Student Management System Backend

Features

1. Management Features

• Create and Edit Records: Management can create and edit records for both teachers and students.
• Authentication: Firebase Authentication is used for student login, while teachers have separate authentication.

2. Profile and Academic Information

• Profile Access: Teachers and students can view their profiles.
• Fee Details: Students can view their fee details.
• Results: Students can access their academic results.

3. Learning Materials and Assignments

• Material Distribution: Teachers can efficiently send learning materials and assignments to their students using GraphQL.
• Assignment Checking: Student assignments are automatically checked using ChatGPT APIs.

4. Attendance and Examination

• Automatic Attendance: Attendance is automatically tracked using AWS Rekognition.
• Examination Proctoring: AWS Rekognition is used for examination proctoring to ensure exam integrity.

Tools and Technologies

• Firebase: Used for authentication and real-time database.
• Node.js: Backend framework.
• MongoDB: Used as the database.
• OpenAI APIs: Used for automatic assignment checking.
• AWS Rekognition: Used for automatic attendance and examination proctoring.
• AWS Textract: Used for document analysis.
• AWS Lambda: Used for serverless deployment.
• AWS ECR: Used for containerized deployment.
• GitHub Actions: Used for CI/CD and deploying the backend.

Setup and Deployment

Prerequisites

• Node.js installed
• Firebase account and project setup
• AWS account with Rekognition, Textract, Lambda, and ECR services enabled
• OpenAI API key

Installation

1. Clone the repository:

   git clone https://github.com/Tushar2001bbdu/SMS_BACKEND

   2. Install dependencies:

   npm install

2. Set up environment variables:

   • Create a .env file in the root directory.
   • Add the following environment variables:

     FIREBASE_API_KEY=<your-firebase-api-key>
     FIREBASE_AUTH_DOMAIN=<your-firebase-auth-domain>
     FIREBASE_PROJECT_ID=<your-firebase-project-id>
     AWS_ACCESS_KEY_ID=<your-aws-access-key-id>
     AWS_SECRET_ACCESS_KEY=<your-aws-secret-access-key>
     OPENAI_API_KEY=<your-openai-api-key>

Running the Application

1. Start the development server:

   npm run start

2. The backend will be available at http://localhost:3001.

Deployment

• The backend is deployed using AWS Lambda and AWS ECR for containerized deployments. GitHub Actions are used to automate the deployment process. Each push to the main branch triggers a deployment workflow.

Contributing

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Commit your changes and push to your branch.
4. Open a pull request to the main branch.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions or support, please contact tusharkumargupta032@gmail.com.