Kathmandu , Nepal — Universal Engineering and Science College (UESC) proudly announces the publication of a research article titled “Nepali License Plate Recognition Using YOLOv8 and CNN on Raspberry Pi for Automated Parking Access Control.”

The research was conducted by Er. Hemant Joshi, Head of the Department of Computer Engineering; Er. Saroj Gautam, Lecturer and 3rd and 4th Year Coordinator; and 2021 Batch Computer Engineering students Janak Bikram Rana Magar, Khushbu Kumari Chaudhary, Diyamand Bohara, and Sonam Babu Bishwakarma.

The study focuses on developing an Artificial Intelligence (AI)-powered Automatic Number Plate Recognition (ANPR) system to automate vehicle identification and parking access control. By integrating YOLOv8 for license plate detection, Convolutional Neural Networks (CNN) for character recognition, and Raspberry Pi for edge computing, the system aims to provide an efficient and practical solution for automated gate control.

The research demonstrates promising results in detecting Nepali vehicle license plates and recognizing their characters. Its implementation on Raspberry Pi also highlights the potential for deploying AI-based solutions in resource-constrained environments, making the technology relevant to practical parking management applications.

This achievement reflects UESC’s commitment to promoting research, innovation, and practical applications of emerging technologies. The work also highlights the growing role of Artificial Intelligence, Computer Vision, and Edge Computing in addressing real-world transportation and parking management challenges in Nepal.

UESC extends its heartfelt congratulations to all the authors on this remarkable research achievement and wishes them continued success in research, innovation, and technological advancement.