Smart City Gnosys

Smart city article details

Title	The Performance Of Vacant Parking Spaces Detection Using Yolov5
ID_Doc	56210
Authors	Nugroho A.; Fathurrahman M.; Wijaya Z.V.
Year	2024
Published	2024 International Conference on Informatics Electrical and Electronics, ICIEE 2024 - Proceedings
DOI	http://dx.doi.org/10.1109/ICIEE63403.2024.10920318
Abstract	Parking challenges are increasingly significant in urban areas, particularly in nations with high numbers of private vehicles, such as Indonesia. Conventional parking systems often struggle to effectively identify available spaces, leading to wasted time, congestion, and environmental issues. This study addresses these challenges by implementing YOLOv5, a deep learning-based object detection model, to improve the efficiency and accuracy of vacant parking space detection. The proposed system processes video input from parking areas to detect vehicle presence and determine the occupancy status of designated parking spaces. A dataset of 3,843 images was compiled for model training and testing, encompassing diverse conditions to enhance detection robustness. The model's performance was tested on two video samples recorded under different environmental conditions, achieving a high accuracy rate of 96.4% in detecting vacant and occupied spaces. These results underscore the potential of YOLOv5 for optimizing parking management, reducing the limitations of traditional systems, and providing a scalable solution for smart city infrastructure. © 2024 IEEE.
Author Keywords	Object Detection; Parking Management; Smart Parking; YOLOv5

Similar Articles

Id	Similarity	Authors	Title	Published
22414	0.942	Ramesh M.; Sriram N.; Suganth K.M.; Shree Tharun Krushna K.S.; Anitha Rani A.; Kodeeswari K.	Efficient Smart Parking Space Identification And Classification System Using Yolov8 Network Model	3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025 (2025)
41322	0.931	Asy'Ari M.F.; Fatichah C.; Suciati N.	Parking Space Detection In Different Weather Conditions Based On Yolov5 Method	8th International Conference on Software Engineering and Computer Systems, ICSECS 2023 (2023)
39996	0.912	Morell J.Á.; Luque G.; Alba E.	On-Street Parking Space Localization With Deep Learning Using Low-Quality Images From Public Cameras	Internet of Things (The Netherlands), 32 (2025)
51304	0.911	Sayson J.L.; Valdehueza A.; Maghanoy M.J.; Flores P.R.; Haim S.; Alagon F.J.; Visitacion S.; Villame C.M.; Clar S.; Zamayla A.; Aleluya E.R.	Smart Parking: Detecting Vacant Spots From An Angled Viewpoint	Proceedings - 2024 IEEE Conference on Dependable, Autonomic and Secure Computing, DASC 2024 (2024)
17836	0.904	Sathishkumar P.; Boopalan R.; Shree S.K.; Dhanish R.	Deep Learning Based Efficient Parking Management System Framework	2024 International Conference on Knowledge Engineering and Communication Systems, ICKECS 2024 (2024)
51884	0.901	Santosh N.; Kumar M.S.	Smartpark Visionaire: Ai-Driven Advanced Parking Slot Detection	Proceedings of 8th International Conference on Inventive Computation Technologies, ICICT 2025 (2025)
5405	0.896	Maharshi R.T.; Nagajyothi D.; Thrishul P.; Reethika P.	A System For Detecting Automated Parking Slots Using Deep Learning	2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023 (2023)
22358	0.894	Safran M.; Alajmi A.; Alfarhood S.	Efficient Multistage License Plate Detection And Recognition Using Yolov8 And Cnn For Smart Parking Systems	Journal of Sensors, 2024 (2024)
41321	0.888	Asy’ari M.F.; Fatichah C.; Suciati N.	Parking Space Availability Detections From Two Overlapping Cameras Using Yolov5 And Image Stitching Methods	International Journal of Intelligent Engineering and Systems, 16, 4 (2023)
56528	0.886	Rasheed F.; Saleem Y.; Yau K.-L.A.; Chong Y.-W.; Keoh S.L.	The Role Of Deep Learning In Parking Space Identification And Prediction Systems	Computers, Materials and Continua, 75, 1 (2023)