Paper Title
Smart Parking System Using Yolo

Abstract
The paper presents a system that will provide an accurate and reliable way of locating empty parking slots. A growing interest in creating smart-parking systems has been seen recently in the automotive sector. Accurately detecting and localizing the parking-slots indicated by regular line segments is a crucial and unresolved problem for such systems. The vision-based parking-slot recognition is more challenging than it appears due the variety of ground materials, variations in ambient light, and unexpected shadows generated by neighboring trees, etc. Using computer vision and machine learning approaches, the work seeks to overcome these challenges. The proposed system will be using YOLO object detection program. It uses a single neural network with fewer convolution layers and filters in those layers to predict a bounding box and a confidence score. The system will find empty parking slots and will give a text-based and a speech-based alert Keywords - Parking Detection, Yolov5, CNN

Author - Nilesh Sonawane, Aishwarya Honap, Madhura Wani, Sanika Tambekar, Sharvin Pharande

Published : Volume-10,Issue-6  ( Jun, 2023 )

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