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Modern urbanization and the increasing number of vehicles are making urban mobility and parking management increasingly important. Rapid urbanization has increased demand for parking spaces, complicating their management. The installation of smart parking systems, which optimize urban mobility, is a key component of smart cities. The implementation of these technologies is important for increasing parking spaces and reducing harmful emissions. The aim of this research is to present a smart parking approach based on Arduino access control technologies and a deep learning model for monitoring parking occupancy, called MobileNet SSD, providing real-time information on parking availability and occupancy. The presented system will be useful for drivers to find free parking spaces more easily, which will lead to time savings, less congestion and fuel consumption. Through these technologies, smart parking systems increase the accuracy of on-site availability predictions. Future developments may integrate new artificial intelligence models and IoT connectivity to improve decision-making capabilities.

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Integrating Artificial Intelligence and Machine Learning Techniques in Intelligent Parking Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Fatima Sapundzhi,
  • Umran Gunduz,
  • Salih Sapundzhi,
  • Metodi Popstoilov,
  • Slavi Georgiev,
  • Venelin Todorov

摘要

Modern urbanization and the increasing number of vehicles are making urban mobility and parking management increasingly important. Rapid urbanization has increased demand for parking spaces, complicating their management. The installation of smart parking systems, which optimize urban mobility, is a key component of smart cities. The implementation of these technologies is important for increasing parking spaces and reducing harmful emissions. The aim of this research is to present a smart parking approach based on Arduino access control technologies and a deep learning model for monitoring parking occupancy, called MobileNet SSD, providing real-time information on parking availability and occupancy. The presented system will be useful for drivers to find free parking spaces more easily, which will lead to time savings, less congestion and fuel consumption. Through these technologies, smart parking systems increase the accuracy of on-site availability predictions. Future developments may integrate new artificial intelligence models and IoT connectivity to improve decision-making capabilities.