Abstract:
Agriculture plays a vital role in the Indian economy, and its improvement is crucial for overall economic growth. This project aims to leverage machine learning models to predict crop yields and provide advice on the best alternative crops based on various features. The frontend development will utilize HTML, CSS, and JavaScript, while the backend will be built using the Flask framework. The project will include the creation of a web page where users can input parameters such as district, state, temperature, humidity, soil type, area, and desired crop. The system will then provide yield predictions based on these inputs. Additionally, the user interface will offer advice on crop selection based on soil composition (nitrogen, potassium, and phosphorus), temperature, humidity, and soil type.
This project is suitable for publication in IEEE and serves as an excellent IEEE machine learning project for final year students. Smart AI Technologies specializes in machine learning, AI, and data science, and we are committed to providing comprehensive support throughout the project. Our services include:
As a leading provider of commercial IEEE machine learning projects, we ensure that this project is fully developed, supported, and ready for publication in IEEE, providing students with a valuable and impactful final year project experience.