발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.4] Design and Implementation of a Facial Recognition Model to Prevent Safety Accidents in Buses |
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| 논문투고자 |
Seonho Ryu, Chool Ryu, Sangchul Lee, Hoekyung Jung |
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| 논문내용 |
The process of getting off through the drop-off tag action using a transportation card when getting off the bus increases the incidence of sudden stop accidents. In this paper, we propose a face recognition model to prevent in-bus safety accidents that can match passengers' transportation card ride information to classify passengers' ID, ride time, and passengers' face image, and communicate face recognition and boarding/leaving information in real time in a bus environment by combining hardware. Facial image data is applied to a convolutional neural network (CNN) model through preprocessing to extract and classify facial features. In addition, a server that extracts characteristic information of an image according to the in-bus environment and an MCU(Micro Controller Unit) board that transmits images of passengers on the bus are used, and RFID is used to extract card information of passengers. Using the Raspberry PI, a web streaming server is built, and a face recognition model for preventing safety accidents on buses is implemented using Socket communication for communication with a server that extracts feature information. Through this, it is believed that it will contribute to the prevention of accidents by recognizing passengers' drop-off information only with facial information without drop-off tag action, and will serve as a cornerstone for the use and application of various safety accidents on the bus, such as safety warnings through the model. |
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