Team Member Name

Muhammad Alif Asyraf bin Mohd Azlan (Leader) Muhammad Farhan Aiman bin Mohd Fairuz Muhammad Fariz Danial bin Risman MUHAMMAD NUR FITRI BIN FAISAL

Project Info

🏘️ SmartHabit-MY AI-Driven Housing Affordability & Inclusivity Dashboard for Malaysia

SDG XI Hackathon 2025 | Smart Mobility & Communities | SDG 11: Sustainable Cities

🎯 Project Overview SmartHabit-MY is an intelligent dashboard that helps Malaysians find affordable and livable housing options using cutting-edge AI technologies:

Fuzzy Logic Engine: Handles uncertainty in housing decisions with intelligent livability scoring Machine Learning Predictor: Random Forest model predicts fair rental prices Interactive Visualization: Beautiful dark-themed dashboard with real-time insights

💡 Key Features

Fuzzy Livability Logic Engine (Innovation Highlight) Uses fuzzy inference to assess housing livability Considers distance to transport and price affordability Outputs intelligent livability scores (0-100)
ML Affordability Predictor Random Forest model trained on Malaysian housing data Predicts fair rental prices based on location features Displays R² and MSE metrics for transparency
Interactive Dashboard User-friendly sidebar for preference input Real-time metric cards showing predictions Interactive scatter plots with highlighted recommendations AI-powered text recommendations

🎨 Technology Stack Frontend: Streamlit with custom CSS (Dark Theme + Neon Accents) Data Processing: Pandas, NumPy Machine Learning: Scikit-learn (Random Forest) Fuzzy Logic: Scikit-fuzzy Visualization: Plotly

📊 Dataset Real Dataset from Kaggle called "Rental Pricing Dataset": Kuala Lumpur & Selangor locations Rental prices (RM 800 - 5000) Distance to MRT (0.5 - 15 km) Safety indices and amenity counts 🏆 Hackathon Judging Criteria Alignment ✅ Innovation: Fuzzy Logic for livability assessment (unique approach) ✅ Technical Implementation: ML + Fuzzy Logic + Interactive UI ✅ SDG Impact: Addresses SDG 11 (Affordable Housing & Sustainable Cities) ✅ User Experience: Modern, intuitive dark-themed dashboard ✅ Scalability: Modular code, easy to extend with real data

📝 Usage Example Select your preferred location (e.g., Cyberjaya) Set your budget (e.g., RM 2000) Choose max distance to MRT (e.g., 5 km) View AI recommendations with livability scores Explore interactive charts and top options

🔮 Future Enhancements Multi-criteria decision analysis (MCDA) User authentication and saved preferences Mobile-responsive design

👨‍💻 Developer Built for SDG XI Hackathon 2025 Focus: Smart Mobility & Communities (Housing & Urban Planning)

📄 License MIT License - Feel free to use and modify for your projects