📊 Real-Time Classroom Occupancy Monitoring App

A MERN-stack application to monitor classroom occupancy in real-time using Azure Digital Twins and Azure Application Insights.
Since physical IoT sensors are not available, the project simulates sensor data and demonstrates cloud integration, authentication, GenAI, responsive frontend, and modern web security practices.

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📐 System Architecture

🚀 Features

• 🔹 Real-Time Occupancy Simulation – Generates random occupancy values for classrooms.
• 🔹 Azure Digital Twins Integration – Models classrooms and tracks live occupancy.
• 🔹 Application Insights Telemetry & Logging –
  • Logs system events (errors, warnings, info)
  • Monitors failed/successful login attempts
  • Provides admin dashboards for activity monitoring
• 🔹 Authentication & Security
  • Google OAuth 2.0 for secure login
  • JWT-based authentication with distributed key system (JWKS)
  • Tokens sent via secure HTTP-only cookies
  • Rate limiting to prevent abuse
  • Input validation and secure headers
• 🔹 Role-Based Access – Different dashboards for students, faculty, and admins.
• 🔹 Responsive Frontend – Mobile-friendly UI with TailwindCSS + Shadcn/UI.
• 🔹 GenAI Service – Uses Google Gemini model to generate intelligent insights (e.g., usage summaries, recommendations).
• 🔹 Multi-Service Setup – Independent Node.js services running on different ports (Auth, Simulation, GenAI, API Gateway, Frontend).

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🛠️ Tech Stack

• Frontend: React (Vite, TailwindCSS, Shadcn/UI)
• Backend Services: Node.js, Express
• Database: MongoDB
• Cloud Services: Azure Digital Twins, Azure Application Insights
• GenAI Service: Google Gemini API

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📸 Screenshots:

Landing Page

Dashboard Page

Gen-AI Page

Admin Page-1

Admin Page-2

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🎯 Learning Goals

• Understand how Azure Digital Twins can represent physical spaces.
• Implement secure authentication (OAuth + JWT + cookies) in a distributed system.
• Learn real-time monitoring & logging using Application Insights.
• Build protected routes & responsive UI in React.
• Use GenAI (Google Gemini) for intelligent reporting.
• Practice multi-service architecture using different Node.js services.

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📚 Future Improvements

• Replace simulated data with real IoT sensors.
• Add WebSockets for instant occupancy updates.
• Extend GenAI service for predictive analytics (e.g., peak usage times).
• Add detailed admin dashboards for logs and telemetry insights.

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👨‍💻 Author

• [Sabarish M] – College Project for Cloud + Security + GenAI with MERN