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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Real-Time Parking Space Management System Based on a Low-Power Embedded Platform.

Kapyol Kim1, Jongwon Lee1, Incheol Jeong1

  • 1Department of Computer Engineering, Gachon University, Seongnam 1342, Republic of Korea.

Sensors (Basel, Switzerland)
|November 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an edge-based smart parking system for real-time outdoor occupancy detection. The low-power system uses AI for accurate vehicle recognition and management, reducing costs and enabling dynamic pricing.

Keywords:
AIRTSPYOLOlow-power embeddedmachine learningobject detectionreal-time video processingsmart parking systemvideo analytics

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Area of Science:

  • Computer Vision
  • Embedded Systems
  • Artificial Intelligence

Background:

  • Traditional parking management systems often rely on costly sensors and extensive maintenance.
  • Real-time occupancy data is crucial for efficient parking management and dynamic pricing strategies.

Purpose of the Study:

  • To develop an edge-centric outdoor parking management system for real-time, slot-level occupancy detection.
  • To create a cost-efficient and scalable smart parking infrastructure using low-power embedded devices.

Main Methods:

  • Constructed a dataset of 13,691 images captured under varied conditions.
  • Trained a YOLOv8-based detector for vehicle recognition.
  • Implemented a temporal occupancy decision module with smoothing and occlusion-robust rules for enhanced stability.

Main Results:

  • Achieved end-to-end latency p50/p95 of 195 ms and 400 ms on an AI-BOX edge platform.
  • Sustained 10 FPS at 3.35 W (2.99 FPS/W) during 24-hour operation.
  • Demonstrated improved stability in adverse weather and nighttime conditions.

Conclusions:

  • The proposed edge-based system offers a flexible, scalable, and cost-efficient solution for smart parking.
  • Reduces upfront deployment costs and recurring maintenance compared to conventional architectures.
  • Enables automated fee calculation through integration with dynamic pricing mechanisms.