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Kaggle

Smart Farming Sensor Data for Yield Prediction

Agriculture
Feb 19, 2026
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Abstract

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

Description

This dataset simulates real-world smart farming operations powered by IoT sensors and satellite data. It captures environmental and operational variables critical for precision agriculture and crop yield prediction. Features include soil moisture levels, soil temperature, pH levels, NPK (Nitrogen-Phosphorus-Potassium) readings, air temperature, humidity, rainfall, solar radiation, wind speed, and satellite-derived vegetation indices (NDVI). The dataset includes crop type labels, planting dates, and actual yield measurements for supervised learning. Covers multiple crop types including wheat, corn, rice, and soybeans across different geographic regions and growing seasons.

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Cite This Dataset

Atharva, Soundankar (2024). Smart Farming Sensor Data for Yield Prediction. [Dataset]. Kaggle. https://www.kaggle.com/datasets/atharvasoundankar/smart-farming-sensor-data-for-yield-prediction

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Original source: Kaggle (2024). Visit official page for more details.

Indexed by IoTDataset.com on Feb 19, 2026

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