Navya Agricultural Intelligence Platform

System Requirements

• Node.js (v18 or higher recommended)
• npm (comes with Node.js)
• That's it! No MongoDB or other database installation is required.

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Quickstart (Newbie Manual)

This project is built to be 100% plug-and-play. Just run these two commands and the entire platform (both frontend and backend) will start up:

1. Install everything:

   npm install

   (This automatically installs dependencies for both the frontend and backend folders.)

2. Start the app:

   npm start

   (This launches the backend API, the frontend React app, and the embedded offline database all at once!)

You can now view the app at: http://localhost:5173

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Important Notes: How It Works

The Database (Zero-Install Offline MongoDB)

You do not need to install MongoDB on your machine. When you run npm start, the backend uses a portable, embedded version of MongoDB (mongodb-memory-server).

• On its first run, it automatically downloads the correct MongoDB binary for your operating system (Windows, Mac, or Linux) in the background.
• It is configured to save data persistently to the backend/.mongo_data directory. This means your data is fully preserved even after you restart the server.
• This ensures the application works fully offline in edge environments (like a local server at an aggregator center) without any manual database setup.

Sync Manager

Because this platform acts as a "Local Edge Server", it is designed to work completely offline.

• We built a SyncManager service (backend/src/services/syncManager.js) that runs in the background.
• When an internet connection is available, it silently syncs the local database with the central cloud MongoDB (if configured), ensuring that data is never lost during offline periods.

Mock IoT Data

The frontend currently uses decoupled mock data to simulate real-world IoT sensor readings (Temperature, Humidity, Ethylene/VOC, Light).

• All hardcoded UI data was extracted into a single file: frontend/src/services/mockData.js.
• This allows developers to easily swap out the mock data for actual hardware API calls later by simply updating the imports, without needing to rewrite any React UI components.

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Detailed Technical Overview

Architecture

This repository contains a full-stack JavaScript application separated into two main workspaces:

• frontend/: A React application built with Vite. It contains dashboards for Aggregators and Farmers, as well as the public Quality Passport view.
• backend/: A Node.js/Express REST API that handles business logic, authentication, and database interactions using Mongoose.

Start Script Details

The root package.json uses the concurrently package to manage multiple processes. When you run npm start:

1. It runs npm run start:backend, which navigates to the backend and starts the Express server.
2. It runs npm run start:frontend, which navigates to the frontend and starts the Vite development server.
3. Inside the backend, before listening on port 5000, mongoWaker.js creates an isolated MongoDB instance natively using the downloaded binaries.

Folder Structure

• backend/src/models/: Mongoose schemas (e.g., User, Batch, QualityAssessment).
• backend/src/routes/: Express route handlers for the API endpoints.
• backend/src/utils/mongoWaker.js: The script responsible for booting the zero-install embedded MongoDB instance.
• frontend/src/pages/: React components organized by user roles (aggregator, farmer, public, common).
• frontend/src/services/mockData.js: Centralized JSON objects representing simulated IoT payloads.

Environment Variables (.env)

If you need to configure Cloud Sync or JWT secrets, create a .env file inside the backend/ directory. (Note: The .env file is safely ignored by git).

PORT=5000
JWT_SECRET=your_jwt_secret_here
# Optional: Set this to sync local data to the cloud when online
CLOUD_MONGO_URI=mongodb+srv://...