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ABSTRACT
Automatic Number Plate Recognition (ANPR) technology has significantly evolved since its inception by the British Police Scientific Development Branch in 1976. This technology initially focused on reading vehicle number plates in controlled environments. Still, it has transformed into a robust tool for traffic monitoring, law enforcement, and urban planning, thanks to advancements in computing power and image processing algorithms. The literature review traces ANPR's historical development, highlighting its pivotal role in crime prevention, traffic management, and broader applications in modern cities. Despite its benefits, ANPR systems face challenges such as privacy concerns and the need for robust performance under diverse conditions. The Nigerian Vehicle Identification System (NVIS), managed by the Federal Road Safety Corps (FRSC), is evaluated for its strengths and weaknesses, emphasizing its reliability as an official government service. However, limitations such as manual input errors and lack of OCR capabilities are noted. A new system incorporating advanced features like OCR with PaddleOCR, enhanced user interface, API integration for detailed vehicle information retrieval, and robust data management is proposed to address these issues. This system aims to improve accuracy, user experience, and efficiency in vehicle verification processes. The methodology uses the Structured Systems Analysis and Design Method (SSADM) and Agile development practices to ensure continuous improvement and adaptability. The proposed enhancements are expected to lessen identified weaknesses, enhance system performance, and comply with legal and ethical data privacy and security standards.
