melvas6 / anti-cheat-app-web

An Online Exam Platform which detects cheating with the power of AI and ML

Anti-Cheat Exam App 🌟

A platform that aims to stop cheating in online exams with the power of AI and ML.

This is the web version of my Anti-Cheat Exam App with enhanced features, UI/UX, and performance.

• Demo

• About Project

• Features and Interfaces

  • Home
  • Login and Authentication
  • Dashboard
  • Exam
  • Face Detection

• Tech Stack

  • Front-end
  • Backend
  • Mobile App
  • Other Tools

• Important Points

• Getting Started Instructions

• Test Cases

• Links

• Contact

Features and Interfaces

I'm currently making some final changes to the web app and will soon update this document with the latest demo images of the web app.

1. Home Page

   • Landing Page which lists all the features of the app
   

2. Login Page (Authentication)

   • Fast and secure authentication
   • JWT tokens used to persist the authentication state
   

3. Dashboard

   • Shows bried information about all the exams assigned to the user

   • The user can start an exam only at the correct timeslot

   

4. Exam Page

   • Simple and minimalistic exam page where the user can answer MCQ-based questions

   • The user can view and track their progress

   

5. AI-powered face motion detector

   • I've used Google's Mediapipe library to track the motion of the user's face

   • This app can check if a user is trying to cheat by monitoring the co-ordinates of their face

   • The face detection is performed on-device without sending anything to the backend

   • Thus, Face detection is fast and real-time

     Anti-Cheat.Web.Demo.MP4.mp4

Tech stack

Frontend

• Next.js (React)

• TypeScript

• Redux

Backend

• Nodejs

• Express

• MongoDB

Mobile App

• Flutter
• MobX + Provider

Other Tools

• Google Mediapipe (Web)
• Google on-device ML-Kit (Mobile)

Points to remember while testing the app

1. First setup the backend by following the instructions in this repository

2. The test username and password are given in the login form

3. Allow permissions for camera and mic when asked

4. Make sure the BACKEND_URL is appended with /api

Instructions

1. Clone the project

   • https://github.com/prathamesh-mutkure/anti-cheat-app-web.git

2. Install all the packages

   • npm install

3. Create a .env file and set the following variables or as shown in the .env.example file

   • BACKEND_URL

   • AUTH_SECRET

4. Run the app

   • npm run dev

5. Open http://localhost:3000 with your browser to see the app

Test Cases

To make sure your changes don't break anything, run npm run dev to run unit tests.

Useful Links

• Project Demo

• Mobile App (Android & iOS)

• Backend Repository

• Project Thesis (Submitted mobile app as final year project for my diploma)

Need help?

Feel free to contact me on Twitter or LinkedIn, know more about me at prathamesh.co