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http://dx.doi.org/10.12673/jant.2021.25.2.162

Implementing Parking Zone Management System for Disabled based on Deep Learning using Cloud Platform  

Hwang, Ju-hoon (Department of Energy IT, Gachon University)
Kim, Chang-Bok (Department of Energy IT, Gachon University)
Publication Information
Journal of Advanced Navigation Technology / v.25, no.2, 2021 , pp. 162-168 More about this Journal
Abstract
This study proposed a system that manages parking spaces for the disabled, this will lead to the promotion of welfare for those who are disabled by using deep learning and cloud platforms. Deep learning used you only look once (YOLO) for license plate detection concerning car images in parking areas, and convolutional neural network (CNN) was used for license plate character recognition from extracted numbers and text images. This system can be managed in real time, and it has been simplified so that it can be managed only with video. In addition, it is recognized and accurate by increasing the recognition rate of Korean characters compared to the existing optical character recognition (OCR), and it has the advantage of scalability in the management area by enabling parking management but only if closed circuit television (CCTV) is installed. This system requires a study to increase the accurate license plate recognition rate. This is an important factor, and a continuous study on the processing speed problem to execute YOLO and CNN algorithms in a somewhat low performance raspberry environment.
Keywords
Cloud platform; YOLO; CNN; Raspberry pi; Android phone; Deep learning;
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