An approach for building an intelligent parking support system

Thai-Nghe, Nguyen; Chi-Ngon, Nguyen

doi:10.1145/2676585.2676594

Cited by 6 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thai-Nghe and Chi-Ngon [17] proposed a solution for building an intelligent parking support system that integrates three recognition techniques: automatic recognition for motorcycle license plate, barcode recognition, and semiautomatic recognition via surveillance cameras with an accuracy of 99% for license plate area recognition, 95.88% for letter area recognition, and 98.99% for classification.…”

Section: Related Workmentioning

confidence: 99%

Efficient Multistage License Plate Detection and Recognition Using YOLOv8 and CNN for Smart Parking Systems

Safran,

Alajmi,

Alfarhood

2024

Journal of Sensors

View full text Add to dashboard Cite

Smart parking systems play a vital role in enhancing the efficiency and sustainability of smart cities. However, most existing systems depend on sensors to monitor the occupancy of parking spaces, which entail high installation and maintenance costs and limited functionality in tracking vehicle movement within the car park. To address these challenges, we propose a multistage learning-based approach that leverages existing surveillance cameras within the car park and a self-collected dataset of Saudi license plates. The approach combines YOLOv5 for license plate detection, YOLOv8 for character detection, and a new convolutional neural network architecture for improved character recognition. We show that our approach outperforms the single-stage approach, achieving an overall accuracy of 96.1% versus 83.9% of the single-stage approach. The approach is also integrated into a web-based dashboard for real-time visualization and statistical analysis of car park occupancy and vehicle movement with an acceptable time efficiency. Our work demonstrates how existing technology can be leveraged to improve the efficiency and sustainability of smart cities.

show abstract

Section: Related Workmentioning

confidence: 99%

Efficient Multistage License Plate Detection and Recognition Using YOLOv8 and CNN for Smart Parking Systems

Safran,

Alajmi,

Alfarhood

2024

Journal of Sensors

View full text Add to dashboard Cite

show abstract

“…The paper wants to go beyond just permitting smart parking by improving real-time monitoring and administration of available parking spaces, which will generate a lot of money. [15] This article [4] reviews numerous works related to the deployment of smart parking systems and analyses the types of each component that are most frequently utilised, focusing on use patterns throughout the analysis period. Each section analyses and examines current usage patterns for software, protocols, and sensors.…”

Section: International Journal Of Research In Science and Technologymentioning

confidence: 99%

Enhanced Cloud Car Parking System using ML and Advance Neural Network

Kaushik¹

2023

IJRST

View full text Add to dashboard Cite

It is a challenging challenge for the users to find a parking spot to park their vehicles because of the rapid increase in vehicle density, particularly during the busiest times of the day. Moreover, a smartphone application is available that enables users to check parking space availability and reserve a spot accordingly. By lowering fuel use and pollution in cities, smart parking can boost the economy. Using parking resources more effectively is referred to as parking management. Finding the root of the issue is the first step in effective parking management. In light of the rising number of vehicles on the road, finding adequate parking is one of the sectors with the quickest growth rates. Traffic has typically been a nightmare. intelligent parking solutions from major hardware vendors to address these problems. On the other side, these are unsuited for their intended use and have led to significant parking problems at numerous businesses. The strategy makes an effort to provide a workable solution to the smart parking issue.

show abstract

“…By identifying the source of parking difficulties that affect residents, business owners, and visitors to establish feasible parking management solutions. Instead of manually spending hours finding a suitable parking spot for their vehicle, users can use the proposed solution to find parking spots efficiently without having to waste time and fuel [23].…”

Section: Objectivesmentioning

confidence: 99%

Next Generation Parking System with Computer Vision and Machine Learning

T¹,

Megala²,

S³

et al. 2022

ECS Trans.

View full text Add to dashboard Cite

Parking management is a term that describes methods for making better use of parking resources. The first step toward successful parking management is to identify the cause of the problem. Finding suitable parking is among the fastest-growing industries of all, given the ever-increasing number of cars on the road. Traditionally, traffic has been a nightmare. To address these issues, businesses adopted intelligent parking systems from large hardware vendors. These, on the other hand, are unfit for purpose and also have resulted in major parking issues at many businesses. The approach attempts to offer a practical answer to the problem of smart parking. We aim to create a functioning software that will inform requesting customers if there is still a free parking spot near their location using technologies like Machine Learning, CNN, OpenCV, and React.

show abstract

An approach for building an intelligent parking support system

Cited by 6 publications

References 13 publications

Efficient Multistage License Plate Detection and Recognition Using YOLOv8 and CNN for Smart Parking Systems

Efficient Multistage License Plate Detection and Recognition Using YOLOv8 and CNN for Smart Parking Systems

Enhanced Cloud Car Parking System using ML and Advance Neural Network

Next Generation Parking System with Computer Vision and Machine Learning

Contact Info

Product

Resources

About