Remote Irrigation IoT Logs

This dataset provides granular operational logs from networked agricultural IoT devices used in remote irrigation systems. It includes device metadata, event types, sensor readings, water usage statistics, and anomaly reports, enabling advanced analytics for optimizing irrigation, detecting faults, and supporting sustainable water management. Ideal for AI/ML teams seeking actionable insights into smart agriculture operations.

  • last updated 28 Dec 2025
  • by GoMask
The brief that made it

Optimizing irrigation schedules and water usage through data-driven analysis

Sample rows

preview · 8 of 120 rows · all 21 columns
log_idstringstatusstringsignal_strength_dbmfloatfield_idstringdevice_idstringtimestampdatetimefarm_idstringdevice_typestringevent_typestringsoil_moisturefloattemperature_celsiusfloathumidity_percentfloatwater_flow_rate_lpmfloatirrigation_duration_secintegerwater_volume_litersfloatbattery_level_percentfloatlocation_latitudefloatlocation_longitudefloatanomaly_codestringnotesstringanomaly_descriptionstring
LOG0001normal-62.3FIELD_01DEV_A1002023-05-14T04:15:23ZFARM_XYZsoil_sensorsensor_reading34.715.256.4blankblankblank88.229.4317-82.1372blankRoutine sensor check before sunriseblank
LOG0002success-38.9FIELD_01DEV_B1502023-05-14T05:12:08ZFARM_XYZvalve_controllerirrigation_startedblankblankblank21.4780174.295.629.4318-82.1373blankAutomated schedule triggered for morning irrigationblank
LOG0003normal-12.4blankDEV_C1012023-05-14T06:03:44ZFARM_XYZweather_stationsensor_readingblank18.562.3blankblankblank7229.432-82.1369blankAfternoon weather station readingblank
LOG0004success-74.2FIELD_02DEV_D2022023-05-14T06:15:18ZFARM_XYZsoil_sensorsensor_reading57.121.642.8blankblankblank68.929.4324-82.1379blankPre-dawn sensor readingblank
LOG0005success-86.9FIELD_10DEV_E3002023-05-14T07:02:51ZFARM_QRSflow_metersensor_readingblankblankblank18.3blankblank59.735.5104-91.432blankPeak irrigation flow measuredblank
LOG0006success-42.3FIELD_01DEV_B1502023-05-14T07:32:26ZFARM_XYZvalve_controllerirrigation_stoppedblankblankblank20.8780174.292.129.4318-82.1373blankIrrigation completed successfullyblank
LOG0007warning-101.3FIELD_01DEV_A1002023-05-14T08:22:17ZFARM_XYZsoil_sensoranomaly_detected10022.498.7blankblankblank16.429.4317-82.1372SM_MAX100Saturated soil reading reportedSoil moisture reading at maximum, potential sensor fault.
LOG0008success-11blankDEV_F4002023-05-14T09:15:29ZFARM_QRSweather_stationmaintenanceblankblankblankblankblankblank99.235.5108-91.4317blankFirmware updated successfullyblank

What the 120 rows show

from the 120-row sample

Error status stands out: mean signal_strength_dbm is -150.0, against -63.8 for the rest.

  • -62.9median signal_strength_dbm
  • 5device types
  • 7event types
  • 14farms
  • 44.4median soil_moisture
  • 20.6median temperature_celsius
signal_strength_dbm120 rows, in bands of 20
015302148529132515-160-800signal_strength_dbm →

Median -62.9, from -150.0 to 0.0.

field_id79 rows with a value · 41 left blank
  1. FIELD228
  2. FIELD_017
  3. FIELD_025
  4. FIELD_105
  5. FIELD995
  6. FIELD555
  7. FIELD_414
  8. FIELD124
  9. FIELD1074
  10. FIELD1084
21 columns by typefrom the column list below
  • string 10
  • integer 1
  • float 9
  • datetime 1

Columns

21 columns in three groups
blueprint · 21 columns
columntypedescriptionexample
Text 10 columns
log_idstringUnique identifier for each log entryuniqueLOG0001
device_idstringUnique identifier for the IoT device generating the logDEV_A100
farm_idstringUnique identifier for the farm or agricultural siteFARM_XYZ
field_idstringIdentifier for the specific field or plot within the farmoptionalFIELD_01
device_typestringType of IoT device (e.g., soil_sensor, valve_controller, weather_station)5 valuessoil_sensor
event_typestringType of event or action logged (e.g., irrigation_started, irrigation_stopped, anomaly_detected, sensor_reading)7 valuessensor_reading
statusstringStatus of the device or event (e.g., success, failure, warning, normal, error)6 values · optionalnormal
anomaly_codestringCode representing the type of anomaly detected, if anyoptionalSM_MAX100
anomaly_descriptionstringDetailed description of the anomaly or error, if applicableoptionalSoil moisture reading at …
notesstringAdditional notes or comments about the log entryoptionalPre-dawn sensor reading
Numbers 10 columns
soil_moisturefloatSoil moisture level as measured by the device (percentage, 0-100)0 to 100 · optional34.7
temperature_celsiusfloatTemperature reading in degrees Celsius-50 to 80 · optional15.2
humidity_percentfloatRelative humidity percentage (0-100)0 to 100 · optional56.4
water_flow_rate_lpmfloatWater flow rate in liters per minute0 or more · optional21.4
irrigation_duration_secintegerDuration of the irrigation event in seconds0 or more · optional780
water_volume_litersfloatTotal volume of water used during the event (liters)0 or more · optional174.2
battery_level_percentfloatBattery level of the device as a percentage (0-100)0 to 100 · optional88.2
signal_strength_dbmfloatWireless signal strength in dBm-150 to 0 · optional-62.3
location_latitudefloatLatitude coordinate of the device at the time of log-90 to 90 · optional29.4317
location_longitudefloatLongitude coordinate of the device at the time of log-180 to 180 · optional-82.1372
Dates and times 1 column
timestampdatetimeDate and time when the log entry was recorded (in UTC)2023-05-14T04:15:23Z

Use it for

  • median signal …-62.9120 rows

    An agriculture dashboard

    Signal_strength_dbm by status and a breakdown of field_id. Excel, Power BI or Tableau.

  • Why do the 11 error rows have a mean signal_strength_dbm of -150.0?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable logs with device_id, timestamp and farm_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 21 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset120 rows21 columns
Yours1,000 rows21 columnslocation_latitude: UK only

blueprint · remote-irrigation-iot-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 21 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 single irrigation event with timestamp.
  • Records include device ID, water dispensed (liters), and valve status.
  • Events flagged for abnormal duration or quantity must include an 'anomaly' indicator.
  • Sensor data must track soil moisture and weather conditions at event time.
  • Device offline or error events must be recorded with error code.
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
remote-irrigation-iot-logs

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