Intelligent Parking Management System for Smart Cities Using YOLOv8-Based Computer Vision

Abstract

The advent of smart cities marks  a significant leap towards creating urban environments that are more efficient, sustainable, and livable. A pivotal aspect in the evolution of smart cities is the integration of Artificial Intelligence (AI) with computer vision technologies. This research outlines the role of AI-driven computer vision in advancing the functionalities and efficiencies of smart cities. Smart cities use a multitude of data sources and technologies to optimize city management and improve the quality of life for their inhabitants. AI and computer vision play crucial roles in this ecosystem by enabling real-time data processing, analysis, and decision-making. These technologies facilitate numerous applications, including traffic management, public safety, environmental monitoring, and urban planning. One major challenge in modern cities is the search for unoccupied parking spaces. The increase in the number of vehicles, combined with limited parking spaces and low-speed parking searches, worsened traffic congestion, creating a time-consuming and polluted environment. The Intelligent Parking Management System for Smart Cities project aims to address the growing need for efficient parking solutions in urban areas. Traditional parking systems are plagued by inefficiencies, such as a lack of real-time information, difficulty in finding available parking spaces, and challenges in detecting illegal parking. In this proposal, we outline a comprehensive plan to create an intelligent parking management system using computer vision and  YOLOv8, which will significantly enhance parking management in smart cities. The system  successfully detects and displays  Occupied and Available parking lots, as well as indicated right-parked and wrong-parked vehicles in real-time using a stable camera in the parking lot. We have employed a combination of cameras, image processing techniques, and real-time data analysis.

Keywords: Intelligent Parking, YOLOv8, Machine Learning, computer vision