https://github.com/pranavv34/navigo-fedexhackathon
NAVIGO is a dynamic routing system that optimizes delivery routes while minimizing carbon footprint by integrating real-time traffic, weather, and emissions data.
https://github.com/pranavv34/navigo-fedexhackathon
api fedex flask hackathon-project reactjs
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NAVIGO is a dynamic routing system that optimizes delivery routes while minimizing carbon footprint by integrating real-time traffic, weather, and emissions data.
- Host: GitHub
- URL: https://github.com/pranavv34/navigo-fedexhackathon
- Owner: pranavv34
- Created: 2025-01-07T17:33:14.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-07T18:03:02.000Z (over 1 year ago)
- Last Synced: 2025-01-07T18:45:08.396Z (over 1 year ago)
- Topics: api, fedex, flask, hackathon-project, reactjs
- Language: Python
- Homepage:
- Size: 186 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# NAVIGO: Precision Route Optimization Technology
NAVIGO is a dynamic routing system that optimizes delivery routes while minimizing carbon footprint by integrating real-time traffic, weather, and emissions data.
## 🎯 Problem Statement
The logistics and transportation industry faces challenges in:
- Optimizing routes for timely deliveries
- Minimizing carbon footprint
- Managing real-time traffic conditions
- Adapting to weather impacts
## ⚡ Key Features
- **Real-time Traffic Integration**: Uses TomTom API to avoid congestion and reduce travel time
- **Weather Impact Analysis**: Integrates AQICN data for weather-aware routing
- **Emission Estimation**: Calculates CO2, NOx, and Particulate Matter emissions per route
- **Route Optimization**: Leverages OSRM for efficient route calculation
- **User-Friendly Interface**: Simple input for vehicle details and destinations
## 🛠️ Technology Stack
### Frontend
- React.js
- Interactive mapping interface
- Real-time route visualization
### Backend
- Flask (Python)
- Multi-threaded API processing
- Advanced routing algorithms
### APIs
- TomTom: Traffic data
- AQICN: Weather and air quality data
- OSRM: Route optimization
## 🚀 Getting Started
### Note:
Our current UI is minimal and serves as a basic interface for showcasing the system's functionality. We plan to improve the UI for a more polished and user-friendly experience. The backend functionality is complete, and the presentation has been submitted.
### Prerequisites
```bash
python 3.x
npm/yarn
```
### Installation
1. Clone the repository
```bash
git clone [repository-url]
```
2. Install backend dependencies
```bash
cd backend
pip install -r requirements.txt
```
3. Install frontend dependencies
```bash
cd frontend
npm install
```
### Running the Application
1. Start the Flask backend
```bash
python app.py
```
2. Start the React frontend
```bash
npm start
```
## 🔄 System Flow
1. **User Input**: Vehicle details and destination
2. **Data Collection**: Parallel API requests for traffic and weather
3. **Route Calculation**: OSRM optimization considering all factors
4. **Emission Analysis**: Calculate environmental impact
5. **Results**: Display optimized route with emission metrics
## 🎯 Future Enhancements
- Machine Learning integration for predictive analytics
- Telematics integration for real-time vehicle data
- Mobile application development
- Enhanced emission prediction models
## 👥 Team
- Pranav Vuddagiri
- Vishnu Vamsith Yejju
## 🤝 Acknowledgments
- FedEx Smart Hackathon
- API Service Providers