Real-Time Best-Fitted Crops Recommendation System Based On Agricultural Soil Health

The rising population every year parallels the increase in food shortage. One of the main reasons for food shortage is because of crop failure. Essentially, identifying soil health leads to sustainable crop production. Previous crop recommender systems were created using Machine Learning algorithms to categorize crops based on soil health parameters. Therefore, an improved real-time best-fitted crop recommendation system was created in this paper. The real-time best-fitted crop recommendation system is a cloud-based system that utilizes a deep learning algorithm that can be trained to analyze the number of nutrients needed by each crop to identify the three best-fitted crops recommended to the farmers. The system comprises a web and mobile application that the users can access to view the recommended crops and the nutrients it has and different cloud services that run the whole system’s network. The experts validated the project with an accuracy of 98.62%. Thus, the system created the best-fitted crops based on the agricultural soil health parameters.