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Title	Real-Time Parking Lot Monitoring For Smart Cities: A Cnn-Based Approach Using Yolo And Rtsp-Compatible Cameras
ID_Doc	44417
Authors	Kurinaah E.; Hall M.; Viera N.; Smith K.; Yu Y.; Shen X.
Year	2025
Published	Proceedings of SPIE - The International Society for Optical Engineering, 13465
DOI	http://dx.doi.org/10.1117/12.3058674
Abstract	This undergraduate research project is focused on developing a real-time parking lot monitoring system leveraging the YOLO (You Only Look Once) object detection framework, which is designed for efficient sensing and imaging in dynamic environments. The proposed system integrates RTSP-enabled cameras for continuous video streaming, capturing high-resolution frames processed by a Raspberry Pi 5. YOLO's convolutional neural network architecture enables real-time vehicle detection and classification with high accuracy and low latency, making it well-suited for edge computing applications. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
Author Keywords	Computer Vision; Convolutional Neural Network; Edge Computing; Image Processing; Object Detection; YOLOv5

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