Agriculture
19 columns
74 rows
8 formats

Smart Irrigation Sensor Efficiency Log

This dataset records detailed logs from IoT-enabled irrigation sensors, capturing water usage, soil moisture changes, environmental conditions, and energy consumption for precision agriculture. Designed for agri-tech startups and farm managers, it enables optimization of irrigation schedules, reduction of water waste, and robust ESG sustainability reporting. The comprehensive schema supports advanced analytics for resource efficiency and environmental compliance.

last updated 11 Jan 2026
by GoMask

The brief that made it

Optimize irrigation schedules and water usage based on sensor data

Sample rows

preview · 8 of 74 rows · all 19 columns

log_idstring	irrigation_methodstring	soil_moisture_afterfloat	esg_compliance_flagboolean	farm_idstring	sensor_idstring	plot_idstring	timestampdatetime	irrigation_event_idstring	water_volume_litersfloat	duration_minutesfloat	soil_moisture_beforefloat	ambient_temperature_cfloat	humidity_percentfloat	rainfall_mmfloat	sensor_statusstring	water_sourcestring	energy_consumed_kwhfloat	notesstring
IRR-LOG-001A	drip	24.1	true	FARM-01	SEN-1001	PLOT-1A	2024-06-01T06:20:00	EVT-20240601-001	950.5	45	17.2	21.5	62	0	active	well	2.1	Routine morning irrigation
IRR-LOG-001B	sprinkler	30.2	true	FARM-01	SEN-1002	PLOT-1B	2024-06-01T06:35:00	EVT-20240601-002	1200	60	19	22.1	58	0	active	municipal	3.5	Higher volume due to dry spell
IRR-LOG-001C	drip	20.8	true	FARM-02	SEN-1010	PLOT-2A	2024-06-01T07:10:00	EVT-20240601-003	800.2	38.5	14.5	20.9	65	0	active	river	1.7	Sensor calibrated last week
IRR-LOG-001D	sprinkler	27.6	true	FARM-02	SEN-1011	PLOT-2B	2024-06-01T07:20:00	EVT-20240601-004	1100	55	20.1	21.2	64	0	active	pond	3.1	Sprinkler system checked
IRR-LOG-001E	drip	18.2	true	FARM-02	SEN-1012	PLOT-2C	2024-06-01T08:05:00	EVT-20240601-005	650	30	12.8	19.8	68	0	active	rainwater	1.2	Rainwater utilized for sustainability
IRR-LOG-001F	flood	39.2	false	FARM-03	SEN-1013	PLOT-3A	2024-06-01T08:45:00	EVT-20240601-006	1500	80	25	23.5	55	1.2	active	river	4.8	Flood method used after river level rise
IRR-LOG-001G	pivot	23	true	FARM-03	SEN-1014	PLOT-3B	2024-06-01T09:15:00	EVT-20240601-007	900	40	15.5	21	61	0	active	well	2.6	Pivot system checked for leaks
IRR-LOG-001H	drip	15.3	true	FARM-03	SEN-1015	PLOT-3C	2024-06-01T09:30:00	EVT-20240601-008	500	25	10.2	20	70	0.8	active	pond	0.9	Short drip cycle for seedlings
IRR-LOG-001I	flood	42	false	FARM-04	SEN-1020	PLOT-4A	2024-06-01T10:00:00	EVT-20240601-009	1750	90	27.5	24.2	52	0	active	river	5.2	Flooding event due to crop requirement
IRR-LOG-001J	sprinkler	23.8	true	FARM-04	SEN-1021	PLOT-4B	2024-06-01T10:35:00	EVT-20240601-010	850	37	16.3	21.9	63	0	active	municipal	2.9	Sprinkler scheduled for lettuce plot
IRR-LOG-001K	drip	26.7	true	FARM-04	SEN-1022	PLOT-4C	2024-06-01T11:05:00	EVT-20240601-011	1000	48	18.9	22.6	59	0	active	rainwater	2	Rainwater harvested for sustainability
IRR-LOG-001L	drip	19.5	true	FARM-05	SEN-1023	PLOT-5A	2024-06-01T11:40:00	EVT-20240601-012	700	32	13.5	20.3	67	0	active	well	1.5	Well water, routine maintenance
IRR-LOG-001M	drip	17.1	true	FARM-05	SEN-1024	PLOT-5B	2024-06-01T11:55:00	EVT-20240601-013	600	28	12.2	19.6	72	0	active	pond	1.1	Low energy consumption event
IRR-LOG-001N	flood	46.5	false	FARM-05	SEN-1025	PLOT-5C	2024-06-01T12:25:00	EVT-20240601-014	2000	105	29	25.2	52	1.7	active	river	6.1	Flood event post rainfall
IRR-LOG-001O	pivot	22.5	true	FARM-06	SEN-1026	PLOT-6A	2024-06-01T13:05:00	EVT-20240601-015	950	42	15	23	60	0	active	municipal	2.4	Pivot used for high coverage
IRR-LOG-001P	sprinkler	33.7	true	FARM-06	SEN-1027	PLOT-6B	2024-06-01T13:40:00	EVT-20240601-016	1200	62	22	24.1	55	0	active	well	3.2	Sprinkler event after midday
IRR-LOG-001Q	drip	19.8	true	FARM-06	SEN-1028	PLOT-6C	2024-06-01T14:10:00	EVT-20240601-017	750	35	13.9	20.9	63	0	active	rainwater	1.4	Rainwater system recently installed
IRR-LOG-001R	pivot	24.2	true	FARM-07	SEN-1029	PLOT-7A	2024-06-01T14:45:00	EVT-20240601-018	900	40	16.8	22.8	58	0	active	municipal	2.7	Pivot system checked for coverage
IRR-LOG-001S	flood	51.2	false	FARM-07	SEN-1030	PLOT-7B	2024-06-01T15:15:00	EVT-20240601-019	1800	98	31.4	26.4	50	2	active	river	5.7	Flood event post heavy rainfall
IRR-LOG-001T	drip	17.4	true	FARM-07	SEN-1031	PLOT-7C	2024-06-01T15:40:00	EVT-20240601-020	650	31	11.7	20.6	69	0	active	well	1.2	Drip system for new crop

What the 74 rows show

from the 74-row sample

Flood (irrigation method) stands out: mean soil_moisture_after is 39.6, against 25.0 for the rest.

83%esg_compliance_flag = true
26.4median soil_moisture_after
4sensor statuses
5water sources
625.0median water_volume_liters
40.8median duration_minutes

Mean soil_moisture_after by irrigation_method74 rows

soil_moisture_after74 rows, in bands of 5

Median 26.4, from 13.8 to 51.2.

farm_id74 rows · top 10 of 22 values

farm-PNW-027
farm-NE-057
farm-MIDW-036
farm-SW-075
farm-MIDW-044
farm-SW-064
FARM-023
FARM-033
FARM-043
FARM-053

19 columns by typefrom the column list below

string 9
float 8
datetime 1
boolean 1

Columns

19 columns in four groups

blueprint · 19 columns
column	type	description	example
Text 9 columns
`log_id`	string	Unique identifier for each sensor efficiency log entryunique	IRR-LOG-001A
`sensor_id`	string	Unique identifier for the IoT irrigation sensor	SEN-1001
`farm_id`	string	Unique identifier for the farm or agricultural site	FARM-01
`plot_id`	string	Identifier for the specific plot or field within the farm	PLOT-1A
`irrigation_event_id`	string	Identifier for the specific irrigation event	EVT-20240601-001
`sensor_status`	string	Operational status of the sensor at the time of loggingactive · inactive · error · maintenance	active
`irrigation_method`	string	Type of irrigation method used (e.g., drip, sprinkler, flood)drip · sprinkler · flood · pivot · other	drip
`water_source`	string	Source of water used for irrigation (e.g., well, river, rainwater)6 values	well
`notes`	string	Additional notes or comments about the irrigation eventoptional	Sprinkler system checked
Numbers 8 columns
`water_volume_liters`	float	Volume of water dispensed during the irrigation event, in liters0 or more	950.5
`duration_minutes`	float	Duration of the irrigation event in minutes0 or more	45
`soil_moisture_before`	float	Soil moisture percentage measured before irrigation0 to 100	17.2
`soil_moisture_after`	float	Soil moisture percentage measured after irrigation0 to 100	24.1
`ambient_temperature_c`	float	Ambient temperature at the time of irrigation, in Celsius-50 to 60 · optional	21.5
`humidity_percent`	float	Relative humidity at the time of irrigation, percentage0 to 100 · optional	62
`rainfall_mm`	float	Rainfall amount in millimeters during the irrigation event0 or more · optional	0
`energy_consumed_kwh`	float	Energy consumed by the irrigation system during the event, in kWh0 or more · optional	2.1
Dates and times 1 column
`timestamp`	datetime	Date and time when the sensor log was recorded	2024-06-01T06:20:00
True or false 1 column
`esg_compliance_flag`	boolean	Indicates if the irrigation event meets ESG sustainability criteriaoptional	true

Use it for

An agriculture dashboard
The esg_compliance_flag rate, soil_moisture_after by irrigation_method and a breakdown of farm_id. Excel, Power BI or Tableau.
Why do the 14 flood rows have a mean soil_moisture_after of 39.6?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs74
IRR-LOG-001A24.1drip
IRR-LOG-001B30.2sprinkler
IRR-LOG-001F39.2flood
A software demo
Believable logs with sensor_id, farm_id and plot_id to fill a screen in front of a buyer.

This dataset74 rows19 columns

Yours1,000 rows19 columns

blueprint · smart-irrigation-sensor-efficiency-log

Behind this dataset

Same schema. As many rows as you need.

These 74 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 row represents a unique irrigation event triggered by a sensor.
Include sensor ID, field location, soil moisture % before/after, valve status, and duration.
Record ambient weather conditions (temperature, rainfall) at event time.
Flag events exceeding recommended water thresholds for compliance review.
Associate every event with crop type and growth stage.

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: smart-irrigation-sensor-efficiency-log

What should your data show?

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Sample rows

What the 74 rows show

Columns

Use it for

An agriculture dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Agriculture

What should your data show?