Logistics
17 columns
121 rows
8 formats

Warehouse IoT Energy Consumption

This dataset provides granular, time-stamped IoT sensor readings of energy consumption across different zones within e-commerce and technology sector warehouses. It includes sensor health, environmental conditions, and operational context, enabling detailed analysis for supply chain optimization, sustainability reporting, and anomaly detection.

last updated 15 Jan 2026
by GoMask

The brief that made it

Analyzing warehouse energy consumption patterns for operational efficiency

Sample rows

preview · 8 of 121 rows · all 17 columns

record_idstring	sensor_statusstring	sensor_battery_levelfloat	is_peak_timeboolean	zone_namestring	warehouse_idstring	warehouse_namestring	zone_idstring	sensor_idstring	sensor_typestring	timestampdatetime	energy_consumed_kwhfloat	interval_minutesinteger	temperature_celsiusfloat	humidity_percentfloat	anomaly_detectedboolean	notesstring
REC001	active	92.6	false	Packing	WH-A	Central Fulfillment	ZN-A1	SEN-A1E01	energy_meter	2024-06-01T08:05:00Z	24.81	15	blank	blank	false	blank
REC002	active	87.4	true	Freezer	WH-B	East Regional Hub	ZN-B2	SEN-B2E02	energy_meter	2024-06-01T09:15:00Z	38.94	30	blank	blank	false	blank
REC003	active	79.8	false	Returns	WH-C	South Logistics	ZN-C1	SEN-C1E03	energy_meter	2024-06-01T10:30:00Z	20.17	15	blank	blank	false	blank
REC004	active	84.2	false	Storage	WH-A	Central Fulfillment	ZN-A2	SEN-A2E04	energy_meter	2024-06-01T11:45:00Z	17.44	15	blank	blank	false	blank
REC005	active	93.5	true	Packing	WH-B	East Regional Hub	ZN-B1	SEN-B1E05	energy_meter	2024-06-01T12:00:00Z	41.63	30	blank	blank	false	blank
REC006	active	77.1	false	Freezer	WH-C	South Logistics	ZN-C2	SEN-C2E06	energy_meter	2024-06-01T13:15:00Z	12.77	15	blank	blank	false	blank
REC007	active	95.2	true	Returns	WH-A	Central Fulfillment	ZN-A3	SEN-A3E07	energy_meter	2024-06-01T14:30:00Z	33.29	30	blank	blank	false	blank
REC008	active	80.8	false	Storage	WH-B	East Regional Hub	ZN-B3	SEN-B3E08	energy_meter	2024-06-01T15:45:00Z	7.68	15	blank	blank	false	blank
REC009	active	86.9	true	Packing	WH-C	South Logistics	ZN-C3	SEN-C3E09	energy_meter	2024-06-01T16:00:00Z	46.11	30	blank	blank	false	blank
REC010	active	88.4	false	Freezer	WH-A	Central Fulfillment	ZN-A4	SEN-A4E10	energy_meter	2024-06-01T17:15:00Z	13.57	15	blank	blank	false	blank
REC011	active	61.3	false	Security	WH-D	North Distribution	ZN-D1	SEN-D1T11	temperature	2024-06-01T08:15:00Z	0	10	22.5	blank	false	blank
REC012	maintenance	11.8	false	Battery Room	WH-E	West Storage	ZN-E2	SEN-E2T12	temperature	2024-06-01T09:30:00Z	0	20	27.9	blank	false	Routine sensor maintenance
REC013	active	48.3	false	Isolation	WH-F	Isolated Depot	ZN-F1	SEN-F1T13	temperature	2024-06-01T10:45:00Z	0	30	18.1	blank	false	blank
REC014	active	67.5	false	Security	WH-D	North Distribution	ZN-D2	SEN-D2H14	humidity	2024-06-01T11:00:00Z	0	20	blank	42.3	false	blank
REC015	maintenance	15.2	false	Battery Room	WH-E	West Storage	ZN-E1	SEN-E1H15	humidity	2024-06-01T12:15:00Z	0	30	blank	59.1	false	Battery check scheduled
REC016	active	54.7	false	Isolation	WH-F	Isolated Depot	ZN-F2	SEN-F2H16	humidity	2024-06-01T13:45:00Z	0	60	blank	35.4	false	blank
REC017	active	73.6	false	Security	WH-D	North Distribution	ZN-D3	SEN-D3O17	other	2024-06-01T14:15:00Z	0	10	blank	blank	false	blank
REC018	maintenance	18.3	false	Battery Room	WH-E	West Storage	ZN-E3	SEN-E3O18	other	2024-06-01T15:00:00Z	0	20	blank	blank	false	Firmware update event
REC019	active	57.2	false	Isolation	WH-F	Isolated Depot	ZN-F3	SEN-F3O19	other	2024-06-01T16:15:00Z	0	30	blank	blank	false	blank
REC020	active	90.1	false	Packing	WH-A	Central Fulfillment	ZN-A5	SEN-A5E20	energy_meter	2024-06-01T18:00:00Z	9.62	15	blank	blank	false	blank

What the 121 rows show

from the 121-row sample

Active (sensor status) stands out: mean sensor_battery_level is 75.3, against 6.6 for the rest.

30%is_peak_time = true
69.0median sensor_battery_level
4sensor types
20warehouses
27warehouse names
6.2median energy_consumed_kwh

Mean sensor_battery_level by sensor_status116 rows

sensor_battery_level116 rows, in bands of 10

Median 69.0, from 0.0 to 100.0.

zone_name119 rows with a value · 2 left blank

Packing29
Freezer18
Returns17
Battery Room12
Isolation11
Security9
Storage6
Test Lab6
Experimental6
Cold Storage3

17 columns by typefrom the column list below

string 9
integer 1
float 4
datetime 1
boolean 2

Columns

17 columns in four groups

blueprint · 17 columns
column	type	description	example
Text 9 columns
`record_id`	string	Unique identifier for each energy consumption recordunique	REC001
`warehouse_id`	string	Unique identifier for the warehouse	WH-A
`warehouse_name`	string	Human-readable name of the warehouseoptional	Central Fulfillment
`zone_id`	string	Unique identifier for the warehouse zone	ZN-A1
`zone_name`	string	Human-readable name of the warehouse zone (e.g., 'Packing', 'Storage')11 names · optional	Packing
`sensor_id`	string	Unique identifier for the IoT sensor	SEN-A1E01
`sensor_type`	string	Type of IoT sensor (e.g., energy_meter, temperature, humidity)energy_meter · temperature · humidity · other	energy_meter
`sensor_status`	string	Operational status of the sensor at the time of readingactive · inactive · error · maintenance	active
`notes`	string	Additional notes or comments about the record (e.g., maintenance events, manual overrides)optional	Battery check scheduled
Numbers 5 columns
`energy_consumed_kwh`	float	Amount of energy consumed in kilowatt-hours during the interval0 or more	24.81
`interval_minutes`	integer	Duration of the measurement interval in minutes1 or more	15
`sensor_battery_level`	float	Sensor battery level as a percentage (0-100)0 to 100 · optional	92.6
`temperature_celsius`	float	Ambient temperature in Celsius at the time of reading (if available)optional	22.5
`humidity_percent`	float	Ambient humidity percentage at the time of reading (if available)0 to 100 · optional	42.3
Dates and times 1 column
`timestamp`	datetime	Date and time when the energy consumption was recorded	2024-06-01T08:05:00Z
True or false 2 columns
`is_peak_time`	boolean	Indicates if the reading was taken during a defined peak energy usage periodoptional	false
`anomaly_detected`	boolean	Indicates if an anomaly was detected in energy consumption for this recordoptional	false

Use it for

A logistics dashboard
The is_peak_time rate, sensor_battery_level by sensor_status and a breakdown of zone_name. Excel, Power BI or Tableau.
Why do the 92 active rows have a mean sensor_battery_level of 75.3?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Records121
REC00192.6active
REC00287.4active
REC00593.5active
A software demo
Believable records with warehouse_id, warehouse_name and zone_id to fill a screen in front of a buyer.

This dataset121 rows17 columns

Yours1,000 rows17 columns

blueprint · warehouse-iot-energy-consumption

Behind this dataset

Same schema. As many rows as you need.

These 121 rows came out of a blueprint — 17 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 daily energy usage per warehouse zone
Include readings from at least three distinct IoT sensor types (temperature, motion, energy meter)
Flag anomalies when consumption exceeds zone historical average by 20%
Assign each reading to specific shift (day/evening/night)
Calculate and include zone-level efficiency score (0-100)

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: warehouse-iot-energy-consumption

What should your data show?

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Sample rows

What the 121 rows show

Columns

Use it for

A logistics dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Logistics

What should your data show?