Virtual Toll Booth Based on Number Plate Recognition System Using Yolo V8 and Easy OCR

The transportation sector has undergone a transformation thanks to the convergence of visual computing and optical character recognition, also known as OCR, technologies, which have provided new approaches for effective toll collection systems. Using a unique "Virtual Toll Booth" constructed around an automobile plate identification system that uses the YOLO V8 engine (You Only Look Once Version 8) over object identification and Easy OCR that character recognition, we show in this paper a state-of-the-art method for collecting tolls. This automated and seamless toll collection system reduces traffic congestion and enhances overall traffic flow by doing away with manually operated tolling booths and human operators. The creation and implementation of a thorough system architecture that incorporates YOLO V8 for accurate automobile and number card detection is the main goal of our research. To reliably extract alphanumeric information from the accurately recognised number plates, the system also uses Easy OCR. We establish the system's excellent accuracy, resilience, and instantaneous computation capabilities through thorough testing and assessment. We also address user data security issues by implementing security measures, highlighting the significance of data security in contemporary transportation systems. The findings of this study demonstrate the potential for increased effectiveness and decreased operating expenses in the transportation industry. In addition to streamlining toll collection, referred to as Virtual Toll Booth systems lays the groundwork for upcoming improvements and advances in autonomous traffic management. The combination of YOLO V8 with Easy OCR creates new opportunities for intelligent systems that could revolutionise the way we handle transport as it changes.