AI-based free parking space detection system for large parking areas

  • Tuan Luong
  • , Yeongbin Shin
  • , Jooeon Park
  • , Sihoon Leeu
  • , Hyungpil Moon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents an AI-based vision system for free parking space recognition using a CCTV camera and deep learning-based object detection. The system captures video streams from a roof-mounted camera and processes them using a YOLO-based algorithm to determine parking occupancy. The detection results are transmitted to an AWS cloud server and visualized through a Progressive Web Application (PWA) for real-time monitoring. The system was deployed and tested in a large parking lot at Sungkyunkwan University, achieving over 98% accuracy in well-visible areas. The proposed system demonstrates the feasibility of low-cost, automated parking monitoring, with potential for further scalability and deployment in real-world smart parking solutions.

Original languageEnglish
Title of host publicationRCAR 2025 - IEEE International Conference on Real-Time Computing and Robotics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1072-1077
Number of pages6
ISBN (Electronic)9798331502058
DOIs
StatePublished - 2025
Event2025 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2025 - Toyama, Japan
Duration: 1 Jun 20256 Jun 2025

Publication series

NameRCAR 2025 - IEEE International Conference on Real-Time Computing and Robotics

Conference

Conference2025 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2025
Country/TerritoryJapan
CityToyama
Period1/06/256/06/25

Keywords

  • AI
  • Free parking space recognition
  • Vision-based detection
  • YOLO

Fingerprint

Dive into the research topics of 'AI-based free parking space detection system for large parking areas'. Together they form a unique fingerprint.

Cite this