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A transformative tool empowering farmers to sell directly to consumers while offering blockchain-based insurance for financial security.

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AgriLink

A transformative tool empowering farmers to sell directly to consumers while offering blockchain-based insurance for financial security.

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About The Project

AgriLink revolutionizes agricultural commerce by enabling farmers to bypass middlemen and directly connect with consumers, fostering fairer trade and higher profits. Our platform builds a vibrant community where farmers showcase their products, bridging the gap between farm and table.

🔗 Leveraging blockchain technology, AgriLink establishes a secure insurance pool, ensuring farmers receive timely payouts with minimal hassle. With blockchain-based insurance, accessing funds is streamlined, eliminating bureaucratic hurdles commonly associated with traditional banking systems.

Built With

  • Built with the power of MERN stack for seamless performance and scalability.
  • Smart contracts implemented in Solidity ensure transparency and security in insurance transactions.
  • Stripe integration facilitates smooth and secure payment processing for farmers and buyers alike.

Getting Started

  1. Clone Repository: Clone the AgroInsight repository from GitHub and navigate to the project directory.

  2. Install Dependencies: Navigate to the "Frontend" and "Backend" directories and run npm install to install the dependencies.

  3. Set Up Environment: Configure environment variables in the .env file following the provided template.

    • In the backend: Add a MONGO_URI, PORT (assume 5000), and a SECRET (for JWT verification).
    • In the frontend: Add the BACKEND_URI (address and port of the backend server) and MODEL_URI (address and port of the python model server).
  4. Start Servers:

    • Starting backend: Launch the backend server with node server in the "Backend" directory. If you have nodemon installed, run nodemon server for automatic restarts on file changes.
    • Starting frontend: Launch the frontend server with npm run dev in the "Frontend" directory.
    • Starting the Python server: Start the Python server containing the neural model by running uvicorn main:app --reload --port 8000.
  5. Explore Application: Access AgroInsight to begin exploring and customizing the application for your crop monitoring needs.

Note

Note: Before running the project, ensure that you have all necessary dependencies installed and configured according to the instructions provided in the "Getting Started" section.

Tip

Tip: For the best experience, consider running the project on a modern web browser such as Google Chrome or Mozilla Firefox.

Important

Important: Make sure to set up the environment variables correctly in the .env file before starting the backend and frontend servers.

Warning

Warning: Running the project without proper configuration or environment setup may result in unexpected errors or incomplete functionality.

Caution

Caution: Be cautious when modifying sensitive configuration settings or environment variables, as incorrect changes could lead to security vulnerabilities or data loss.

Like this project?

If you found this project helpful or interesting, please give it a star on GitHub! ⭐

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A transformative tool empowering farmers to sell directly to consumers while offering blockchain-based insurance for financial security.

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