Agriculture Field Sensor Readings
This dataset contains detailed, timestamped sensor readings from agricultural fields, including soil moisture, air temperature, and pest detection data. Each record is geotagged and linked to specific fields and sensors, enabling advanced analysis for precision farming, crop management, and yield optimization. The dataset supports operational monitoring, predictive analytics, and research into sustainable agriculture practices.
Sample rows
preview · 8 of 200 rows · all 15 columns| reading_idstring | sensor_typestring | soil_moisture_percentfloat | pest_detectedboolean | field_idstring | field_namestring | location_latitudefloat | location_longitudefloat | sensor_idstring | reading_datetimedatetime | air_temperature_celsiusfloat | pest_typestring | pest_countinteger | battery_level_percentfloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| R1-20240601-001 | moisture | 34.5 | blank | F-NE-001 | North East Cornfield | 41.403 | -72.496 | S-M-001 | 2024-06-01T08:12:34 | blank | blank | blank | 82.4 | Normal morning reading |
| R1-20240601-002 | temperature | blank | blank | F-NW-002 | North West Wheat Zone | 41.415 | -72.501 | S-T-002 | 2024-06-01T08:16:20 | 16.8 | blank | blank | 95.1 | blank |
| R1-20240601-003 | pest | blank | true | F-SE-003 | South East Soybean | 41.388 | -72.482 | S-P-003 | 2024-06-01T08:19:45 | blank | aphids | 12 | 78.2 | Aphid cluster detected |
| R1-20240601-004 | moisture | 46.7 | blank | F-CENT-004 | Central Barley Plot | 41.397 | -72.493 | S-M-004 | 2024-06-01T08:22:10 | blank | blank | blank | 90.5 | Moisture rising after rain |
| R1-20240601-005 | temperature | blank | blank | F-NE-001 | North East Cornfield | 41.405 | -72.495 | S-T-005 | 2024-06-01T08:28:30 | 17.3 | blank | blank | 88.7 | blank |
| R1-20240601-006 | moisture | 28.1 | blank | F-NW-002 | North West Wheat Zone | 41.417 | -72.503 | S-M-006 | 2024-06-01T08:32:12 | blank | blank | blank | 75.6 | Dry patch detected |
| R1-20240601-007 | temperature | blank | blank | F-SE-003 | South East Soybean | 41.389 | -72.48 | S-T-007 | 2024-06-01T08:34:59 | 18.2 | blank | blank | 79.4 | Sunny conditions |
| R1-20240601-008 | pest | blank | false | F-CENT-004 | Central Barley Plot | 41.398 | -72.491 | S-P-008 | 2024-06-01T08:37:33 | blank | blank | 0 | 85 | No pests found |
| R1-20240601-009 | moisture | 52.9 | blank | F-SW-005 | South West Potato | 41.378 | -72.487 | S-M-009 | 2024-06-01T08:39:55 | blank | blank | blank | 79.8 | Moisture peak after irrigation |
| R1-20240601-010 | pest | blank | true | F-NE-001 | North East Cornfield | 41.406 | -72.494 | S-P-010 | 2024-06-01T08:44:18 | blank | cutworms | 5 | 76.3 | Cutworms detected near rows |
| R1-20240601-011 | temperature | blank | blank | F-NW-002 | North West Wheat Zone | 41.416 | -72.502 | S-T-011 | 2024-06-01T08:46:50 | 16.4 | blank | blank | 97.2 | blank |
| R1-20240601-012 | moisture | 31 | blank | F-SE-003 | South East Soybean | 41.391 | -72.483 | S-M-012 | 2024-06-01T08:49:21 | blank | blank | blank | 84.3 | blank |
| R1-20240601-013 | temperature | blank | blank | F-CENT-004 | Central Barley Plot | 41.399 | -72.492 | S-T-013 | 2024-06-01T08:52:37 | 15.9 | blank | blank | 91.6 | Cloudy morning |
| R1-20240601-014 | pest | blank | false | F-SW-005 | South West Potato | 41.381 | -72.488 | S-P-014 | 2024-06-01T08:54:46 | blank | blank | 0 | 87.7 | No pest activity |
| R1-20240601-015 | temperature | blank | blank | F-NE-001 | North East Cornfield | 41.404 | -72.497 | S-T-015 | 2024-06-01T08:57:10 | 17.5 | blank | blank | 89.2 | Temperature rising |
| R1-20240601-016 | pest | blank | true | F-NW-002 | North West Wheat Zone | 41.418 | -72.504 | S-P-016 | 2024-06-01T09:01:32 | blank | grasshoppers | 8 | 93 | Grasshopper infestation |
| R1-20240601-017 | moisture | 29.7 | blank | F-SE-003 | South East Soybean | 41.39 | -72.482 | S-M-017 | 2024-06-01T09:04:11 | blank | blank | blank | 80.2 | Low moisture alert |
| R1-20240601-018 | temperature | blank | blank | F-CENT-004 | Central Barley Plot | 41.4 | -72.488 | S-T-018 | 2024-06-01T09:06:24 | 16.2 | blank | blank | 92.8 | blank |
| R1-20240601-019 | moisture | 55.3 | blank | F-SW-005 | South West Potato | 41.379 | -72.489 | S-M-019 | 2024-06-01T09:09:01 | blank | blank | blank | 81.5 | Post irrigation |
| R1-20240601-020 | pest | blank | false | F-NE-001 | North East Cornfield | 41.403 | -72.493 | S-P-020 | 2024-06-01T09:12:43 | blank | blank | 0 | 77.4 | No pests, normal reading |
What the 200 rows show
from the 200-row sample- 51%pest_
detected = true - 37.9median soil_
moisture_ percent - 34field names
- 18.3median air_
temperature_ celsius - 5median pest_
count - 80.6median battery_
level_ percent
Median 37.9, from 19.1 to 81.2.
- string 7
- integer 1
- float 5
- datetime 1
- boolean 1
Columns
15 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 7 columns | |||
reading_id | string | Unique identifier for each sensor reading recordunique | R1-20240601-001 |
field_id | string | Unique identifier for the agriculture field where the sensor is located | F-NE-001 |
field_name | string | Human-readable name of the agriculture fieldoptional | North East Cornfield |
sensor_id | string | Unique identifier for the sensor device | S-M-001 |
sensor_type | string | Type of sensor (e.g., moisture, temperature, pest)moisture · temperature · pest | moisture |
pest_type | string | Type of pest detected, if anyoptional | aphids |
notes | string | Additional notes or comments about the readingoptional | Normal morning reading |
| Numbers 6 columns | |||
location_latitude | float | Latitude coordinate of the sensor's location-90 to 90 | 41.403 |
location_longitude | float | Longitude coordinate of the sensor's location-180 to 180 | -72.496 |
soil_moisture_percent | float | Measured soil moisture as a percentage (0-100)0 to 100 · optional | 34.5 |
air_temperature_celsius | float | Measured air temperature in degrees Celsius-50 to 60 · optional | 16.8 |
pest_count | integer | Number of pests detected, if any0 or more · optional | 12 |
battery_level_percent | float | Sensor device battery level as a percentage (0-100)0 to 100 · optional | 82.4 |
| Dates and times 1 column | |||
reading_datetime | datetime | Timestamp when the sensor reading was recorded | 2024-06-01T08:12:34 |
| True or false 1 column | |||
pest_detected | boolean | Indicates whether pests were detected (true/false)optional | true |
Use it for
An agriculture dashboard
The pest_
detected rate, soil_ moisture_ percent by sensor_ type and a breakdown of field_ id. Excel, Power BI or Tableau. Why do 30 of 59 rows have pest_
detected = true? A class exercise
Hand out the rows and one question. Everyone works from the same 200 rows.
- Readings200R1-20240601-003pestR1-20240601-008pestR1-20240601-010pest
A software demo
Believable readings with field_
id, field_ name and location_ latitude to fill a screen in front of a buyer.
This dataset200 rows15 columns
Yours1,000 rows15 columnslocation_latitude: UK only
blueprint · agriculture-field-sensor-readings
Behind this dataset
Same schema. As many rows as you need.
These 200 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
- Daily readings per field
- Include sensor type and location
- Flag critical threshold breaches
- Record crop type
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
- agriculture-field-sensor-readings