Smart Parking System Using Image Recognition

Abstract: The Smart Parking System with Image Recognition is a state-of-the-art technology made to solve parking management issues in cities. The method uses a deep learning model based on YOLO to reliably identify and categorise parking spots as "occupied" or "empty" from photos of parking lots. The goal of this study is to develop a productive, automated method for maximising parking space usage and cutting down on time spent looking for spots. After being trained on a bespoke dataset, the YOLO model analyses photos and annotates them with bounding boxes to identify parking spaces with high accuracy. Streamlit was used to create an intuitive user interface that allows users to input photographs for processing in real time. The program shows counts of open and occupied spaces and gives a visual representation of the data. This system integrates easily with current infrastructure and provides a scalable, affordable option for smart city efforts. Enhancing parking efficiency helps to improve urban mobility and lessen traffic congestion, demonstrating how AI-powered solutions can revolutionise common problems.