• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.652-665
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• 2022

Difference found in the degree of activating commercial space in subway stations is getting bigger and bigger. With an assumption that commercial space in stations demands public management, this study is aimed to figure out factors that influence the activation of commercial space in stations. To address the goal, the AHP was adopted to draw the importance of activation indexes. Applying the importance of activation indexes drawn, this study analyzed 260 stations located in Seoul regarding the ranking of activation of the stations and also the characteristics of each individual region and index. According to the findings of analysis, there exists a great gap in the degree of activation by either life zones or autonomous districts, and factors having big influence over activation are found to be floating population and the number of passengers getting in or out.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1517-1524
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• 2014

In recent years, the interest of environmental-friendly transportation modes has been growing. This is because of social and environmental problems such as increasing gas price and climate change. In Europe, bike-sharing service, one of the environmental-friendly transportation modes, has been already operated. Bike-sharing service named "Tashu" has been operated in Daejeon city since 2009. This study is a fundamental research to increase utilization efficiency of bike-sharing service and to decide optimal locations of bike stations. In addition this study examines characteristics of bike usage and analyzes factors affecting to demands using multiple regression model. Based on the result of examining of characteristics of bike usage, the rate of bike usage is higher compared with installation rate of public bike stations near parks in Daejeon. In addition demands of bike usage in weekend is higher than in weekday. It reveals that the main purpose of bike usage could be recreational activities. The return rate at the same location with rental station is comparatively high. Moreover, bike usage pattern is biased in specific areas (Dunsan and Yuseong) because bike-sharing stations are not equally located. As a result of multiple regression model, the factors affecting to demands are number of passengers in buses, length of bike lanes, parks, distance to waterfront, and rate of young people. A statistical significance of factors (r-square) is 0.748, which has strong relationship.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.9-19
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• 2024

In this paper, a real-time public transportation monitoring system is proposed. The proposed system was implemented by developing a public transportation app and utilizing optical sensors, pressure sensors, and an object detection algorithm. Additionally, a bus model was created to verify the system's functionality. The proposed real-time public transportation monitoring system has three key features. First, the app can monitor congestion levels within public transportation by detecting seat occupancy and the total number of passengers based on changes in optical and pressure sensor readings. Second, to prevent errors in the optical sensor that can occur when multiple passengers board or disembark simultaneously, we explored the possibility of using the YOLO object detection algorithm to verify the number of passengers through CCTV footage. Third, convenience is enhanced by displaying occupied seats in different colors on a separate screen. The system also allows users to check their current location, available public transportation options, and remaining time until arrival. Therefore, the proposed system is expected to offer greater convenience to public transportation users.