Result Details

Using Computer Vision and Machine Learning for Efficient Parking Management: A Case Study

FRÝZA, T.; KUŽELA, M.; ZELENÝ, O. Using Computer Vision and Machine Learning for Efficient Parking Management: A Case Study. In Proceedings of 13th Mediterranean Conference on Embedded Computing (MECO 2024). Institute of Electrical and Electronics Engineers Inc., 2024. 4 p. ISBN: 979-8-3503-8756-8.
Type
conference paper
Language
English
Authors
Frýza Tomáš, doc. Ing., Ph.D., UREL (FEEC)
Kužela Miloslav, Bc., FEEC (FEEC)
Zelený Ondřej, Ing., UREL (FEEC)
Abstract

This paper addresses the challenges associated with urban mobility and introduces a~low-complexity system for detecting parking lot occupancy using machine learning and computer vision techniques. Through a~field experiment at a~Czech university, images of parking areas were captured to create a~dataset titled T10Lot, and classified to get parking spot occupancy using Raspberry Pi computer. Results indicate satisfactory accuracy despite challenges such as varying lighting conditions and weather.

Keywords

Machine learning, smart parking, edge device, classifier, IoT

URL
Published
2024
Pages
4
Proceedings
Proceedings of 13th Mediterranean Conference on Embedded Computing (MECO 2024)
Conference
2024 13th Mediterranean Conference on Embedded Computing (MECO)
ISBN
979-8-3503-8756-8
Publisher
Institute of Electrical and Electronics Engineers Inc.
DOI
10.1109/MECO62516.2024.10577808
UT WoS
001268606200023
EID Scopus
2-s2.0-85199515051
BibTeX 
@inproceedings{BUT189015,
  author="Tomáš {Frýza} and Miloslav {Kužela} and Ondřej {Zelený}",
  title="Using Computer Vision and Machine Learning for Efficient Parking Management: A Case Study",
  booktitle="Proceedings of 13th Mediterranean Conference on Embedded Computing (MECO 2024)",
  year="2024",
  pages="4",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  doi="10.1109/MECO62516.2024.10577808",
  isbn="979-8-3503-8756-8",
  url="https://ieeexplore.ieee.org/document/10577808"
}
Departments
Department of Radio Electronics (UREL)
Back to top