Smart Farming Sensor Data for Yield Prediction

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.