Agrimitra is a smart farming assistant app designed to support farmers in optimizing agricultural practices through technology. The app leverages AI and machine learning to provide fertilizer recommendations, plant disease detection, and an AI-powered chatbot for seamless interaction.
Farming is one of the major sectors that influences a country’s economic growth.
In countries like India, the majority of the population is dependent on agriculture for their livelihood. Many new technologies, such as Machine Learning and Deep Learning, are being implemented into agriculture so that it is easier for farmers to grow and maximize their yield.
In this project, I present a website in which the following applications are implemented: Crop recommendation, Fertilizer recommendation, and Plant disease prediction, respectively.
In the crop recommendation application, the user can provide the soil data from their side and the application will predict which crop should the user grow.
For the fertilizer recommendation application, the user can input the soil data and the type of crop they are growing, and the application will predict what the soil lacks or has excess of and will recommend improvements.
For the last application, that is the plant disease prediction application, the user can input an image of a diseased plant leaf, and the application will predict what disease it is and will also give a little background about the disease and suggestions to cure it.
- Provides precise fertilizer types and quantities based on soil data and crop needs.
- Reduces overuse of fertilizers, preserving soil health and cutting costs.
- Identifies plant diseases using image recognition and machine learning.
- Suggests remedies and preventive measures for healthier crops.
- Offers instant responses to farmer queries on crop management, fertilizers, and more.
- Enhances user experience with natural language processing (NLP).
- Chatbot is named Arogya.
- Built with HTML, CSS, and Flask to ensure a seamless and responsive interface.
- Accessible on mobile and desktop devices.
- Frontend: HTML, CSS, Bootstrap
- Backend: Python, Flask
- Libraries: TensorFlow, Keras, OpenCV, Scikit-learn, Numpy, pandas, pytorch and other essentials
- Enter the corresponding nutrient values of your soil, along with your state and city.
- The N-P-K (Nitrogen-Phosphorus-Potassium) values should be entered as a ratio between them. For more information on this, refer to this website.
- Note: When entering the city name, ensure it's a commonly recognized city. Remote cities or towns might not be available in the Weather API used to fetch humidity and temperature data.
- Enter the nutrient contents of your soil and the crop you want to grow.
- The algorithm will analyze the data and inform you about which nutrients are in excess or lacking in your soil.
- Based on this, the system will provide suggestions for the best fertilizers to purchase.
- Upload an image of the leaf of your plant.
- The algorithm will identify the crop type and assess whether it's healthy or diseased.
- If diseased, it will inform you of the cause of the disease and suggest ways to prevent or cure it.
- Note: Currently, the disease detection system supports only the following crops: [list of supported crops here].
🌟 Contribute to smarter, sustainable agriculture with AgriMitra!
If you have any doubts or want to contribute, feel free to email me or reach out to me on LinkedIn:
- Email: [email protected]
- Email: [[email protected]] (mailto:[email protected])
- LinkedIn: Sarthak Janrao
- LinkedIn: [Rohit Lad] (https://www.linkedin.com/in/rohit-lad-1550b4259/)