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Related Experiment Video

Updated: Jan 16, 2026

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Real time smart parking system based on IoT and fog computing evaluated through a practical case study.

Mohammed Alaa Ala'anzy1,2, Assyl Abilakim3, Raiymbek Zhanuzak4,5

  • 1School of Microelectronics and Data Science, Anhui University of Technology, Maanshan, 243002, China. m.alanzy@ieee.org.

Scientific Reports
|September 29, 2025
PubMed
Summary

A new smart parking system uses fog computing to efficiently manage parking spaces in urban areas. This system reduces traffic congestion and optimizes resource use, offering a sustainable solution for smart cities.

Keywords:
Cloud computingFog computingInternet of Things (IoT)Parking spotsSmart cities

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Area of Science:

  • Computer Science
  • Urban Planning
  • Environmental Science

Background:

  • Urban populations and private vehicle use are increasing, leading to traffic congestion and parking difficulties.
  • Inefficient parking search wastes time, fuel, and energy, impacting urban sustainability.
  • Smart parking systems are crucial for efficient urban transportation and sustainable city development.

Purpose of the Study:

  • To introduce a provenance-based smart parking system utilizing fog computing.
  • To enhance real-time parking space management and resource allocation in urban environments.
  • To improve urban mobility and reduce the environmental impact of transportation.

Main Methods:

  • A hierarchical fog computing architecture with four layers was designed for efficient data handling and resource utilization.
  • A provenance component was integrated to provide users with real-time parking availability insights.
  • Simulations were performed using the iFogSim2 toolkit to evaluate system performance against cloud-based approaches.

Main Results:

  • The fog-based smart parking system demonstrated superior performance over cloud-based systems in end-to-end latency, execution cost, and energy consumption.
  • The system effectively minimized network usage and optimized parking space utilization.
  • A real-world case study at SDU University Park validated the system's effectiveness, especially during peak hours.

Conclusions:

  • Fog computing offers a more efficient and responsive solution for smart parking systems compared to traditional cloud-based methods.
  • The proposed system contributes to eco-friendly urban transportation by reducing congestion and optimizing resource allocation.
  • This approach supports the development of smarter, more sustainable urban environments by addressing parking challenges effectively.