IoT Soil Health Monitoring Data
This dataset provides high-resolution, time-stamped soil health metrics collected from IoT sensors deployed across agricultural plots and farms. It includes essential soil properties, nutrient levels, ambient climate data, and sensor operational status, supporting smart farming automation, climate resilience analysis, and transparent supply chain reporting for sustainable agriculture.
Sample rows
preview · 8 of 120 rows · all 24 columns| sensor_idstring | sensor_statusstring | battery_levelfloat | data_quality_flagboolean | farm_idstring | plot_idstring | timestampdatetime | latitudefloat | longitudefloat | soil_moisturefloat | soil_temperaturefloat | soil_phfloat | soil_ecfloat | nitrogen_levelfloat | phosphorus_levelfloat | potassium_levelfloat | ambient_temperaturefloat | ambient_humidityfloat | farm_namestring | farm_ownerstring | farm_countrystring | farm_statestring | farm_citystring | farm_postal_codestring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SN-101 | active | 93.2 | true | FARM-Olympus | P-A1 | 2024-05-22T10:15:21Z | 39.9526 | -75.1652 | 42.3 | 19.8 | 6.6 | 1.7 | 21.1 | 11.4 | 18.2 | 17.5 | 70.7 | Olympus Farms | Sophia Papadopoulos | Greece | Thessaly | Larissa | 41223 |
| SN-102 | active | 86.7 | true | FARM-Gaia | P-B2 | 2024-05-23T14:37:08Z | 37.9838 | 23.7275 | 64.1 | 25.2 | 7.1 | 2.8 | 17.8 | 14.2 | 12.9 | 21.4 | 81.2 | Gaia Agro | Ioannis Nikolaou | Greece | Attica | Athens | 10552 |
| SN_103 | active | 91 | true | FARM-Maple | P-C3 | 2024-05-24T06:42:10Z | 45.5017 | -73.5673 | 35.8 | 13.7 | 6.2 | 1.2 | 19.4 | 10.3 | 16.7 | 12.3 | 75.9 | Maple Leaf Farm | Ethan Tremblay | Canada | Quebec | Montreal | H3B1X8 |
| SENSOR-104 | active | 72.5 | true | FARM-Greenfield | P-D4 | 2024-05-25T17:25:59Z | 40.7128 | -74.006 | 77.2 | 32.4 | 7.7 | 2.2 | 27.6 | 15.9 | 28.4 | 29.2 | 88.4 | Greenfield Acres | Olivia Turner | USA | New York | New York | 10001 |
| SN-105 | active | 84.1 | true | FARM-Sunshine | P-E5 | 2024-05-26T13:11:14Z | 28.7041 | 77.1025 | 48.6 | 22.9 | 6.7 | 2 | 25.5 | 16.1 | 21.3 | 26.7 | 68.2 | Sunshine Fields | Priya Sharma | India | Delhi | Delhi | 110001 |
| SN-106 | active | 79.3 | true | FARM-Riverbend | P-F1 | 2024-05-27T16:46:35Z | 51.5074 | -0.1278 | 53.2 | 14.8 | 6.9 | 1.5 | 14.6 | 13.7 | 19.2 | 15.7 | 63.1 | Riverbend Farm | James Clarke | UK | England | London | SW1A2AA |
| SN_107 | active | 64.8 | true | FARM-Harvest | P-G2 | 2024-05-28T08:10:51Z | 34.0522 | -118.2437 | 60.5 | 30.1 | 7.4 | 2.4 | 23.2 | 17.9 | 20.1 | 33.6 | 84.3 | Harvest Ranch | Emma Brooks | USA | California | Los Angeles | 90012 |
| SENSOR-108 | active | 69.2 | true | FARM-Willow | P-H3 | 2024-05-29T19:20:06Z | 55.9533 | -3.1883 | 68.7 | 27.8 | 6.5 | 3.3 | 29.3 | 12.8 | 24.6 | 21.8 | 91.6 | Willow Springs | Liam Stewart | UK | Scotland | Edinburgh | EH12NG |
| SN-109 | active | 90.5 | true | FARM-Serenity | P-I4 | 2024-05-30T11:04:33Z | 35.6895 | 139.6917 | 58.4 | 28.2 | 6.1 | 2.6 | 20.7 | 13.2 | 22.4 | 28.6 | 79.4 | Serenity Gardens | Haruto Takahashi | Japan | Tokyo | Tokyo | 100-0001 |
| SN-110 | active | 77.3 | true | FARM-Cedar | P-J5 | 2024-05-31T15:33:44Z | 53.3498 | -6.2603 | 74.9 | 33.1 | 7.3 | 2.9 | 31.2 | 18.4 | 26.7 | 22.1 | 89.7 | Cedar Grove | Aoife Murphy | Ireland | Leinster | Dublin | D02X285 |
| SN-111 | error | 0 | false | FARM-DesertRose | P-K1 | 2024-05-22T03:20:48Z | 24.7136 | 46.6753 | 0 | -40 | 3 | 0 | blank | blank | blank | -40 | 0 | Desert Rose | Faisal Al Saud | Saudi Arabia | Riyadh | Riyadh | 11564 |
| SN_112 | error | 0 | false | FARM-Frost | P-L2 | 2024-05-23T23:59:59Z | 65.0121 | 25.4651 | 0 | -40 | 3 | 0 | 0 | blank | blank | -40 | 0 | Frost Valley | Mikko Lehtonen | Finland | Lapland | Oulu | 90100 |
| SENSOR-113 | error | 100 | false | FARM-Tundra | P-M3 | 2024-05-24T00:00:00Z | 78.2232 | 15.6469 | 100 | 60 | 10 | 25 | 999.9 | blank | blank | 60 | 100 | Tundra Station | Anna Bergström | Norway | Svalbard | Longyearbyen | 9170 |
| SN-114 | error | 0 | false | FARM-Sahara | P-N4 | 2024-05-25T04:05:12Z | 23.4162 | 25.6628 | 0 | 60 | 10 | 25 | blank | blank | blank | 60 | 0 | Sahara Oasis | Abdelkader Benali | Algeria | Tamanrasset | Tamanrasset | 11000 |
| SN-115 | error | 100 | false | FARM-Tropicana | P-O5 | 2024-05-26T22:51:44Z | -3.4653 | -62.2159 | 100 | 60 | 10 | 25 | 999.9 | 999.9 | 999.9 | 60 | 100 | Tropicana Research | Lucas Silva | Brazil | Amazonas | Manaus | 69000-000 |
| SN_116 | error | 0 | false | FARM-Glacier | P-P1 | 2024-05-27T02:16:37Z | 61.524 | 105.3188 | 0 | -40 | 3 | 0 | blank | blank | blank | -40 | 0 | Glacier Fields | Irina Petrova | Russia | Siberia | Yakutsk | 677000 |
| SENSOR-117 | inactive | 18.2 | false | FARM-Riverside | P-Q2 | 2024-05-28T05:07:11Z | 40.4406 | -79.9959 | 18.2 | 10.1 | 4.8 | 0.8 | blank | blank | blank | 8.9 | 14.3 | Riverside Estate | Benjamin Miller | USA | Pennsylvania | Pittsburgh | 15222 |
| SN-118 | inactive | 19.9 | false | FARM-Meadow | P-R3 | 2024-05-29T09:13:54Z | 52.4862 | -1.8904 | 13.6 | 7.3 | 5.1 | 0.7 | blank | blank | blank | 9.2 | 12.7 | Meadowlands | Charlotte Evans | UK | West Midlands | Birmingham | B1 1AA |
| SN_119 | inactive | 15.7 | false | FARM-Highland | P-S4 | 2024-05-30T18:44:21Z | 56.4907 | -4.2026 | 19.7 | 8.4 | 4.9 | 0.6 | blank | blank | blank | 8.7 | 15.1 | Highland Pastures | Ewan MacGregor | UK | Scotland | Fort William | PH33 6AA |
| SENSOR-120 | inactive | 17.6 | false | FARM-Cascade | P-T5 | 2024-05-31T07:33:41Z | 47.6062 | -122.3321 | 7.7 | 6.5 | 3.7 | 0.9 | blank | blank | blank | 7.3 | 10.9 | Cascade Farm | Megan Smith | USA | Washington | Seattle | 98101 |
What the 120 rows show
from the 120-row sampleActive (sensor status) stands out: mean battery_
- 62%data_
quality_ flag = true - 68.1median battery_
level - 49.1median soil_
moisture - 22.5median soil_
temperature - 6.5median soil_
ph - 2.4median soil_
ec
Median 68.1, from 0.0 to 100.0.
- string 10
- float 12
- datetime 1
- boolean 1
Columns
24 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 10 columns | |||
sensor_id | string | Unique identifier for each IoT soil sensor device | SN-101 |
farm_id | string | Unique identifier for the farm or agricultural site | FARM-Olympus |
plot_id | string | Unique identifier for the specific plot or field within a farm | P-A1 |
sensor_status | string | Operational status of the sensor (e.g., active, inactive, error)active · inactive · error · maintenance | active |
farm_name | string | Name of the farm or agricultural siteoptional | Olympus Farms |
farm_owner | string | Name of the farm owner or manageroptional | Sophia Papadopoulos |
farm_country | string | Country where the farm is locatedoptional | Greece |
farm_state | string | State or region where the farm is locatedoptional | Thessaly |
farm_city | string | City or locality of the farmoptional | Larissa |
farm_postal_code | string | Postal code of the farm locationoptional | 41223 |
| Numbers 12 columns | |||
latitude | float | GPS latitude coordinate of the sensor location-90 to 90 | 39.9526 |
longitude | float | GPS longitude coordinate of the sensor location-180 to 180 | -75.1652 |
soil_moisture | float | Measured soil moisture percentage (volumetric water content)0 to 100 | 42.3 |
soil_temperature | float | Measured soil temperature in degrees Celsius-40 to 60 | 19.8 |
soil_ph | float | Measured soil pH value3 to 10 | 6.6 |
soil_ec | float | Measured soil electrical conductivity (dS/m)0 or more · optional | 1.7 |
nitrogen_level | float | Measured nitrogen concentration in soil (mg/kg)0 or more · optional | 21.1 |
phosphorus_level | float | Measured phosphorus concentration in soil (mg/kg)0 or more · optional | 11.4 |
potassium_level | float | Measured potassium concentration in soil (mg/kg)0 or more · optional | 18.2 |
ambient_temperature | float | Ambient air temperature near the sensor (°C)-40 to 60 · optional | 17.5 |
ambient_humidity | float | Ambient air humidity percentage near the sensor0 to 100 · optional | 70.7 |
battery_level | float | Sensor battery level percentage0 to 100 · optional | 93.2 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time when the soil metrics were recorded | 2024-05-22T10:15:21Z |
| True or false 1 column | |||
data_quality_flag | boolean | Indicates if the reading passed quality checks (true = valid, false = suspect) | true |
Use it for
An agriculture dashboard
The data_
quality_ flag rate and battery_ level by sensor_ status. Excel, Power BI or Tableau. Why do the 74 active rows have a mean battery_
level of 76.5? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Sensors120SN-10193.2activeSN-10286.7activeSN-1110error
A software demo
Believable sensors with farm_
id, plot_ id and timestamp to fill a screen in front of a buyer.
This dataset120 rows24 columns
Yours1,000 rows24 columnsfarm_country: UK only
blueprint · iot-soil-health-monitoring-data
Behind this dataset
Same schema. As many rows as you need.
These 120 rows came out of a blueprint — 24 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 field sensor reading
- Sensors report at regular 4-hour intervals
- Metrics include moisture, pH, temperature, and nutrient levels
- Anomaly flags generated for readings outside crop-specific thresholds
- Sensor IDs mapped to farm zones for traceability
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
- iot-soil-health-monitoring-data