AI Portable Soil Testing for Crop Yield Using Machine Learning in Kannada

AI Portable Soil Testing for Crop Yield Using Machine Learning in Kannada

Shruthi V1 Dr.Nuthan A C2 Ankitha B 3, Poornima L R4, Varshini J5,
1Assistant Professor, Electronics and communication Engineering, G Madegowda Institute of Technology

2Professor & Head, Electonics and communication Engineering, G Madegowda Institute of Technology

3 Student, Electronics and communication Engineering, G Madegowda Institute of Technology

4 Student, Electronics and communication Engineering, G Madegowda Institute of Technology

5 Student, Electronics and communication Engineering, G Madegowda Institute of Technology

Abstract - In India, 51.09 % of Land is used as agricultural Land. More than 60% of farmers perform farming on small-scale or limited Land. To help the farmers improve their income, we are developing smart crop prediction system by performing the soil analysis using the CNN algorithm. It helps to optimize the agricultural trails. The major drawback of the existing system is that the datasets contain unreliable data, directly affecting the model's accuracy. By analyzing the soil types and temperature of the surroundings, we are forecasting the most suitable crops for that particular climate using machine learning algorithms. With this, farmers can increase the quality and quantity of their crops.

Keywords- CNN, Crop prediction, Optimize, temperature, Machine learning