An Interactive Educational Platform Demonstrating the Synergy of AI, IoT, and Big Data
🚀 Quick Start • 📖 Documentation • ✨ Features • 🎯 Target Audience
- About SINERGI
- Key Features
- Target Audience
- Quick Start
- Technology Stack
- Project Structure
- Documentation
- Contributing
- License
SINERGI (Synergy of Intelligent Networks, Edge computing, Real-time analytics, Governance, and Innovation) is a comprehensive educational and sandbox demonstration platform that showcases the transformative power of AI, IoT, and Big Data in modern information systems.
In today's rapidly evolving tech landscape, understanding the intersection of AI, IoT, and Big Data is crucial. SINERGI provides:
- Interactive Learning: Hands-on modules with real code execution
- Real-World Simulations: Live IoT device simulations with real-time data
- Practical Experience: Jupyter-like notebook workspace for experimentation
- Industry Datasets: 10+ curated datasets from various industries
- AI-Powered Assistance: Integrated AI tutors and coding helpers
- Professional Outputs: Generate certifications and business case reports
- 12 Comprehensive Modules covering beginner to advanced topics
- Interactive quizzes with instant feedback
- Progress tracking and achievement system
- Difficulty levels: Easy, Medium, Hard
- Real code examples with syntax highlighting
- Visual interactive architecture diagrams
- Deep-dive into each component (IoT Layer, Data Layer, AI Layer, Edge Computing)
- Technology recommendations and best practices
- Real-world implementation patterns
- Real-time IoT device simulations
- Multiple device types: Temperature sensors, Smart meters, GPS trackers, Industrial machines
- Live data streaming with MQTT protocol
- Anomaly detection and alerts
- Data export capabilities
- 6 Practical labs with step-by-step guides
- Real Python code execution via Pyodide
- Labs cover: IoT basics, data processing, ML integration, real-time analytics
- Code editor with syntax highlighting
- Import datasets directly from Dataset Library
- Jupyter-like interactive environment
- Real Python execution in browser
- Pre-loaded libraries: pandas, numpy, scikit-learn, matplotlib
- Save and manage multiple notebooks
- Import datasets for analysis
- 10 Industry Datasets including:
- Manufacturing Equipment Sensors
- Patient Vital Signs Monitoring
- Smart City Traffic Analytics
- Financial Transaction Stream
- Smart Agriculture IoT Data
- Supply Chain Tracking Data
- Search and filter capabilities
- CSV export functionality
- Direct integration with Labs and Notebooks
- ROI Calculator with customizable parameters
- Professional PDF report generation
- QR code embedded reports
- Scenario analysis (Conservative, Moderate, Aggressive)
- Cost-benefit breakdown
- Comprehensive governance frameworks
- GDPR, HIPAA, ISO compliance guides
- Best practices for data privacy and security
- Industry-specific regulations
- Professional certification generation
- Comprehensive Progress Tracking
- Quiz performance analytics
- Time tracking per module
- Learning streaks and consistency metrics
- Category-based performance breakdown
- 7-day activity visualization
- Personalized insights and recommendations
- Export analytics data
- AI Learning Assistant: Get explanations, examples, and learning guidance
- AI Coding Helper: Debug code, get suggestions, and learn best practices
- Powered by Perplexity API
- Context-aware responses
Perfect for students learning about IoT, Big Data, AI, and Information Systems
Upskill in modern tech stacks and architectural patterns
Understand technical capabilities and make informed decisions
Learn about governance, compliance, and ethical considerations
Explore possibilities and build business cases for IoT/AI solutions
- Node.js 18+
- npm or yarn
- Modern web browser (Chrome, Firefox, Safari, Edge)
-
Clone the repository
git clone https://github.com/yourusername/sinergi.git cd sinergi -
Install dependencies
npm install # or yarn install -
Set up environment variables
cp .env.example .env.local
Add your API keys:
PERPLEXITY_API_KEY=your_api_key_here
-
Run the development server
npm run dev # or yarn dev -
Open your browser
http://localhost:3000
- 🎓 Start with Learning Hub - Complete Module 1 (Introduction to IoT)
- 🏗️ Explore Architecture Explorer - Understand the system components
- 🔄 Try Live Simulator - See real-time IoT data in action
- 🧪 Complete a Hands-on Lab - Build your first IoT data processor
- 📈 Check Analytics Dashboard - Track your progress
- Next.js 14 - React framework with App Router
- TypeScript - Type-safe development
- Tailwind CSS - Utility-first styling
- Framer Motion - Smooth animations
- Recharts - Data visualization
- Lucide React - Icon library
- Pyodide - Python runtime in WebAssembly
- CodeMirror - Code editor with syntax highlighting
- Perplexity API - AI-powered assistance and learning
- React Hooks - State management
- LocalStorage - Progress persistence
- Context API - Global state
- jsPDF - Professional report generation
- QR Code - Certificate verification
- WebSocket-ready - For future real-time features
- MQTT concepts - IoT protocol demonstrations
sinergi/
├── src/
│ ├── app/
│ │ ├── page.tsx # Main application entry
│ │ └── layout.tsx # Root layout
│ ├── components/
│ │ ├── ui/ # Reusable UI components
│ │ ├── learning-hub.tsx # Learning modules
│ │ ├── architecture-explorer.tsx
│ │ ├── live-simulator.tsx
│ │ ├── hands-on-labs.tsx
│ │ ├── notebook-workspace.tsx
│ │ ├── dataset-library.tsx
│ │ ├── business-case-builder.tsx
│ │ ├── policy-governance.tsx
│ │ ├── analytics-dashboard.tsx
│ │ ├── ai-assistant.tsx
│ │ └── quiz-modal.tsx
│ ├── lib/
│ │ ├── modules.ts # Learning module data
│ │ ├── datasets.ts # Dataset definitions
│ │ ├── labs.ts # Lab content
│ │ └── utils.ts # Utility functions
│ └── styles/
│ └── globals.css # Global styles
├── public/
│ └── .well-known/
│ └── farcaster.json # Farcaster integration
├── docs/
│ ├── USER_GUIDE.md # User documentation
│ ├── DEVELOPER_GUIDE.md # Developer documentation
│ ├── API_REFERENCE.md # API documentation
│ └── DEPLOYMENT_GUIDE.md # Deployment guide
├── README.md # This file
├── package.json
├── tsconfig.json
└── tailwind.config.ts
- User Guide - Complete guide for end users
- Developer Guide - Technical documentation for developers
- API Reference - API endpoints and integrations
- Deployment Guide - How to deploy SINERGI
- Dark theme with vibrant purple/cyan neon accents
- Glassmorphism effects
- Smooth animations and transitions
- Modern, futuristic UI
- Intuitive navigation
- Progressive disclosure
- Real, tangible outputs (no mockups)
- Cross-feature integration
- Persistent progress tracking
- Learn by doing
- Immediate feedback
- Real code execution
- Industry-relevant examples
- Gamification elements
- ✅ 12 Learning modules with quizzes
- ✅ Architecture Explorer
- ✅ Live IoT Simulator
- ✅ 6 Hands-on Labs
- ✅ Notebook Workspace
- ✅ 10 Industry Datasets
- ✅ Business Case Builder
- ✅ Policy & Governance
- ✅ Analytics Dashboard
- ✅ AI Assistant & Coding Helper
- 🔄 Multi-user collaboration
- 🔄 Social learning features
- 🔄 More advanced labs
- 🔄 Video tutorials
- 🔄 Certification programs
- 🔄 Community marketplace for notebooks
- 🔄 Real hardware integration guides
- 🔄 Mobile app
We welcome contributions! Whether it's:
- 🐛 Bug reports
- ✨ Feature requests
- 📝 Documentation improvements
- 🔧 Code contributions
Please see our Contributing Guidelines for details.
This project is licensed under the MIT License - see the LICENSE file for details.
- Built with Next.js
- AI powered by Perplexity
- Python execution via Pyodide
- Icons by Lucide
- UI components inspired by shadcn/ui
- 📧 Email: support@elpeef.com
- 🌐 Web: elpeef.com
Built with ❤️ for the future of education
SINERGI - Smart Integration of AI, IoT, and Big Data; Version: 1.0.0