Empowering Neurodiverse Adolescents through Adaptive Learning
LexAyudha is an innovative, AI-powered learning platform designed to assist adolescents with dyslexia and dyscalculia. By combining advanced AI, NLP, emotion detection, and multisensory teaching strategies, LexAyudha provides a truly personalized and inclusive educational experience. The system adapts content dynamically based on each learner’s cognitive and emotional state to improve comprehension, engagement, and confidence.
- 🎨 Chromatic Teaching Module – Reduces visual stress through real-time contrast and font adjustments.
- 🧾 Adaptive Content Generator – Simplifies sentences using a fine-tuned BERT model for individualized reading levels.
- 😐 Emotion Detection AI – Real-time facial analysis with Xception and MTCNN to tailor task difficulty based on emotion.
- 🔊 Speech Pace Optimizer – CNN-RNN model predicts ideal speech rate and delivers audio via Google TTS.
- 🧮 Touch Math Platform – Gamified, multisensory math learning with voice feedback and interaction tracking.
- AI-Powered Personalization – Emotion-aware, content-adaptive learning environment
- Speech & Audio Feedback – Real-time pronunciation and pace correction
- Gamified Math Support – Touch-point interaction and real-time quizzes
- Inclusive Design – WCAG-compliant UI with chromatic variation and font customization
- Progress Analytics – Emotional reports and academic insights for guardians and educators
- Python – Core language for AI modules
- TensorFlow & Keras – Model training for emotion and speech prediction
- BERT (fine-tuned) – Sentence simplification and level adaptation
- Xception Model + MTCNN – Real-time emotion classification
- Hybrid CNN-RNN – Speech pace prediction from mel spectrograms
- Wav2Vec 2.0 – Audio temporal pattern recognition
- React.js – Component-based UI
- Tailwind CSS – Utility-first responsive styling
- SVG + Canvas – Touch point math visualizations
- React-voice-visualizer – Speech calibration feedback
- Node.js & Express.js – API-driven services
- Python Flask – ML microservices
- MongoDB Atlas – NoSQL cloud database
- RabbitMQ – Messaging queue for microservice communication
- Docker & Kubernetes – Containerization and orchestration
- Librosa – Audio processing and mel spectrogram generation
- NLTK & SpaCy – NLP for sentence restructuring
- Chroma.js – Real-time visual theme rendering
- AWS Fargate – Serverless backend container hosting
- Vercel – Frontend deployment platform
- Firebase – Image storage and real-time data
- SendGrid – Transactional and notification emails
- Google TTS API – Custom speech playback
- GitHub Actions – CI/CD pipeline
- Git – Version control
- Jest – Unit testing
- Postman & Selenium – API and integration testing
- Apache JMeter – Performance and load testing
- Prometheus & Grafana – Monitoring and visualization
Developed as part of a BSc (Hons) Software Engineering final year project at the Sri Lanka Institute of Information Technology – 2025. EOF
- Node.js (v18 or higher)
- npm or yarn
- Git
-
Clone the repository
git clone https://github.com/IsuruX98/Intelligent-Eco-Urban-Monitoring-System.git cd Intelligent-Eco-Urban-Monitoring-System -
Install dependencies
npm install # or yarn install -
Set up environment variables
cp .env.example .env.local
Configure the following variables in
.env.local:NEXT_PUBLIC_EMAILJS_SERVICE_ID=your_emailjs_service_id NEXT_PUBLIC_EMAILJS_TEMPLATE_ID=your_emailjs_template_id NEXT_PUBLIC_EMAILJS_PUBLIC_KEY=your_emailjs_public_key
-
Add required assets
- Place team member images in
public/images/ - Add document PDFs in
public/documents/ - Add presentation PDFs in
public/presentations/
- Place team member images in
-
Run the development server
npm run dev # or yarn dev -
Open your browser Navigate to http://localhost:3000
IEMS-Static/
├── components/ # React components
│ ├── About.tsx # Team information
│ ├── Contact.tsx # Contact form and information
│ ├── Downloads.tsx # Documents and presentations
│ ├── Hero.tsx # Landing section
│ ├── Methodology.tsx # Project methodology
│ ├── Milestones.tsx # Project timeline
│ ├── Navbar.tsx # Navigation component
│ ├── ProjectScope.tsx # Literature survey and objectives
│ └── Technologies.tsx # Technology stack
├── pages/ # Next.js pages
│ ├── _app.tsx # App configuration
│ ├── _document.tsx # Document structure
│ └── index.tsx # Main page
├── public/ # Static assets
│ ├── documents/ # PDF documents
│ ├── images/ # Images and photos
│ └── presentations/ # Presentation files
├── styles/ # CSS styles
└── README.md # Project documentation
- ✅ Project Proposal - August 23, 2024
- ✅ Progress Presentation I - December 8, 2024
- 🔄 Research Paper - February 2025
- ⏳ Progress Presentation II - March 2025
- ⏳ Website Assessment - April 2025
- ⏳ Logbook - April 2025
- ⏳ Final Report - May 2025
- ⏳ Final Presentation & Viva - May 26, 2025
npm run dev- Start development servernpm run build- Build for productionnpm run start- Start production servernpm run lint- Run ESLintnpm run lint:fix- Fix ESLint errors
The project follows strict linting rules and TypeScript standards:
- ESLint configuration for React and TypeScript
- Proper entity escaping for accessibility
- Unused import detection and removal
- Consistent code formatting
- Topic Assessment - Research area and scope definition
- Project Proposal - Individual proposals (Google Drive)
- Research Paper - Academic publication (Coming Soon)
- Final Report - Individual project reports (Google Drive)
- Project Proposal - Initial concept presentation
- Progress Presentation I - Development progress showcase
- Progress Presentation II - Advanced functionality demo (Coming Soon)
- Final Presentation - Complete implementation overview (Coming Soon)
We welcome collaboration opportunities, research partnerships, and inquiries about IEMS. Whether you're a researcher, environmental agency, or technology partner, we'd love to hear from you.
- Email: [email protected]
- Phone: +94 76 685 9740
- Institution: Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
- GitHub Repository: LexAyuda GitHub
- Live Application: Coming Soon
This project is developed as part of academic research at Sri Lanka Institute of Information Technology (SLIIT). All documents and presentations are provided for educational and research purposes.
- Sri Lanka Institute of Information Technology (SLIIT)
- Department of Information Technology
- Department of Computer Science and Software Engineering
- Research supervisors and academic staff
- Environmental monitoring research community
LexAyudha - AI-Based Personalized Rehabilitation Tool for Dyslexic Adolescents
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For more information, visit our project website or contact our team.