Published Paper Details:

: In present world where there is an increasing number of vehicles, it has become more apparent that manual record-keeping is insufficient to manage the vast influx of vehicles. Having a continuous human presence to record license plate numbers is not only labour-intensive but also challenging. Additionally, there are concerns about the legibility of manually stored data. Instances of theft within residential societies are often linked to insufficient authentication procedures during exit, especially during nighttime hours. Authorization for exit is granted only if the information associated with the vehicle and the individual aligns with the database records. To enhance authentication, QR codes are employed. During the time of entry, the number plate recognition serves to be an exceptional solution. The user enters without any obstruction if found to be a resident, and if not, registers himself as one and moves ahead for his own business. At the time of exit, a protected QR code scanner is accomplished by the number plate recognition. This QR code scanner works in a protected manner where the individual consents to their identity. It will be used to match the encrypted key using the designated software or application and when found to be illicit, is denied the exit from the premises. Hence, a protected QR code scanner prioritizes user safety by inspecting content and employing encrypted measures to avoid risks and misleads that may occur. The combination of Python for development, Yolo V8 for real-time object detection, Easy OCR for precise character recognition, and a protected QR Code scanner for authentication reasons, propel this system to an unprecedented level of performance and reliability. This system has the potential to revolutionize security and management at various entry points, ensuring smoother operations and heightened security measures at all times.