Crop Recommendation System For Intelligent Smart Farming Technology

Nowadays farmers are moving towards precision agriculture instead of the traditional approach.Smart Farming in the present scenario is a farming approach that is done using IoT sensors, satellites, etc. In Smart Farming 5G Networks can be used for taking images of soil using satellites and further the soil nutrients quality is analyzed with the help of images taken by district agricultural officers. It will allow farmers to monitor the quality of the soil such as temperature, humidity, soil nutrients such as pH label, nitrates, urea, potassium, etc remotely even if they are physically present on the farmland or not. It can help the farmers in determining whether the soil needs fertilizers or not. This will reduce the excessive use of fertilizers in the soil thus increasing crop production. This will be cost-effective for the farmers, conserve natural resources like water, and will help in increasing the agricultural economy. In this paper, an application of smart farming is a crop recommendation system has been implemented. For crop recommendation, machine learning algorithms such as Decision Tree, SVM, Gaussian Naive Bayes, Logistic Regression, Random Forest, XG-Boost, and KNN are used. In comparison to other machine learning algorithms, Random Forest and XG-Boost have been found to be effective, with an accuracy rate of 99.09 percent and SVM has the lowest accuracy rate of 10.68%.