An Enhanced Car Parking Detection Using YOLOv8 Deep Learning Capabilities

This research paper introduces a novel approach for car parking slot detection using YOLOv8, an advanced object detection algorithm renowned for its state-of-the-art performance. The objective of this study is to address the increasing demand for efficient parking management in urban areas, where optimizing parking space utilization is essential to alleviate traffic congestion. The proposed model efficiently uses the power of YOLOv8's single-shot detection. It uses anchor boxes to automatically identify and classify vacant and occupied parking slots in real time. By utilizing YOLOv8's deep learning capabilities, the proposed method achieved impressive accuracy and efficiency in car parking slot detection. The simulation results showcase the system's effectiveness, providing valuable insights for urban mobility planning and management.