SmartMap - AI-Powered Taxi Management System for Dubai

Table of Contents

• Overview
• Demo Video
• Problems We Are Solving
• Features
• Value Proposition
• Technologies Used
• Hackathon Context
• Future Enhancements
• Installation
  • Prerequisites
  • Backend Setup
  • Frontend Setup
• Running the Application
• Usage
• API Endpoints
  • Authentication
  • Data Retrieval
• Dataset Information
• Team Members
• Contribution Guidelines
• Acknowledgements
• License
• Contact

---

Overview

SmartMap is an AI-driven navigation and taxi management system designed to enhance taxi services in Dubai. Developed during the Alibaba Cloud and RTA Hackathon, SmartMap leverages machine learning algorithms to identify accident hotspots and high-demand areas, thereby improving safety and efficiency in taxi operations.

Our team— Homam Mourad , Mohammad Thabet , Mohamad Hamadeh , and Adeeb Mohammed

— under the supervision of Dr. Said Elnaffar, collaborated to create this innovative solution for smarter and safer taxi navigation in Dubai.

Demo Video

DEMO.mp4

Problems We Are Solving

1. Lack of Awareness of Accident Hotspots for Drivers: Many taxi drivers are unaware of accident-prone areas, increasing the likelihood of accidents.

2. Long Wait Times and Taxi Overcrowding in Certain Zones: Inefficient dispatching and static taxi stands lead to delays in customer pick-up times and overcrowded areas with too many taxis.

Features

• Accident Hotspot Identification: Utilizes KMeans clustering to detect accident-prone areas, enabling proactive safety measures.
• Dynamic Taxi Dispatching: Offers real-time insights into taxi stand locations and high-demand areas to optimize taxi availability and reduce idle time.
• AI-Driven Interactive Map: Provides taxi drivers with an interactive map that leverages real-time data and AI-driven insights for efficient navigation.
• Customizable Map Filters: Allows drivers to filter map markers based on their preferences (e.g., accident hotspots, busy points, taxi stands).
• Real-Time Notifications: Alerts drivers when they are near accident hotspots or high-demand areas.
• Driver Focus Monitoring: Future integration with camera systems will track driver distractions and improve safety.

Value Proposition

1. Reduction in Taxi Accidents

By alerting drivers to accident hotspots, SmartMap helps prevent many accidents. This improves driver and passenger safety and reduces potential losses for taxi companies.

2. Decrease in Customer Pick-Up Times

SmartMap ensures that a taxi can reach a customer in 2-5 minutes in high-demand zones, significantly increasing customer satisfaction. By optimizing taxi stand locations and utilizing real-time demand data, drivers are dispatched efficiently, minimizing wait times.

3. Increased Efficiency

By clustering demand areas and taxi stand usage patterns, the system dynamically adjusts stand locations and optimizes taxi routes, reducing idle time for drivers and improving service quality.

Technologies Used

• Frontend:

  • React.js: For building a responsive and dynamic user interface.
  • Tailwind CSS: For styling and designing the UI components.
  • JavaScript (ES6+): Core programming language for frontend logic.
  • Axios: For handling API requests and integration.

• Backend:

  • FastAPI: High-performance web framework for building RESTful APIs with Python.
  • Uvicorn: ASGI server for running FastAPI applications.

• Machine Learning:

  • Python Libraries: Including NumPy, Pandas, and Scikit-learn for data processing and machine learning.
  • KMeans Clustering: Algorithm used for identifying patterns in accident hotspots and high-demand areas.

• Infrastructure:

  • Nginx: Web server for serving the frontend application.
  • Alibaba Cloud Services: Hosting and deployment of the application.

Hackathon Context

This project was developed during the Alibaba Cloud and RTA Hackathon in collaboration with Dubai's Roads and Transport Authority (RTA). SmartMap addresses critical challenges in taxi services, aiming to reduce accidents, enhance taxi dispatching efficiency, and maximize taxi occupancy rates in Dubai.

Future Enhancements

• Camera Integration: Integrating with camera systems to track driver distractions.
• Real-Time Data Collection: Continuously collecting real-time data to improve the AI model.
• Mobile Application: Developing a mobile app version for taxi drivers for easier access on the go.
• Multi-Language Support: Adding support for multiple languages to cater to a diverse driver population.
• Integration with RTA Systems: Direct integration with RTA systems for seamless data exchange and enhanced functionality.

Installation

Prerequisites

Ensure you have the following installed on your system:

• Node.js: v12.x or higher
• npm: v6.x or higher
• Python: v3.6 or higher
• pip: Python package installer
• Uvicorn: ASGI server
• FastAPI: Python backend framework
• Nginx: Web server (for deployment)

Backend Setup

1. Clone the Repository:

   git clone https://github.com/h0m4m/alibaba-rta-hackathon.git
   cd alibaba-rta-hackathon/backend

2. Create a Virtual Environment (Optional but recommended):

   python3 -m venv venv
   source venv/bin/activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Run the Backend Server:

   uvicorn main:app --host 0.0.0.0 --port 8000

Frontend Setup

1. Navigate to the Frontend Directory:

   cd ../frontend/alibabarta-frontend

2. Install Dependencies:

   npm install

3. Update the DashboardPage Component:

   Ensure you have the latest code from the repository, which includes new features such as customizable map filters and real-time notifications.

4. Build the Frontend Application:

   npm run build

5. Deploy the Frontend with Nginx:

   • Copy Build Files to Nginx Directory:

     sudo cp -r build/* /var/www/html/

   • Restart Nginx:

     sudo systemctl restart nginx

Running the Application

• Backend API: Accessible at http://<server-ip>:8000
• Frontend Application: Accessible at http://smartmap.cc or http://<your-domain>

Usage

1. Access the Application: Open your web browser and navigate to http://smartmap.cc or your domain.

2. Login or Sign Up: Use the authentication endpoints or the frontend UI to create an account or log in.

3. Navigate the Dashboard: After logging in, you'll be directed to the dashboard where you can:

   • View real-time notifications about nearby accident hotspots and high-demand areas.
   • Customize map filters to display or hide accident hotspots, busy points, and taxi stands.
   • Use the interactive map to plan safer and more efficient routes.

4. Filter Map Markers:

   • Click on the Filter button to open the filter modal.
   • Select or deselect the markers you wish to display on the map.
   • Apply the filters to update the map in real-time.

5. Navigate to High-Demand Areas:

   • If a high-demand area is nearby, you'll receive a notification.
   • Click on the Go button to navigate to the closest high-demand point.

Note: Screenshots or a user guide can be added here to help users navigate the application more effectively.

API Endpoints

Authentication

• POST /login: Authenticate a user.

  Request Body:

  {
    "username": "user1",
    "password": "password1"
  }

• POST /signup: Register a new user.

  Request Body:

  {
    "username": "newuser",
    "password": "newpassword",
    "email": "user@example.com"
  }

Data Retrieval

• GET /accident-hotspots: Retrieve accident hotspot data.
• GET /high-demand-areas: Retrieve areas with high taxi demand.
• GET /taxi-stands: Retrieve taxi stand locations.
• GET /traffic-incidents: Retrieve recent traffic incidents.

Example API Request

curl -X POST http://<server-ip>:8000/login \
-H "Content-Type: application/json" \
-d '{"username": "user1", "password": "password1"}'

Dataset Information

The following datasets were used in this project:

• Accident Hotspots: accidents_hotspots.csv
• Anonymized Taxi Data: anonymized-taxi-data.csv
• High-Demand Areas: high_demand_areas_reduced.csv
• Taxi Stand Locations: Taxi_Stand_Locations.csv
• Traffic Incidents: Traffic_Incidents.csv

Note: Due to privacy and licensing restrictions, the datasets are not included in this repository.

Team Members

• Homam Mourad
• Mohammad Thabet
• Mohamad Hamadeh
• Adeeb Mohammed

Supervised by: Dr. Said Elnaffar

Contribution Guidelines

We welcome contributions to improve SmartMap. To contribute:

1. Fork the Repository: Click the "Fork" button at the top right of the repository page.

2. Clone Your Fork:

   git clone https://github.com/your-username/alibaba-rta-hackathon.git

3. Create a New Branch:

   git checkout -b feature/your-feature-name

4. Make Your Changes: Implement your feature or bug fix.

5. Commit Your Changes:

   git commit -am "Add new feature"

6. Push to Your Fork:

   git push origin feature/your-feature-name

7. Submit a Pull Request: Go to the original repository and create a pull request from your fork.

Acknowledgements

We extend our gratitude to:

• Alibaba Cloud and Dubai RTA for hosting the hackathon and providing us with this opportunity.
• Dr. Said Elnaffar for his guidance and supervision.
• All team members for their dedication and hard work.

License

This project is licensed under the MIT License.

---

Note: This project was developed as a prototype during a hackathon and may require additional development for production use.

Contact

For any inquiries or support, please contact us at:

• GitHub Issues: Create an Issue