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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials, Volume 37, Number 9(3) (2025)
Copyright(C) MYU K.K.
pp. 4167-4283
S&M4180 Technical paper of Special Issue
https://doi.org/10.18494/SAM5897
Published: September 30, 2025

Implementation of an AIoT-based Smart Parking System for Urban Mobility and Sustainable Infrastructure Management [PDF]

Wen-Hsien Tsai, Hsiang-Ching Chen, Kuo-Hsien Lee, and Cheng-Fu Yang

(Received August 21, 2025; Accepted September 18, 2025)

Keywords: smart parking system, IoT sensor applications, urban mobility optimization, activity-based costing (ABC), carbon emission analysis

As urban populations continue to grow, conventional parking systems increasingly fail to meet demands for space efficiency, user convenience, and sustainability. In this paper, we propose an AIoT-based smart parking system that reimagines the traditional mechanical tower through a modular Rubik’s Cube-inspired design stabilized by a three-axis motion control framework. IoT-enabled sensors including ultrasonic units for vehicle detection, infrared modules for alignment, and radio frequency identification tags for occupancy tracking ensure accurate and responsive operation. Cars are shifted horizontally and vertically via tray-level rollers and lateral tracks, enabling multi-directional slot movement while reducing vibration and energy use. Integrated cloud infrastructure supports real-time monitoring, dynamic pricing, and user navigation through mobile applications. An operational simulation estimated retrieval times across varying occupancy levels, showing reduced waiting periods with performance dependent on scale and load. A simulated deployment in a mixed-use urban area demonstrated improved space utilization, energy efficiency, and service accessibility. Net carbon emission reduction was calculated by balancing shorter idling times with the energy costs of tray shuffling. Finally, we outline the future application of activity-based costing to compare economic and environmental performances between traditional and AIoT-based systems, providing a comprehensive framework for evaluating feasibility, cost efficiency, and sustainability in smart mobility planning.

Corresponding author: Kuo-Hsien Lee and Cheng-Fu Yang


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Wen-Hsien Tsai, Hsiang-Ching Chen, Kuo-Hsien Lee, and Cheng-Fu Yang, Implementation of an AIoT-based Smart Parking System for Urban Mobility and Sustainable Infrastructure Management, Sens. Mater., Vol. 37, No. 9, 2025, p. 4167-4283.



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