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.
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.
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- Landing Page which lists all the features of the app
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- Fast and secure authentication
- JWT tokens used to persist the authentication state
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Shows bried information about all the exams assigned to the user
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The user can start an exam only at the correct timeslot
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Simple and minimalistic exam page where the user can answer MCQ-based questions
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The user can view and track their progress
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AI-powered face motion detector
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I've used Google's Mediapipe library to track the motion of the user's face
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This app can check if a user is trying to cheat by monitoring the co-ordinates of their face
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The face detection is performed on-device without sending anything to the backend
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Thus, Face detection is fast and real-time
Anti-Cheat.Web.Demo.MP4.mp4
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Next.js (React)
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TypeScript
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Redux
- Flutter
- MobX + Provider
- Google Mediapipe (Web)
- Google on-device ML-Kit (Mobile)
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First setup the backend by following the instructions in this repository
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The test username and password are given in the login form
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Allow permissions for camera and mic when asked
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Make sure the
BACKEND_URL
is appended with/api
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Clone the project
https://github.com/prathamesh-mutkure/anti-cheat-app-web.git
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Install all the packages
npm install
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Create a
.env
file and set the following variables or as shown in the.env.example
file-
BACKEND_URL
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AUTH_SECRET
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Run the app
npm run dev
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Open
http://localhost:3000
with your browser to see the app
To make sure your changes don't break anything, run npm run dev
to run unit tests.
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Mobile App (Android & iOS)
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Project Thesis (Submitted mobile app as final year project for my diploma)
Feel free to contact me on Twitter or LinkedIn, know more about me at prathamesh.co