Spot-Wise Smart Parking: An Edge-Enabled Architecture with YOLOv11 and Digital Twin Integration

TL;DR

This paper presents an edge-enabled smart parking system using YOLOv11 and digital twin integration, achieving high accuracy and real-time spot-level monitoring with innovative spatial matching and hardware reuse.

Contribution

It introduces a spot-wise monitoring strategy with spatial tolerance, an Adaptive Bounding Box Partitioning method, and a Digital Shadow for parking visualization, enhancing existing smart parking solutions.

Findings

Achieves 98.80% accuracy in spot detection

Maintains 8-second inference time on resource-constrained devices

Introduces a scalable, hardware-reusable support server

Abstract

Smart parking systems help reduce congestion and minimize users' search time, thereby contributing to smart city adoption and enhancing urban mobility. In previous works, we presented a system developed on a university campus to monitor parking availability by estimating the number of free spaces from vehicle counts within a region of interest. Although this approach achieved good accuracy, it restricted the system's ability to provide spot-level insights and support more advanced applications. To overcome this limitation, we extend the system with a spot-wise monitoring strategy based on a distance-aware matching method with spatial tolerance, enhanced through an Adaptive Bounding Box Partitioning method for challenging spaces. The proposed approach achieves a balanced accuracy of 98.80% while maintaining an inference time of 8 seconds on a resource-constrained edge device, enhancing the capabilities of YOLOv11m, a model that has a size of 40.5 MB. In addition, two new components were introduced: (i) a Digital Shadow that visually represents parking lot entities as a base to evolve to a full Digital Twin, and (ii) an application support server based on a repurposed TV box. The latter not only enables scalable communication among cloud services, the parking totem, and a bot that provides detailed spot occupancy statistics, but also promotes hardware reuse as a step towards greater sustainability.