This research focuses on real-time license plate detection, a critical feature in electronic systems that rapidly identify and remove identification numbers from vehicle registrations in dynamic global environments. The study leverages the integration of region-based convolutional neural networks (RCNN) and advanced RCNN algorithms to create a powerful and accessible system. The methods optimize algorithm performance and deploy the system in a cloud-based environment to enhance accessibility and scalability. Through careful design and optimization, the proposed system achieves consistent results in license recognition, as evidenced by well-accounted performance metrics including precision, recall, and computational efficiency. The results demonstrate the system's efficiency and usability in real installations, promising to revolutionize automatic vehicle identification. The integration of AI and ML technology into real-time license plate recognition is expected to bring about changes in traffic management, safety assessments, and smart city plans. Interdisciplinary collaboration and continuous innovation are crucial for shaping a sustainable and balanced future for intelligent transportation systems.This research focuses on real-time license plate detection, a critical feature in electronic systems that rapidly identify and remove identification numbers from vehicle registrations in dynamic global environments. The study leverages the integration of region-based convolutional neural networks (RCNN) and advanced RCNN algorithms to create a powerful and accessible system. The methods optimize algorithm performance and deploy the system in a cloud-based environment to enhance accessibility and scalability. Through careful design and optimization, the proposed system achieves consistent results in license recognition, as evidenced by well-accounted performance metrics including precision, recall, and computational efficiency. The results demonstrate the system's efficiency and usability in real installations, promising to revolutionize automatic vehicle identification. The integration of AI and ML technology into real-time license plate recognition is expected to bring about changes in traffic management, safety assessments, and smart city plans. Interdisciplinary collaboration and continuous innovation are crucial for shaping a sustainable and balanced future for intelligent transportation systems.