An intelligent Public Transport Analytics & Optimization System built using Machine Learning + Interactive Streamlit Dashboard to reduce overcrowding, improve scheduling, and enable smarter urban mobility decisions.
👉 Try the Live Project:
https://routewise---ai-transport-optimization-system-yssewfosdumjt9kfg.streamlit.app/
👉 View Source Code:
https://github.com/shreya975/RouteWise---AI-Transport-Optimization-System
Traditional public transport systems operate on fixed routes and schedules, while real-world passenger demand changes continuously.
This creates issues such as:
- 🚨 Overcrowded buses during peak hours
- 🚌 Underutilized buses during off-peak hours
- ⏳ Delays and poor commuter experience
- ⛽ Fuel and resource wastage
RouteWise solves this using AI-powered demand prediction and smart optimization.
- 📊 Passenger Demand Prediction using Machine Learning
- 🚦 Traffic-Aware Decision System
- 🧠 Smart Service Recommendations
- 🗺️ Interactive Route Map Visualization
- 🔮 What-If Simulation (Add Extra Buses)
- 📈 Demand Heatmaps & Trend Analysis
⚠️ Overcrowding Detection- 🔄 Alternative Route Suggestions
- 📋 Route Comparison Dashboard
The system automatically suggests actions such as:
- ➕ Add Extra Buses
- 🔁 Reroute Vehicles
- ⏱ Increase Service Frequency
- 🛑 Reduce Frequency During Low Demand
- ✅ Continue Normal Operation
- Passenger Load
- Traffic Conditions
- Delay Time
- Peak Hours
- Route Demand Patterns
- Collect transport and demand-related data
- Process data and create smart features
- Use Random Forest ML Model for demand prediction
- Analyze crowd level and route efficiency
- Generate recommendations instantly
- Display outputs through dashboard visualizations
- Route & Stop Data
- GPS Coordinates (Latitude / Longitude)
- Passenger Demand Count
- Traffic Levels
- Delay & Speed Data
- Bus Load Factor
- Bus Count
- Travel Distance & Time
- Peak Hour Indicators
- AI Recommendation Fields
- Python 🐍
- Streamlit 🌐
- Scikit-learn 🤖
- Pandas 📊
- NumPy 🔢
- Plotly 📈
- Folium 🗺️
git clone https://github.com/shreya975/RouteWise---AI-Transport-Optimization-System.git
cd RouteWise---AI-Transport-Optimization-System
pip install -r requirements.txt
python -m streamlit run app.py
- 🚦 Live Traffic API Integration
- 📍 Real-time Bus GPS Tracking
- 🌦️ Weather-Based Demand Prediction
- 📱 Passenger Mobile App
- 🎫 Smart Ticketing Integration
- 🏙️ Government Smart City Deployment
- 🚇 Multi-Modal Transport Sync (Bus + Metro)
- 🤖 Deep Learning Based Demand Forecasting
- 📊 Advanced Admin Analytics Dashboard
Built as a solution during a 24-Hour Hackathon at VNIT to solve real-world transport challenges using AI, Machine Learning, and Data Analytics.
The goal was to create a smart transport system that can predict passenger demand, optimize routes, and improve urban mobility efficiency.
RouteWise doesn’t just move people — it moves cities intelligently.