🎓 Edutwin AI

Centralised Digital-Twin Platform for Student Activity Records & Institutional NAAC Accreditation Forecasting in HEIs

Transforming higher education administration with AI OCR, predictive ML credit projections, TF-IDF skill density mapping, vector-based career alignment, and automated NAAC institutional CGPA forecasting.

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📌 Executive Summary

Edutwin AI is an institutional digital-twin ecosystem built specifically for Higher Education Institutions (HEIs). Traditional manual certificate collection and credit auditing workflows suffer from data fragmentation, verification delays, and lack of real-time insights into institutional accreditation standards (such as NAAC).

Edutwin AI bridges this gap by deploying an intelligent, multi-role digital platform that standardizes student activity logging, automates faculty credit verification, dynamically maps department-wide skill vectors, and delivers real-time accreditation CGPA forecasting for academic leadership.

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✨ Key Platform Capabilities

🤖 1. AI-Powered OCR & Certificate Parser

• Extracts critical activity data directly from uploaded certificates, including Event Title, Category, Organizing Body, and Date.
• Generates an AI Confidence Score (%) and suggests credit allocation to streamline faculty verification workflows.

📈 2. ML Graduation Credit Projector

• Implements linear regression models to analyze individual participation velocity.
• Projects expected credit accumulation by graduation, highlighting students requiring academic intervention or credit acceleration.

🧠 3. TF-IDF Departmental Skill Density Engine

• Analyzes unstructured text in verified achievement logs using TF-IDF (Term Frequency-Inverse Document Frequency) classification algorithms.
• Dynamically maps department-level core competencies (e.g. Software Development, Machine Learning, Leadership, Research & Publications).

🎯 4. Cosine Similarity Career Alignment Matcher

• Converts verified student skill profiles into high-dimensional vector representations.
• Evaluates Cosine Similarity against industry role matrices to output percentage job readiness and personalized skill gap recommendations.

🏆 5. Institutional NAAC Accreditation Forecaster

• Computes institutional CGPA metrics (scaled from 0.00 to 4.00) in real time based on departmental student participation density and verified co-curricular achievements.
• Provides institutional leadership with actionable data breakdowns across engineering, management, and science departments.

🛡️ 6. Multi-Tiered Role-Based Access Control (RBAC)

• Dedicated, secure dashboards customized for three institutional stakeholders:
  • Students: Log achievements, track credit progress, run ML projections, and view career match vectors.
  • Faculty Reviewers: Audit pending student submissions, review AI confidence ratings, adjust credits, and leave feedback.
  • System Admins: Institutional analytics, NAAC CGPA breakdown, departmental metrics, and system-wide audit controls.

📄 7. Dynamic NLG Resume & Public PDF Portfolio

• Automatically compiles student achievement records into shareable web portfolios with custom Natural Language Generation (NLG) summaries.
• Supports native browser print-to-PDF formatting for institutional submissions and employer sharing.

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🗺️ System Architecture

flowchart TD
    subgraph Client_Layer ["Frontend Application (Vite + React 19 + TypeScript)"]
        UI_Student["Student Dashboard (Log Activities & Run ML)"]
        UI_Faculty["Faculty Reviewer Dashboard (Audit & Allocate Credits)"]
        UI_Admin["Admin NAAC Dashboard (CGPA Analytics & Dept Metrics)"]
        UI_Portfolio["Public Student Portfolio (PDF Generator & NLG Summaries)"]
    end

    subgraph Service_Layer ["Services & ML Analytics Engine"]
        OCR["AI OCR Certificate Parser"]
        ML_Proj["ML Credit Projector (Linear Regression)"]
        TFIDF["TF-IDF Skill Density Engine"]
        Cosine["Vector Cosine Similarity Matcher"]
        NAAC_Engine["NAAC Forecaster Engine"]
    end

    subgraph Database_Layer ["Backend Infrastructure (Supabase Cloud)"]
        Auth["Supabase Auth (JWT & Role Claims)"]
        DB[("Supabase Postgres DB (Profiles & Activities Tables)")]
        Storage["Supabase Storage Bucket (Certificate Documents)"]
        RLS["Row-Level Security Policies"]
    end

    UI_Student --> Auth
    UI_Faculty --> Auth
    UI_Admin --> Auth
    UI_Student --> OCR
    OCR --> Storage
    UI_Student --> ML_Proj
    UI_Student --> Cosine
    UI_Faculty --> DB
    UI_Admin --> NAAC_Engine
    NAAC_Engine --> TFIDF
    DB --- RLS

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👥 Role-Based Capabilities Matrix

Feature / Capability	Student	Faculty Reviewer	Admin
Certificate Upload & AI OCR Extraction	✅	—	—
View Individual Credit Velocity & ML Projection	✅	—	—
Vector Cosine Career Skill Matcher	✅	—	—
Audit & Verify Student Submissions	—	✅	✅
Custom Credit Allocation & Feedback	—	✅	✅
Departmental Skill Density Visualizer	—	✅	✅
Institutional NAAC Accreditation CGPA Forecaster	—	—	✅
Public Portfolio & PDF Resume Export	✅	✅	✅

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🛠️ Technology Stack

Layer	Technology	Purpose & Usage
Frontend Framework	React 19	Modern UI component rendering with high reactivity
Language	TypeScript 6	End-to-end static type safety and contract enforcement
Build Tool	Vite 8	Rapid bundling, HMR, and lightning-fast developer experience
Styling & UI	Tailwind CSS v4	Design system tokens, responsive glassmorphism & 3D micro-interactions
Icons & Visuals	Lucide React	Clean, accessible SVG icons
Database	Supabase Postgres	Relational data persistence for profiles and activity records
Authentication	Supabase Auth	Secure authentication handling role-based state
Security Layer	Supabase RLS	Row Level Security enforcing strict data isolation per user
Storage	Supabase Storage	Public/Private cloud bucket storing student certificates
Hosting & CI/CD	Vercel	Edge deployment and continuous integration

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📂 Project Directory Structure

Edutwin-AI/
├── .env                       # Environment configuration (Supabase keys)
├── .gitignore                 # Excluded dependencies and build artifacts
├── EDUTWIN_AI_PROJECT_REPORT.md # Comprehensive institutional research report
├── EDUTWIN_AI_PROJECT_REPORT.pdf # Full formatted PDF project document
├── README.md                  # Project documentation
├── eslint.config.js           # ESLint linting configuration
├── index.html                 # HTML application shell
├── package.json               # Package dependencies & scripts
├── public/                    # Static assets & public resources
├── src/
│   ├── App.tsx                # Client-side router configuration
│   ├── main.tsx               # Bootstrap & 3D parallax interaction engine
│   ├── index.css              # Custom Tailwind directives & SaaS design tokens
│   ├── assets/                # App image assets & logos
│   ├── components/            # Reusable UI components (Navbar, CustomButton, etc.)
│   ├── lib/                   # Supabase client initialization
│   ├── pages/                 # Role-based page views
│   │   ├── Activities.tsx     # Student Activity Logging & OCR interface
│   │   ├── AdminDashboard.tsx # Institutional Analytics & NAAC Forecaster
│   │   ├── FacultyDashboard.tsx# Faculty Verification & Audit Panel
│   │   ├── Login.tsx          # Authentication login view
│   │   ├── Portfolio.tsx      # Public Student Portfolio & PDF Export
│   │   ├── Profile.tsx        # User profile settings & register metadata
│   │   ├── Register.tsx       # Student & Faculty registration view
│   │   └── StudentDashboard.tsx# Student overview & ML credit predictor
│   ├── services/              # API & database service layer
│   │   ├── activityService.ts # Activity CRUD, metadata serialization & joins
│   │   ├── authService.ts     # User authentication handling
│   │   ├── profileService.ts  # User profile fetching & upserting
│   │   └── storageService.ts  # Certificate document storage uploads
│   └── types/                 # Centralized TypeScript interface definitions
│       └── index.ts           # Core types (Profile, Activity, NAACSummary, etc.)
├── supabase_setup.md          # SQL database schemas, triggers & RLS policies
├── tsconfig.json              # TypeScript compiler configuration
├── vercel.json                # Vercel deployment configuration
└── vite.config.ts             # Vite build & plugin configurations

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📦 Quick Start & Local Setup

1. Prerequisites

Ensure you have the following installed on your machine:

• Node.js (v18.0.0 or higher)
• npm (v9.0.0 or higher) or pnpm / yarn
• A Supabase account (Free tier works perfectly)

2. Clone the Repository

git clone https://github.com/Mugilan-md/Edutwin-AI.git
cd Edutwin-AI

3. Install Dependencies

npm install

4. Environment Variables Setup

Create a .env file in the project root directory:

VITE_SUPABASE_URL=https://your-supabase-project-id.supabase.co
VITE_SUPABASE_ANON_KEY=your-supabase-anon-public-key

5. Database Schema Initialization

1. Open your Supabase Project Console.
2. Navigate to the SQL Editor.
3. Copy the database setup script from supabase_setup.md.
4. Run the query to create tables (profiles, activities), enable Row Level Security (RLS), and apply policies.

6. Start Development Server

npm run dev

Open your browser at http://localhost:5173.

7. Production Build Verification

To compile the TypeScript project and bundle production artifacts:

npm run build

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🔒 Security & Database Policy Design

Edutwin AI enforces security at both the application level and database layer using Supabase Row Level Security (RLS):

• Profiles Table:
  • SELECT: Public access to view student profiles for portfolio generation.
  • INSERT / UPDATE: Users can only edit their own profile matching auth.uid().
• Activities Table:
  • SELECT: Students can view their own activities; Faculty and Admins can view all pending/approved activities.
  • INSERT: Students can insert activities bound to student_id = auth.uid().
  • UPDATE: Faculty and Admins can update status, credits, and feedback.

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📜 License

Distributed under the MIT License. See LICENSE for details.

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_{Built by ❤️ B . MUGILAN}