Crop Recommendation and Yield Production using SVM Algorithm

Different soil parameters affect agriculture growth, namely Nitrogen, Phosphorous, Potassium, Crop Rotation, Soil Moisture, pH, surface temperature, and weather factors such as temperature, rainfall, etc. With the help of technology, farm yields will improve due to increased crop productivity. Smart Agriculture is provided by the proposed work via the monitoring of the agricultural field. As a result, it can greatly increase farmers' output. This research work present a website to employ Machine Learning [ML] algorithms combined with historical weather information to determine the most profitable crop under the current weather conditions. Using weather parameters, soil parameters and historic yields, this system can also predict crop yields. The proposed work aims at creating a system that integrates data from multiple sources, data analytics, and forecast analysis that can enhance crop yield productivity and make farmers more profitable in the long run.