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Sustainable IoT-Enabled Parking Management: A Multiagent Simulation Framework for Smart Urban Mobility

Author

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  • Ibrahim Mutambik

    (Department of Information Science, College of Humanities and Social Sciences, King Saud University, Riyadh P.O. Box 11451, Saudi Arabia)

Abstract

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems.

Suggested Citation

  • Ibrahim Mutambik, 2025. "Sustainable IoT-Enabled Parking Management: A Multiagent Simulation Framework for Smart Urban Mobility," Sustainability, MDPI, vol. 17(14), pages 1-24, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6382-:d:1699978
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    References listed on IDEAS

    as
    1. Ibrahim Mutambik, 2024. "Unlocking the Potential of Sustainable Smart Cities: Barriers and Strategies," Sustainability, MDPI, vol. 16(12), pages 1-16, June.
    2. Bao, Yitian & Bao, Yue & Kang, Liujiang, 2025. "Modeling the departure time choices of attendees for special events with cruising-for-parking," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 198(C).
    3. Xiao, Runhua Ivan & Jaller, Miguel, 2025. "Spatial analysis and predictive modeling framework of truck parking and idling impacts on environmental justice communities," Journal of Transport Geography, Elsevier, vol. 127(C).
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    5. Ibrahim Mutambik & Abdullah Almuqrin, 2024. "Employee Acceptance of Digital Transformation: A Study in a Smart City Context," Sustainability, MDPI, vol. 16(4), pages 1-21, February.
    6. Piotr Powroźnik & Paweł Szcześniak & Krzysztof Piotrowski, 2021. "Elastic Energy Management Algorithm Using IoT Technology for Devices with Smart Appliance Functionality for Applications in Smart-Grid," Energies, MDPI, vol. 15(1), pages 1-23, December.
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