CUSTECH-JIMSS

Abstract:
The deteriorating security situation in Nigeria, particularly in Niger State, has become a major concern for both national and international communities. They often move in large groups using motorcycles and vehicles to transport weapons and abducted victims. Their activities have caused a lot of harm to both their victims and the economy of Niger State, specifically Minna, and the country's image at large. Many measures have been implemented to manage insecurity in Minna, but none have yielded the required results, as most measures were passive. Hence, the development of an active system like the AVNPR system for security management in Minna, Niger State. The design utilizes hardware components such as a Raspberry Pi board, a Pi camera module, a microSD card, and a network interface for its design. While the software elements utilized for the design include Pi Imager, Python 3, and OpenCV, among others. YOLOv11 was used to detect the number plate, while Tesseract OCR was used to extract the alphanumeric write-ups on the number plate region. The results show that the developed system achieved over 90% detection accuracy. In conclusion, the ANPR system developed is effective in detecting vehicle and alphanumeric information on the number plate, assisting law enforcement agencies in monitoring activities of unregistered vehicles within Minna.

Abstract:
The deteriorating security situation in Nigeria, particularly in Niger State, has become a major concern for both national and international communities. They often move in large groups using motorcycles and vehicles to transport weapons and abducted victims. Their activities have caused a lot of harm to both their victims and the economy of Niger State, specifically Minna, and the country's image at large. Many measures have been implemented to manage insecurity in Minna, but none have yielded the required results, as most measures were passive. Hence, the development of an active system like the AVNPR system for security management in Minna, Niger State. The design utilizes hardware components such as a Raspberry Pi board, a Pi camera module, a microSD card, and a network interface for its design. While the software elements utilized for the design include Pi Imager, Python 3, and OpenCV, among others. YOLOv11 was used to detect the number plate, while Tesseract OCR was used to extract the alphanumeric write-ups on the number plate region. The results show that the developed system achieved over 90% detection accuracy. In conclusion, the ANPR system developed is effective in detecting vehicle and alphanumeric information on the number plate, assisting law enforcement agencies in monitoring activities of unregistered vehicles within Minna.