Impact of the Development of a License Plate Recognition Software Prototype on the Efficiency of Vehicular Access Control at the Pocohuanca Community Mine, Aymaraes, 2024
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Abstract
This study evaluates the impact of developing a software prototype with automatic vehicle license plate recognition on the efficiency of access control at the mine of the Pocohuanca community, Aymaraes. The system was designed to operate under real, uncontrolled conditions, using a fixed camera, a YOLOv8n-based detection model, and an embedded processing platform running on a Raspberry Pi 5. During the training stage, the model achieved high precision, recall, and mAP@0.5 values, demonstrating stable learning under controlled conditions. Subsequently, the system was evaluated in real operation through real-time video streaming, facing challenges such as lighting variations, dust presence, and different vehicle speeds. The results showed that while license plate detection remained stable, optical character recognition exhibited limitations, leading to the incorporation of a human-assisted validation mechanism. In addition, a temporal filtering process was implemented to avoid event overestimation. Overall, the prototype proved to be a viable solution for continuous vehicle event registration, facilitating access management, temporal filtering, and subsequent analysis of access information in a real operational environment.
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