Real-time number plate detection using AI and ML

Patakamudi Swathi, Dara Sai Tejaswi, Mohammad Amanulla Khan, Miriyala Saishree, Venu Babu Rachapudi and Dinesh Kumar Anguraj

Gamification and Augmented Reality, 2024, vol. 2, 37

Abstract: The abstract presents a research study focusing on real-time license plate verification, a key feature of electronic systems that operate by rapidly identifying and removing identification numbers from vehicle registration in a dynamic global environment. The research leverages the combination of artificial intelligence (AI) and machine learning (ML) techniques, specifically the integration of region-based convolutional neural networks (RCNN) and advanced RCNN algorithms, to create a powerful and readily available system. In terms of methods, this research optimizes algorithm performance and deploys the system in a cloud-based environment to improve accessibility and scalability. Through careful design and optimization, the proposed system has achieved a consistent result in license recognition, as evident from the well-accounted evaluation of performance, including precision, recall, and computational efficiency. The results demonstrate the efficiency and usability of this system in a real installation and promise to revolutionize automatic vehicle identification. Finally, the integration of artificial intelligence and machine learning technology into real-time license plate recognition signifies changes in traffic management, assessment safety and smart city plans. Therefore, interdisciplinary collaboration and continuous innovation are crucial to shaping a sustainable and balanced future for intelligent transportation systems.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:gammif:v:2:y:2024:i::p:37:id:37

DOI: 10.56294/gr202437

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