

Automatic Car Parking System Using Machine Learning
Abstract
In this project, we develop an Automatic Car Parking System utilizing YOLOv8, Jetson Nano, IR sensors, and a stepper motor to enable efficient and intelligent vehicle parking. The system employs YOLOv8, a deep learning-based object detection model, to recognize and track vehicles in real time. The Jetson Nano serves as the processing unit, handling image recognition and decision-making tasks. IR sensors detect the presence of a vehicle and confirm parking slot availability, while a stepper motor controls the gate mechanism for automated entry and exit. The integration of these components creates a cost-effective, smart parking solution that minimizes human intervention, enhances space utilization, and reduces congestion in parking facilities. The proposed system aims to improve the efficiency of urban parking management through automation and AI-driven decision-making.
References
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