A systematic review on computer vision-based parking lot management applied on public datasets

Almeida, Paulo Ricardo Lisboa de; Alves, Jeovane Honório; Parpinelli, Rafael Stubs; Barddal, Jean Paul

doi:10.1016/j.eswa.2022.116731

Cited by 25 publications

(7 citation statements)

References 32 publications

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“…If there is no significant correlation between the effective values calculated by the two index systems, it can be considered that the optimization index system is not comprehensive. On the contrary, if the correlation is significant, it indicates that the optimized index system can replace the previous index system for performance evaluation analysis [ 21 ]. The steps are as follows:…”

Section: Performance Evaluation Of Public Management Cultural Service...mentioning

confidence: 99%

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Application of Improved DEA Algorithm in Public Management Problem Classification

2022

Computational Intelligence and Neuroscience

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In order to effectively solve the related problems in the process of public management, this research proposes an improved algorithm technology based on Data Envelopment Analysis (DEA) and classification algorithm. With the help of lever management, this paper further solves and overcomes the problem of DEA algorithm itself and the defect of “relative effectiveness.” At the same time, in order to avoid the impact on the input and output indicators, with the help of principal component analysis, taking the performance evaluation of public management departments as the research direction, this paper makes an empirical analysis on the performance evaluation of public management departments. The evaluation results of the index system show that the correlation coefficient between the efficiency value of the initial index system and the efficiency value of optimization 2 is 0.977759, and the correlation coefficient is less than 0.7. The evaluation results are more reasonable than those before the improvement.

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Section: Performance Evaluation Of Public Management Cultural Service...mentioning

confidence: 99%

“…Bring equation (20) into equation ( 17) and use equation (21) to know that the dual problem of the original optimization problem can be expressed as…”

Section: Improved Dea Algorithm and Classification Algorithmmentioning

confidence: 99%

Application of Improved DEA Algorithm in Public Management Problem Classification

2022

Computational Intelligence and Neuroscience

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“…Пауло де Алмеіда та ін. зробили досить детальний огляд наявних публічних датасетів, які створені спеціально для проблеми керування паркувальними майданчиками з використанням комп'ютерного зору, а також наукових праць, де згадано ці датасети [6]. Вони визначили критерій відбору датасетів, відкидаючи ті, що не підходять для вирішення реальних проблем.…”

Section: проблеми реалізації моделі комп'ютерного зоруunclassified

Parking Spot Occupancy Classification Using Deep Learning

Kreshchenko

Yushchenko

2023

NRPCOMP

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In today’s world, where a car is present in almost every family, the parking problem plays an extremely important role. Parking is one of the most important factors in modern transport infrastructure, because it allows to save the time of both drivers and passengers, to increase the level of comfort and safety of road trips. In Ukraine, this problem is especially relevant, since nowadays it is going through the process of improving its parking infrastructure.The paper examines the problem of parking in large cities, proposes a system for recognizing occupancy of parking spots using computer vision. Such system would use camera feed to track the occupancy of each parking space within a slot. Its benefits would include ease of scalability, saving time of drivers and passengers, automation of parking payment and detection of unpaid parkings. In addition, it makes it possible to easily collect statistics about the busyness of various areas throughout the day or week.The paper also describes the algorithm of classifying the parking spot, as well as a possible architecture that the system may have.Possible problems in training a computer vision model for building the proposed system are considered. Firstly, the available parking datasets are lacking images collected in snow conditions or during nighttime. The hypothesized solution is to use vehicle detection datasets, the number of which that are publicly available is considerably bigger. Another problem is that classification accuracy drops drastically when using different images in train and test dataset. The hypothesized solution here is to apply incremental learning to improve the model as it is being used in a real-life scenario.

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“…The literature review provides a comprehensive examination of the existing body of knowledge concerning the utilization of AI and CV technologies in transportation systems and parking facility management, with a specific focus on their application in lane identification and parking spot detection. Several studies [17,18] have extensively explored the integration of deep learning and transfer learning techniques to enhance lane identification and parking spot detection across various contexts. These investigations [17][18][19][20] have effectively demonstrated the prowess of deep learning models, notably convolutional neural networks (CNN), in proficiently analyzing video data and accurately detecting lanes and parking spaces.…”

Section: Related Workmentioning

confidence: 99%

“…Several studies [17,18] have extensively explored the integration of deep learning and transfer learning techniques to enhance lane identification and parking spot detection across various contexts. These investigations [17][18][19][20] have effectively demonstrated the prowess of deep learning models, notably convolutional neural networks (CNN), in proficiently analyzing video data and accurately detecting lanes and parking spaces.…”

Section: Related Workmentioning

confidence: 99%

AI-Powered Intelligent Seaport Mobility: Enhancing Container Drayage Efficiency through Computer Vision and Deep Learning

Lee,

Chatterjee,

Cho

2023

Applied Sciences

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The rapid urbanization phenomenon has introduced multifaceted challenges across various domains, including housing, transportation, education, health, and the economy. This necessitates a significant transformation of seaport operations in order to optimize smart mobility and facilitate the evolution of intelligent cities. This conceptual paper presents a novel mathematical framework rooted in deep learning techniques. Our innovative model accurately identifies parking spaces and lanes in seaport environments based on crane positions, utilizing live Closed-Circuit Television (CCTV) camera data for real-time monitoring and efficient parking space allocation. Through a comprehensive literature review, we explore the advantages of merging artificial intelligence (AI) and computer vision (CV) technologies in parking facility management. Our framework focuses on enhancing container drayage efficiency within seaports, emphasizing improved traffic management, optimizing parking space allocation, and streamlining container movement. The insights from our study provide a foundation that could have potential implications for real-world applications. By integrating cutting-edge technologies, our proposed framework not only enhances the efficiency of seaport operations, but also lays the foundation for sustainable and intelligent seaport systems. It signifies a significant leap toward the realization of intelligent seaport operations, contributing profoundly to the advancement of urban logistics and transportation networks. Future research endeavors will concentrate on the practical implementation and validation of this pioneering mathematical framework in real-world seaport environments. Additionally, our work emphasizes the crucial need to explore further applications of AI and CV technologies in seaport logistics, adapting the framework to address the evolving urbanization and transportation challenges. These efforts will foster continuous advancements in the field, shaping the future of intelligent seaport operations.

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A systematic review on computer vision-based parking lot management applied on public datasets

Cited by 25 publications

References 32 publications

Application of Improved DEA Algorithm in Public Management Problem Classification

Application of Improved DEA Algorithm in Public Management Problem Classification

Parking Spot Occupancy Classification Using Deep Learning

AI-Powered Intelligent Seaport Mobility: Enhancing Container Drayage Efficiency through Computer Vision and Deep Learning

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