string | Operational status of the sensor (e.g., active, inactive, maintenance, error)active · inactive · maintenance · error · optional | active |
| Numbers 7 columns | |||
floor_number | integer | Floor number within the building where the sensor is installed0 or more | 3 |
occupancy_count | integer | Number of people detected by the sensor at the given timestamp0 or more | 7 |
utilization_percentage | float | Percentage of the zone's capacity currently utilized (0-100)0 to 100 · optional | 70 |
zone_capacity | integer | Maximum occupancy capacity for the zone1 or more · optional | 10 |
energy_consumption_kw | float | Energy consumption in kilowatts for the zone at the time of reading (if available)0 or more · optional | 2.3 |
latitude | float | Latitude coordinate of the sensor location-90 to 90 · optional | 37.7749 |
longitude | float | Longitude coordinate of the sensor location-180 to 180 · optional | -122.4194 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time when the sensor reading was recorded (in UTC) | 2024-06-10T08:15:00Z |
| True or false 1 column | |||
esg_compliance_flag | boolean | Indicates if the zone is currently meeting ESG (Environmental, Social, and Governance) occupancy efficiency targetsoptional | true |
Use it for
A real estate dashboard
The esg_
compliance_ flag rate, utilization_ percentage by occupancy_ status and a breakdown of zone_ type. Excel, Power BI or Tableau. Why do the 85 occupied rows have a mean utilization_
percentage of 65.5? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Records96rec-0000170occupiedrec-0000260occupiedrec-000088occupied
A software demo
Believable records with timestamp, building_
id and building_ name to fill a screen in front of a buyer.
This dataset96 rows18 columns
Yours1,000 rows18 columns
blueprint · smart-building-occupancy-analytics
Behind this dataset
Same schema. As many rows as you need.
These 96 rows came out of a blueprint — 18 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 time interval and zone.
- Occupancy count is derived from IoT sensor readings, with noise below threshold flagged.
- Includes HVAC and lighting adjustment triggers based on occupancy.
- Logs non-occupancy periods for anomaly detection and ESG reporting.
- Sensor calibration status must be recorded for each zone.
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-building-occupancy-analytics