Implementation of Automated Tolls with License Plate Recognition Using YOLO

As cities continue to experience rapid urbanization and growing population densities, the demand for efficient and secure parking management solutions has surged. This paper focuses on developing an advanced automated parking system designed to address the complexities of urban transportation. The system leverages cutting-edge technologies to optimize parking operations in high-demand locations, such as shopping centers and metro stations. Specifically, it adapts the YOLO model for real-time vehicle detection and incorporates an EasyOCR model for precise license plate recognition. By automating toll and parking fee collection, the system enhances efficiency, lowering the traffic congestion usually connected to conventional parking systems and the requirement for manual supervision. Additionally, security measures are integrated to detect and prevent the use of fraudulent license plates, thereby boosting overall safety. Users will also benefit from real-time notifications that provide updates on parking space availability, streamlining their parking experience. This paper also aligns with sustainability goals by minimizing vehicle emissions caused by prolonged searches for parking spaces and reducing idle times. It aims to optimize operational workflows, ultimately improving urban mobility. Implementing this automated parking management system marks a significant step toward realizing the broader vision of smart cities, enhancing the quality of life in urban environments.