Skip to main content
Kaggle

Smart Agriculture IoT Sensor Dataset

Smart Agriculture Agriculture IoT
271 views
1 min read
License
Catalog metadata: This page is a discovery record, not publisher documentation. Verify the description, schema, provenance, version, licence, and citation at the linked source before use.

Catalog Summary

"Comprehensive IoT sensor data from smart farming systems. Includes soil moisture, temperature, humidity, NPK levels, and weather conditions for precision agriculture and crop yield optimization."

Catalog Notes

Dataset Overview

Real-world inspired dataset capturing multiple sensor measurements from precision agriculture systems. Designed for developing smart farming solutions and crop management optimization models.

Soil Measurements

  • Soil Moisture: Volumetric water content (%)
  • Soil Temperature: Ground temperature (°C)
  • Soil pH: Acidity/alkalinity levels (0-14 scale)
  • NPK Levels: Nitrogen, Phosphorus, Potassium concentrations (ppm)
  • Electrical Conductivity: Soil salinity indicator (dS/m)

Environmental Data

  • Ambient Temperature: Air temperature (°C)
  • Humidity: Relative humidity (%)
  • Light Intensity: Solar radiation (lux)
  • Rainfall: Precipitation measurements (mm)
  • Wind Speed: Atmospheric conditions (km/h)

Crop Information

  • Crop Type: Wheat, rice, corn, vegetables, fruits
  • Growth Stage: Seedling, vegetative, flowering, harvest
  • Irrigation Status: Automated watering system state
  • Yield Prediction: Expected harvest (tons/hectare)

Applications

Precision irrigation scheduling, crop health monitoring, yield prediction models, fertilizer optimization, disease early warning systems, and automated farming decision support.

Data Preview

TimestampSensor_IDSoil_Moisture_%Soil_Temp_CNPK_N_ppmNPK_P_ppmNPK_K_ppmHumidity_%Crop_TypeIrrigation_Status
2024-01-10 06:00S00145.222.585423868.5WheatOFF
2024-01-10 06:30S00228.724.192384572.3RiceON
2024-01-10 07:00S00352.321.878454065.2CornOFF

Showing first few rows for preview

Provided Citation

Atharva Ingle (2024). Crop Recommendation Dataset. Kaggle. Retrieved from https://www.kaggle.com/datasets/atharvaingle/crop-recommendation-dataset

This citation is displayed as supplied. Automatic style conversion is disabled because structured citation metadata is not recorded.

Source metadata: Kaggle (2026)

Indexed by IoTDataset.com on Jan 14, 2026

Review the Source Record

Confirm the licence, version, access conditions, file format, and provenance at the source before use.

Open Source Page

Related Topics & Keywords

Browse all Smart Agriculture datasets

Share This Research

More in Smart Agriculture

View All
Agriculture Kaggle

IoT Agriculture 2024 - Precision Farming Sensor Dataset

Comprehensive IoT sensor dataset for precision agriculture with soil metrics (moisture, temperature, pH), environmental conditions (humidity, temperature, light intensity), and crop growth parameters. Includes irrigation recommendations and fertilizer optimization data.

Jan 24, 2026
Agriculture Kaggle

Smart Farming Sensor Data for Yield Prediction

Real-world smart farming operations data powered by IoT sensors and satellite data for crop yield prediction.

Feb 19, 2026
Agriculture Kaggle

Smart Farming Data 2024 (SF24) - California Farms

Comprehensive 2024 agricultural data from California farms tracking environmental, soil, and crop metrics for predictive modeling.

Jan 12, 2026
Agriculture University

MuST-C: Multi-Sensor Crop Phenotyping Dataset

MuST-C is a multi-sensor agricultural dataset for in-field phenotyping, covering six crop species with RGB, LiDAR, and multispectral data to automate large-scale growth monitoring.

Feb 13, 2026
Agriculture External

CropClimateX: Multi-modal US Agriculture Monitoring

CropClimateX integrates satellite imagery, weather, and soil data across 1,527 US counties, enabling multi-task learning for yield prediction and climate impact analysis in agriculture.

Feb 13, 2026
Smart Agriculture IoT Mendeley Data

Smart Irrigation System for Rice Farming - AI-IoT-Based SDIS Dataset

AI-IoT-based Smart Drip Irrigation System (SDIS) dataset specifically designed for rice plants considering local agronomic characteristics, featuring soil moisture, weather data, and irrigation control decisions for precision agriculture.

Jan 31, 2026

Explore other topics

All topics →