Spatio-Temporal Clustering for Optimal Real-Time Parking Availability Estimation

Errousso, Hanae; Filali, Youssef; Aghbalou, Nihad; Alaoui, El Arbi Abdellaoui; Benhadou, Siham

doi:10.1007/978-3-031-53824-7_19

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2024

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Cited by 2 publications

References 25 publications

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Real-Time Parking Availability Classification on a Large-Area Scale

Filali,

Errousso,

Aghbalou

et al. 2024

Lecture Notes in Networks and Systems

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Real-Time Parking Availability Classification on a Large-Area Scale

Filali,

Errousso,

Aghbalou

et al. 2024

Lecture Notes in Networks and Systems

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Sustainable Parking Space Management Using Machine Learning and Swarm Theory—The SPARK System

Janowski,

Hüsrevoğlu,

Renigier-Bilozor

2024

Applied Sciences

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The utilization of contemporary technology enhances the efficiency of parking resource management, contributing to more liveable and sustainable cities. In response to the growing challenges of urbanization, intelligent parking systems have emerged as a crucial solution for optimizing parking management, reducing traffic congestion, and minimizing pollution. The primary aim of this study is to present the concept of the developed web application that supports finding available parking spaces, embodied in the SPARK system (Smart Parking Assistance and Resource Knowledge). The integration of the YOLOv9 (You Only Look Once) segmentation algorithm with Artificial Bee Colony (ABC) optimization, combined with the use of crowdsourced data and deep learning for image analysis, significantly enhances the SPARK system’s operational efficiency. It enables rapid and precise detection of available parking spaces while ensuring robustness and continuous improvement. The accuracy of detecting available parking spaces in the presented system, estimated at 87.33%, is satisfactory compared to similar studies worldwide.

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Spatio-Temporal Clustering for Optimal Real-Time Parking Availability Estimation

Cited by 2 publications

References 25 publications

Real-Time Parking Availability Classification on a Large-Area Scale

Real-Time Parking Availability Classification on a Large-Area Scale

Sustainable Parking Space Management Using Machine Learning and Swarm Theory—The SPARK System

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