Smart Irrigation Sensor Metrics
This dataset provides comprehensive, time-stamped sensor metrics from smart irrigation systems deployed across agricultural fields. It includes environmental readings, operational statuses, anomaly flags, and contextual field/crop information, enabling agri-tech teams and sustainability officers to monitor irrigation efficiency, detect issues, and benchmark performance for improved crop yield and water conservation.
Sample rows
preview · 8 of 85 rows · all 17 columns| sensor_metric_idstring | irrigation_statusstring | soil_moisturefloat | anomaly_detectedboolean | sensor_idstring | field_idstring | field_namestring | location_latitudefloat | location_longitudefloat | timestampdatetime | temperaturefloat | humidityfloat | water_flow_ratefloat | anomaly_typestring | battery_levelfloat | crop_typestring | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SM001 | on | 37.4 | false | SEN-A01 | F01 | North Pasture | 38.1102 | -121.3014 | 2024-06-01T09:15:00 | 22.5 | 54.8 | 8.2 | blank | 76.2 | corn | Morning irrigation cycle |
| SM002 | scheduled | 29.7 | false | SEN-A02 | F02 | East Orchard | 38.1127 | -121.2985 | 2024-06-01T10:02:00 | 21.9 | 63.1 | 7 | blank | 83.4 | apples | blank |
| SM003 | on | 41.2 | false | SEN-A03 | F03 | South Meadow | 38.1056 | -121.3042 | 2024-06-01T11:21:00 | 23.8 | 49.6 | 9.5 | blank | 59.7 | alfalfa | High efficiency reading |
| SM004 | manual | 36.6 | false | SEN-A01 | F01 | North Pasture | 38.1103 | -121.3012 | 2024-06-01T12:03:00 | 25.1 | 52.3 | 8.6 | blank | 74.8 | corn | blank |
| SM005 | on | 58.3 | false | SEN-A04 | F04 | West Field | 38.1089 | -121.2999 | 2024-06-01T13:44:00 | 20.6 | 67.2 | 11.1 | blank | 82.1 | soybeans | Soil moisture above average |
| SM006 | scheduled | 18.9 | false | SEN-A05 | F05 | Central Plot | 38.1134 | -121.2971 | 2024-06-01T14:27:00 | 27.7 | 44.6 | 6.5 | blank | 68.9 | lettuce | Low moisture detected |
| SM007 | on | 77.2 | false | SEN-A06 | F06 | Greenhouse | 38.1157 | -121.2963 | 2024-06-01T15:13:00 | 30.4 | 72 | 13.8 | blank | 90.6 | tomatoes | blank |
| SM008 | off | 27.5 | false | SEN-A02 | F02 | East Orchard | 38.1128 | -121.2986 | 2024-06-01T16:22:00 | 19.7 | 61.4 | 7.2 | blank | 81.2 | apples | Irrigation system idle |
| SM009 | manual | 45.9 | false | SEN-A07 | F07 | Berry Patch | 38.1171 | -121.2952 | 2024-06-01T17:05:00 | 24.2 | 58.7 | 9.9 | blank | 64.3 | strawberries | blank |
| SM010 | scheduled | 50.7 | false | SEN-A08 | F08 | Pumpkin Patch | 38.1203 | -121.2938 | 2024-06-01T18:16:00 | 22.8 | 60.5 | 10.7 | blank | 72.5 | pumpkins | blank |
| SM011 | on | 39.1 | false | SEN-A03 | F03 | South Meadow | 38.1058 | -121.3043 | 2024-06-01T19:09:00 | 21.5 | 53.4 | 8.8 | blank | 58.7 | alfalfa | Evening cycle |
| SM012 | on | 85.3 | false | SEN-A09 | F09 | Rice Paddies | 38.1218 | -121.2921 | 2024-06-01T20:35:00 | 26.4 | 79.7 | 14.2 | blank | 91.7 | rice | Flooded field |
| SM013 | off | 31.2 | false | SEN-A10 | F10 | Vineyard | 38.1232 | -121.2903 | 2024-06-01T21:14:00 | 20.3 | 49.1 | 7.5 | blank | 79 | grapes | blank |
| SM014 | scheduled | 62.4 | false | SEN-A04 | F04 | West Field | 38.1091 | -121.2997 | 2024-06-02T07:17:00 | 18.7 | 70.1 | 12.3 | blank | 80.5 | soybeans | Early morning cycle |
| SM015 | manual | 21.7 | false | SEN-A05 | F05 | Central Plot | 38.1137 | -121.2974 | 2024-06-02T08:30:00 | 26.9 | 39.8 | 5.4 | blank | 67.8 | lettuce | blank |
| SM016 | on | 80.5 | false | SEN-A06 | F06 | Greenhouse | 38.1158 | -121.2961 | 2024-06-02T09:12:00 | 31.2 | 75.4 | 14.7 | blank | 88.3 | tomatoes | Humidity high |
| SM017 | scheduled | 43.2 | false | SEN-A07 | F07 | Berry Patch | 38.1174 | -121.2956 | 2024-06-02T10:25:00 | 22.4 | 56.2 | 10.2 | blank | 62.5 | strawberries | Scheduled for next batch |
| SM018 | manual | 48.9 | false | SEN-A08 | F08 | Pumpkin Patch | 38.1207 | -121.2937 | 2024-06-02T11:41:00 | 23.9 | 59.3 | 9.8 | blank | 71.1 | pumpkins | Manual override |
| SM019 | on | 87.1 | false | SEN-A09 | F09 | Rice Paddies | 38.122 | -121.2925 | 2024-06-02T12:52:00 | 27.9 | 82.4 | 15.1 | blank | 89.6 | rice | blank |
| SM020 | off | 33.5 | false | SEN-A10 | F10 | Vineyard | 38.1234 | -121.2907 | 2024-06-02T13:33:00 | 19.5 | 47.8 | 6.9 | blank | 77.6 | grapes | blank |
What the 85 rows show
from the 85-row sampleOn (irrigation status) stands out: mean soil_
- 11%anomaly_
detected = true - 43.2median soil_
moisture - 24.2median temperature
- 56.2median humidity
- 10.7median water_
flow_ rate - 76.3median battery_
level
Median 43.2, from 18.9 to 90.2.
- string 8
- float 7
- datetime 1
- boolean 1
Columns
17 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 8 columns | |||
sensor_metric_id | string | Unique identifier for each sensor metric recordunique | SM001 |
sensor_id | string | Unique identifier for the sensor device | SEN-A01 |
field_id | string | Unique identifier for the agricultural field or plot | F01 |
field_name | string | Human-readable name or label for the field or plotoptional | North Pasture |
irrigation_status | string | Current operational status of the irrigation system at the sensor locationon · off · scheduled · manual · error | on |
anomaly_type | string | Type of anomaly detected (if any), e.g., 'leak', 'sensor_failure', 'overwatering'3 types · optional | leak |
crop_type | string | Type of crop being cultivated in the fieldoptional | corn |
notes | string | Additional notes or comments about the metric or sensor readingoptional | Morning irrigation cycle |
| Numbers 7 columns | |||
location_latitude | float | Latitude coordinate of the sensor's location-90 to 90 | 38.1102 |
location_longitude | float | Longitude coordinate of the sensor's location-180 to 180 | -121.3014 |
soil_moisture | float | Measured soil moisture percentage at the sensor location0 to 100 | 37.4 |
temperature | float | Ambient temperature in degrees Celsius at the sensor location-50 to 60 · optional | 22.5 |
humidity | float | Relative humidity percentage at the sensor location0 to 100 · optional | 54.8 |
water_flow_rate | float | Measured water flow rate in liters per minute through the irrigation system0 or more · optional | 8.2 |
battery_level | float | Current battery level of the sensor device as a percentage0 to 100 · optional | 76.2 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time when the metric was recorded | 2024-06-01T09:15:00 |
| True or false 1 column | |||
anomaly_detected | boolean | Indicates if an anomaly was detected in the sensor data | false |
Use it for
An agriculture dashboard
The anomaly_
detected rate, soil_ moisture by irrigation_ status and a breakdown of sensor_ id. Excel, Power BI or Tableau. Why do the 29 on rows have a mean soil_
moisture of 59.0? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Sensor metrics85SM00137.4onSM03468.1onSM03684.1on
A software demo
Believable sensor metrics with sensor_
id, field_ id and field_ name to fill a screen in front of a buyer.
This dataset85 rows17 columns
Yours10,000 rows17 columnslocation_latitude: UK only
blueprint · smart-irrigation-sensor-metrics
Behind this dataset
Same schema. As many rows as you need.
These 85 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 one sensor reading at a unique timestamp.
- Include soil moisture, temperature, and water flow rate from IoT sensors.
- Flag readings outside optimal ranges for alerting.
- Calculate daily water usage per field segment.
- Tag anomalous sensor patterns for maintenance review.
Open the blueprint in Data Factory
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- smart-irrigation-sensor-metrics