Published Paper Details:

Automating agricultural aspects is the mechanical process with or without human intervention in agriculture field. Due to the availability of less space for domestic lands of farmers, it has become an important area for choosing the most suitable crops based on prevailing factors in the selected area. Even though there are enough knowledge, techniques, and methods which are manually available in agriculture, there is no system in which the environmental factors are detected and will suggest which crop type is best to farming in that condition. In this project consists of a theoretical and conceptual platform of a Recommendation system through the integrated models of collecting environmental factors, we will be using Machine learning techniques such as the SVM, Decision tree model, Random forest, and Logistic Regression concerned with Artificial Intelligence to recommend a crop for the selected land with site-specific parameters with high accuracy and the efficiency. It has been a major problem to identify what to grow in the land, any man has adequate space in the owner's land. Not only for domestic lands but also for the farming lands. Why it has become a problem for all, is that environmental factors such as temperature(humidity), water levels, and soil conditions are uncertain as they change from time to time. Due to these problems mentioned above, this solution of crop recommendation system using a machine learning model predicts to the user what crop type would be the most suitable for the selected area by collecting the environmental factors for plant growth and processing them with the trained sub-models of the main of the system to provide output. Keywords: Crop Recommendation, Machine Learning, Random Forest, Decision Tree, Data Analysis, Data Visualization.