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Mind Master

Mind Master is an AI-powered platform designed to enhance the learning experience by dynamically adjusting study content based on the user's real-time emotional expressions.

Table of Contents

Features

  • Upload Study Materials: Users can upload documents, presentations, and other educational resources to the platform.
  • AI-Based Emotion Recognition: Using advanced computer vision techniques, Mind Master analyzes the user's facial expressions through the webcam during study sessions.
  • Dynamic Content Adjustment: The AI adjusts the presented content in real-time, modifying the complexity, format, or focus based on detected emotions .
  • Enhanced Learning Experience: Personalized content suggestions help keep the user motivated, focused, and better able to understand complex materials.

How It Works

  1. Upload Content: Users upload their study material (PDF, PPT, etc.) to the portal.
  2. Emotion Detection: While the user studies, the AI uses the webcam feed to continuously monitor their facial expressions.
  3. Content Analysis: The AI analyzes the uploaded study materials and breaks them down into manageable sections or key points.
  4. Dynamic Adaptation: Based on the detected emotional cues, the platform adjusts the content, offering simplified explanations, deeper insights, or alternative formats (e.g., visual aids, summaries).

Installation

  1. Clone the repository
  2. Install dependencies
  3. Run the application

Usage

  1. Upload your study material: After launching the application, upload your study materials in supported formats.
  2. Enable Webcam Access: Ensure you grant access to your webcam for real-time emotion tracking.
  3. Begin your study session: As you study, the AI will observe and adjust the content based on your emotional responses, offering real-time feedback and content adjustments.

Tech Stack

We will update later after first version of our website

  • Backend: Python, Flask
  • Frontend: HTML, CSS, JavaScript (React)
  • AI Model: Facial emotion recognition and natural language processing (NLP) for content analysis
  • Database: PostgreSQL for storing user data and study materials
  • Deployment: Docker, AWS/GCP

Contributing

We will soon look at it