This project leverages the power of digital image processing to create an innovative solution for parking management. It identifies available parking spaces in real-time using live video feeds, making parking in crowded urban areas more efficient and hassle-free.
As urbanization increases, parking has become a significant issue in both developed and developing countries. The Smart Parking System aims to alleviate this by automatically detecting vacant parking spots using grayscale images captured from any video camera. This system not only improves parking efficiency but also reduces traffic congestion and air pollution.
- Reduce Parking Time: Quickly guide drivers to available parking spaces.
- Environmental Benefits: Lower CO2 emissions, noise levels, and other pollutants by reducing unnecessary driving.
- Traffic Management: Improve traffic flow in congested areas by minimizing lingering and excessive driving.
- Real-time Updates: Continuously update the availability of parking spaces in a live database.
- Digital Image Processing: Detects parking spots using Python and the OpenCV library.
- Real-Time Data: Uploads parking availability data to Firebase Realtime Database.
- User-Friendly Interface: Displays available parking spaces on a user application.
- Prototype Testing: Successfully tested using a prototype parking lot with toy cars.
- 📷 Mobile Camera Modules: Installed at entry and exit points.
- 🚗 Toy Car: Demonstrates the occupancy of parking spaces.
- 🗺️ A3 Cardboard: Used to create a prototype parking lot.
- 🎥 Tripod Camera Mount: Mounts cameras at strategic points.
- Python 3.x: Ensure Python is installed on your system.
- OpenCV: Used for image processing.
- Firebase Admin SDK: To interact with Firebase Realtime Database.
- Precision: The system was rigorously tested using video footage captured by a drone camera. It successfully detected the availability of parking spaces with high accuracy, demonstrating its potential for real-world applications.
- Cost-Effective: The Smart Parking System is more economical compared to traditional parking management systems that rely on individual sensors for each parking spot. By using digital image processing, it significantly reduces installation and maintenance costs.
- Scalability: The current system is designed for small-scale parking lots. Future work could focus on enhancing scalability to accommodate larger parking areas, including multi-story parking structures.
- Mobile App Integration: Developing a dedicated mobile application would provide users with easier access to real-time parking information, notifications about available spaces, and possibly even reservation capabilities.
- Advanced Features: There is potential to implement dynamic pricing models based on demand, as well as providing real-time analytics and predictions about parking availability. This could further enhance the efficiency and utility of the system.