Developing an Advanced Automated Parking System using Computer Vision

This Omdena Local Chapter Challenge runs for 8 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Fez, Morocco Chapter.

The problem

Developing an advanced automated parking system for a large shopping mall or office complex that can efficiently manage parking spaces and handle the entry and exit of vehicles without the need for human intervention. The goal is to create a system that supports multiple languages, including Arabic, English, and French, for license plate detection. The system uses computer vision technology with YOLOv8-based license plate detection and an OCR module for character recognition.

How it Works:

1. Entrance Monitoring:

As a vehicle approaches the entrance, a camera equipped with YOLOv8-based license plate detection is installed. The camera continuously captures live video footage and processes it in real time using the YOLOv8 model. When the model detects a car within the frame, it focuses on the area where the license plate is expected to be located.

2. Multilingual License Plate Detection:

The YOLOv8 model is trained on a diverse dataset containing license plates from different regions and languages, including Arabic, English, and French. This enables the model to recognize and locate license plates accurately in various languages and fonts.

3. Character Recognition for Multilingual Support:

Once the license plate is detected, the system extracts the characters from the plate. The character recognition module (OCR) is trained on a diverse dataset encompassing Arabic, Latin (English), and French characters to accurately recognize and convert the license plate numbers to text.

4. Language Detection and Translation:

To enhance user experience, the system incorporates language detection to identify the language of the license plate automatically. If the detected language is different from the user interface language, the system can provide real-time translations of the license plate numbers and parking-related information into the user’s preferred language.

5. License Plate Validation and Entry:

The recognized license plate number is checked against the database of registered vehicles, which can accommodate multilingual information. If the plate number matches with an authorized vehicle, the parking barrier automatically opens to allow the vehicle to enter. If the plate number is not registered or matches a blacklisted vehicle, the barrier remains closed, and a security alert is triggered.

6. Parking Space Management:

As the vehicle enters the parking lot, the system updates the available parking spaces count based on the vehicle’s size and allocates an appropriate parking spot for it. Real-time records of available parking spaces are maintained in the multilingual database.

7. Exit Monitoring and Payment:

At the exit, another camera with YOLOv8-based license plate detection verifies the vehicle’s license plate as it approaches the exit. The system checks the recognized plate number against the database to verify if the vehicle has paid for parking or has overstayed its allotted time. If necessary, the system can integrate with payment gateways to automatically charge the parking fee.

The goals

• Multilingual License Plate Detection: The primary goal of the project is to develop a robust automated parking system capable of accurately detecting license plates in multiple languages, including Arabic, French, and English. The system should be able to handle variations in languages, fonts, and designs commonly found on license plates in Morocco.
• Real-Time Processing: The project aims to optimize license plate detection and character recognition algorithms to achieve real-time processing of live video feeds. The system should efficiently process incoming vehicles, verify their license plate information, and make prompt decisions for entry and exit authorization.
• User-Friendly Interface: The project seeks to design an intuitive and multilingual user interface that caters to the diverse linguistic backgrounds of the users. The interface should provide real-time translations and be easy to navigate, ensuring a convenient and inclusive parking experience for all visitors.
• Parking Space Management: The automated parking system should effectively manage parking spaces by accurately allocating spots based on vehicle size and availability. The project aims to optimize parking space utilization and provide real-time data on available spaces.
• Enhanced Security: The project emphasizes enhancing security by accurately identifying authorized vehicles and detecting unauthorized or suspicious entries. By implementing effective license plate detection, the system aims to contribute to a safer parking environment.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work