Interactive Analysis of College Attendance Systems with AI Tools

This project is an interactive, single-page web application that provides a comprehensive analysis of attendance systems used in Indian engineering colleges. It visualizes data on system adoption and effectiveness, compares different attendance-taking methods, and presents case studies from various institutions.

The standout feature is a suite of AI-powered tools, built using the Google Gemini API, designed to assist administrators, faculty, and students with common attendance-related challenges.

✨ Key Features

• Interactive Data Visualizations: Uses Chart.js to display the adoption rates of different systems and their effectiveness in reducing proxy attendance.
• Methods Comparison: A detailed breakdown of various attendance methods (Manual, Biometric, QR Code, Facial Recognition) with their pros, cons, and vulnerability to "proxy" attendance.
• Case Studies: Presents real-world examples and trends from institutions like IITs, NITs, and other top state universities.
• AI-Powered Attendance Suite (Powered by Gemini):
  • Policy Drafter: An administrative tool to automatically generate formal attendance policy notices.
  • System Auditor: A security tool that analyzes a described attendance process to identify potential loopholes.
  • Excuse Validator: A tool for faculty to analyze the genuineness of student excuses and generate a reply.
  • Recovery Planner: A tool for students to calculate the required number of classes they need to attend to meet the minimum attendance criteria.

🚀 How to Use

1. Clone the repository:

   git clone <repository-url>

2. Navigate to the project directory:

   cd <repository-name>

3. Add your API Key:

   • Open the script.js file.
   • Find the line const apiKey = "GEMINI_API_KEY";.
   • Replace the placeholder key with your own Google Gemini API key.

   Warning The AI-powered features will not work without a valid API key.

4. Open the application:

   • Simply open the index.html file in your web browser. No special server is needed.

🛠️ Technology Stack

• Frontend: HTML, Tailwind CSS, Vanilla JavaScript
• Libraries:
  • Chart.js for data visualization.
  • Marked.js for rendering Markdown from the AI's response.
• AI: Google Gemini API