Smart Irrigation Sensor Analytics
This dataset provides detailed, time-stamped logs from smart irrigation sensors deployed across agricultural farms. It captures water usage, system uptime, environmental conditions, sustainability scores, and compliance flags, enabling precision farming, operational efficiency analysis, and regulatory reporting. The dataset supports granular monitoring and optimization of irrigation practices for sustainable agriculture.
Sample rows
preview · 8 of 120 rows · all 15 columns| log_idstring | irrigation_statusstring | system_uptime_secondsinteger | compliance_flagboolean | farm_idstring | sensor_idstring | zone_idstring | timestampdatetime | water_usage_litersfloat | energy_consumption_kwhfloat | soil_moisture_percentfloat | ambient_temperature_celsiusfloat | rainfall_mmfloat | sustainability_scorefloat | manager_idstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| LOG00001 | running | 78000 | false | FARM-001 | SENSOR-A1 | ZONE-1A | 2024-05-01T09:15:23Z | 1820.4 | 14.56 | 24.1 | 36.8 | 0 | 42.7 | MGR-01 |
| LOG00002 | running | 65000 | false | FARM-003 | SENSOR-C2 | ZONE-2B | 2024-05-01T11:08:45Z | 1309.2 | 11.3 | 35.2 | 31.1 | 0 | 55.9 | MGR-02 |
| LOG00003 | stopped | 0 | true | FARM-002 | SENSOR-B3 | ZONE-3A | 2024-05-01T06:24:17Z | 0 | 0 | 96.5 | 10.3 | 34.2 | 98.6 | MGR-04 |
| LOG00004 | maintenance | 4200 | true | FARM-004 | SENSOR-D4 | ZONE-4C | 2024-05-01T14:52:32Z | 135.8 | 1.57 | 53.6 | 22.5 | 8.9 | 78.2 | MGR-03 |
| LOG00005 | stopped | 0 | true | FARM-005 | SENSOR-E5 | ZONE-5A | 2024-05-01T16:30:07Z | 0 | 0 | 87.9 | 15.2 | 27.1 | 94.3 | MGR-05 |
| LOG00006 | running | 81200 | false | FARM-006 | SENSOR-F6 | ZONE-6B | 2024-05-01T17:02:55Z | 1786.5 | 17.1 | 17.5 | 41.6 | 0 | 21.3 | MGR-01 |
| LOG00007 | stopped | 0 | true | FARM-002 | SENSOR-G7 | ZONE-7C | 2024-05-01T20:11:41Z | 0 | 0 | 92.3 | 11.8 | 41.3 | 99.6 | MGR-07 |
| LOG00008 | maintenance | 3300 | true | FARM-003 | SENSOR-H8 | ZONE-8A | 2024-05-02T05:32:18Z | 88.5 | 0.41 | 68.2 | 18.7 | 7.6 | 71.8 | MGR-02 |
| LOG00009 | stopped | 0 | true | FARM-001 | SENSOR-I9 | ZONE-9B | 2024-05-02T07:23:09Z | 0 | 0 | 93.4 | 9.1 | 49.7 | 99.9 | MGR-04 |
| LOG00010 | running | 70300 | false | FARM-002 | SENSOR-J1 | ZONE-10C | 2024-05-02T09:37:50Z | 1222.7 | 10.9 | 22.8 | 33.5 | 0 | 48.5 | MGR-08 |
| LOG00011 | maintenance | 1600 | blank | FARM-004 | SENSOR-K2 | ZONE-11A | 2024-05-02T11:59:14Z | 59.2 | 0.34 | 45.2 | 24 | 4.8 | 68.9 | MGR-03 |
| LOG00012 | error | 0 | false | FARM-005 | SENSOR-L3 | ZONE-12B | 2024-05-02T13:44:27Z | 0 | 0 | blank | blank | 0 | blank | MGR-05 |
| LOG00013 | stopped | 0 | true | FARM-006 | SENSOR-M4 | ZONE-13A | 2024-05-02T15:27:19Z | 0 | 0 | 99.9 | 8 | 44 | 97.2 | MGR-01 |
| LOG00014 | running | 84100 | false | FARM-001 | SENSOR-N5 | ZONE-14C | 2024-05-02T17:15:11Z | 1643.2 | 15.8 | 28.9 | 38.6 | 0 | 31.2 | MGR-08 |
| LOG00015 | maintenance | 3800 | true | FARM-002 | SENSOR-O6 | ZONE-15A | 2024-05-02T18:53:44Z | 210.7 | 2.03 | 62.8 | 19.4 | 12.6 | 86.1 | MGR-10 |
| LOG00016 | error | 0 | true | FARM-003 | SENSOR-P7 | ZONE-16B | 2024-05-02T20:37:12Z | 0 | 0 | 81.7 | 13.2 | 17.4 | 90.3 | MGR-02 |
| LOG00017 | stopped | 0 | true | FARM-004 | SENSOR-Q8 | ZONE-17C | 2024-05-03T02:12:36Z | 0 | 0 | 85.3 | 18.1 | 34.8 | 92.8 | MGR-03 |
| LOG00018 | stopped | 0 | true | FARM-005 | SENSOR-R9 | ZONE-18A | 2024-05-03T04:23:57Z | 0 | 0 | 98.7 | 17.6 | 22.5 | 99 | MGR-05 |
| LOG00019 | error | 0 | true | FARM-006 | SENSOR-S1 | ZONE-19B | 2024-05-03T07:15:39Z | 0 | 0 | 94.1 | 14.2 | 39.2 | 89.5 | MGR-07 |
| LOG00020 | running | 82000 | false | FARM-001 | SENSOR-T2 | ZONE-20C | 2024-05-03T09:48:18Z | 1078.8 | 13.9 | 27.3 | 37.7 | 0 | 44.3 | MGR-10 |
What the 120 rows show
from the 120-row sampleRunning (irrigation status) stands out: mean system_
- 68%compliance_
flag = true - 0median system_
uptime_ seconds - 13managers
- 0.0median water_
usage_ liters - 0.0median energy_
consumption_ kwh - 67.3median soil_
moisture_ percent
Median 0, from 0 to 86,400.
- string 6
- integer 1
- float 6
- datetime 1
- boolean 1
Columns
15 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 6 columns | |||
log_id | string | Unique identifier for each sensor log entryunique | LOG00001 |
sensor_id | string | Unique identifier for the IoT sensor device | SENSOR-A1 |
farm_id | string | Unique identifier for the farm where the sensor is deployed | FARM-001 |
zone_id | string | Identifier for the irrigation zone within the farm | ZONE-1A |
irrigation_status | string | Operational status of the irrigation system during the log (e.g., running, stopped, error)running · stopped · error · maintenance | running |
manager_id | string | Identifier for the agriculture operations manager responsible for the farmoptional | MGR-01 |
| Numbers 7 columns | |||
water_usage_liters | float | Amount of water used during the logged interval, in liters0 or more | 1820.4 |
system_uptime_seconds | integer | Total uptime of the irrigation system in seconds during the logged interval0 or more | 78000 |
energy_consumption_kwh | float | Energy consumed by the irrigation system in kilowatt-hours during the logged interval0 or more · optional | 14.56 |
soil_moisture_percent | float | Measured soil moisture as a percentage at the time of logging0 to 100 · optional | 24.1 |
ambient_temperature_celsius | float | Ambient temperature at the sensor location in degrees Celsiusoptional | 36.8 |
rainfall_mm | float | Rainfall measured at the sensor location in millimeters during the logged interval0 or more · optional | 0 |
sustainability_score | float | Calculated score representing sustainability performance for the logged interval (0-100)0 to 100 · optional | 42.7 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time when the sensor log was recorded | 2024-05-01T09:15:23Z |
| True or false 1 column | |||
compliance_flag | boolean | Indicates whether the irrigation activity complies with regulatory or internal standardsoptional | false |
Use it for
An agriculture dashboard
The compliance_
flag rate, system_ uptime_ seconds by irrigation_ status and a breakdown of farm_ id. Excel, Power BI or Tableau. Why do the 30 running rows have a mean system_
uptime_ seconds of 66,031? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Logs120LOG0000178000runningLOG000030stoppedLOG000044200maintena…
A software demo
Believable logs with sensor_
id, farm_ id and zone_ id to fill a screen in front of a buyer.
This dataset120 rows15 columns
Yours1,000 rows15 columns
blueprint · smart-irrigation-sensor-analytics
Behind this dataset
Same schema. As many rows as you need.
These 120 rows came out of a blueprint — 15 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 reports hourly water usage in liters.
- System downtime must not exceed 2 hours per week.
- Sensors flag abnormal moisture readings for further inspection.
- Monthly sustainability reports aggregate total water savings.
- Data includes sensor model, farm zone, and operational status.
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-analytics