Smart Attendance System

Abstract

1. Introduction

Smart Attendance Management System is an application developed for daily attendance of student/ staff in colleges or schools or any other organizations. This project attempts to record attendance through face detection and live location. The objective of this project is to develop a system for managing attendance that can be used by all individuals in educational institutions or in any organization. This software requires to store the user's own image to be detected. The system will load the user’s image at the sign-up step. For giving attendance the user needs to sign in and the real time image of the user will be captured to take the attendance and it will be matched with the stored image of the person. The proposed system records attendance without allowing any chance of proxy attendance by the students. The administrator maintains the database. After verifying the user, the attendance will be taken, and it will be saved in an excel sheet with their live location and time of attendance. In this approach, face recognition and face detection are used. This face detection differentiates faces from non-faces and is therefore essential for accurate attendance. The other strategy involves face recognition for marking the accurate attendance of the students.

2. Objective

Smart Attendance Management System is an application developed for daily attendance of student/ staff in colleges or schools or any other organizations using face detection and face recognition.

This project demonstrates how JavaScript, Django, PostgreSQL can be applied to a real-world Full Stack Web Development problem.

3. Key Features / Modules

• Facial Recognition: Utilizes the face-recognition library to recognize faces for attendance tracking.
• Responsive UI: A responsive and dynamic user interface developed using React, Redux, and Material UI.
• Database: Stores data in a PostgreSQL database for efficient data management.
• Cloudinary Integration: Manages photo storage using Cloudinary, ensuring scalability and accessibility.

4. Technology Stack

• Backend: Django, face-recognition library, Django REST Framework
• Frontend: React.js, React Router Dom, Redux.js, Material UI
• Database: PostgreSQL
• Photo Storage: Cloudinary

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/asheshmandal2003/smart-attendance-system.git
cd smart-attendance-system

1. Clone the repository:
2. Navigate to the project directory:
3. Setup the .env files using .example.env file in the corresponding directory.
4. Run the backend server
5. Run the frontend server:
6. Open your browser and navigate to http://localhost:3000.

git clone git@github.com:asheshmandal2003/smart-attendance-system.git

cd smart-attendance-system

cd server
pip install -r requirements.txt
python manage.py runserver

cd client
yarn
yarn dev --port 3000

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add role-based access control
• Deploy on a VPS or cPanel hosting with a custom domain
• Add automated tests and a CI pipeline

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Explain the frontend, backend and database layers of this application.
2. How is user authentication and authorisation implemented?
3. Describe the main database tables / collections and their relationships.
4. Which REST APIs or routes are exposed and what do they return?
5. How would you deploy this application to production?

9. Source Code & License

This project is developed by asheshmandal2003 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.