• Title/Summary/Keyword: Kickboard sharing services

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Analysis of User Reviews of Electric Kickboard Sharing Service Using Topic Modeling (토픽 모델링을 활용한 전동킥보드 공유 서비스의 사용자 리뷰 분석)

  • Jung Seung Lee
    • Journal of Information Technology Applications and Management
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    • v.31 no.1
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    • pp.163-175
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    • 2024
  • This study conducts topic modeling analysis on four electric scooter sharing platforms: Alpaca, SingSing, Kickgoing, and Beam. Using user review data, the study aims to identify key topics and issues associated with each platform, as well as uncover common themes across platforms. The analysis reveals that users primarily express concerns and preferences related to application usability, service mobility, and parking/accessibility. Additionally, each platform exhibits unique characteristics and challenges. Alpaca users generally appreciate convenience and enjoyment but express concerns about safety and service areas. SingSing faces issues with application functionality, while Kickgoing users encounter connectivity problems and device usability issues. Beam receives overall positive feedback, but users express dissatisfaction with application usability and parking. Based on these findings, scooter sharing service providers should focus on enhancing application features, stability, and expanding service coverage to meet user expectations and improve customer satisfaction. Furthermore, highlighting platform-specific strengths and providing tailored services can enhance competitiveness and foster continuous service growth and development.

Analysis and Improvement of Utilization Status through GPS Data Analysis of Shared Electric Kickboard in Wirye New Town (위례 신도시 공유 전동 킥보드 GPS데이터 분석을 통한 이용실태 분석 및 개선사항)

  • Hong, Seok-Do;You, Yen-Yoo
    • The Journal of the Korea Contents Association
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    • v.21 no.9
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    • pp.471-476
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    • 2021
  • Personal mobility (PM) is a new concept of transportation used by one or two people using electricity. Personal transportation aims to move quickly and conveniently over an ambiguous distance that is too close to the destination and too far to walk. In particular, as electric kickboard sharing services have become more common in recent years, they are receiving great popularity from citizens. However, it is necessary to come up with an alternative solution as it is acting as a risk not only to users but also to pedestrians and road drivers. Therefore, in order to present measures to establish and improve a safe personal mobility utilization environment, this research was conducted as follows. First, based on GPS data from shared electric kickboards, the usage status in everyday life was examined and analyzed in detail. Second, it is convenient to rent and return shared electric kickboards directly to applications regardless of time, and it is highly accessible to rent them from their location and reach their destination. Based on these findings, this study suggests that careful access to rental and return could have a more positive effect on users and pedestrians by installing a cradle in a place where there is more use than disorderly device placement and expansion.

IoT based Wearable Smart Safety Equipment using Image Processing (영상 처리를 이용한 IoT 기반 웨어러블 스마트 안전장비)

  • Hong, Hyungi;Kim, Sang Yul;Park, Jae Wan;Gil, Hyun Bin;Chung, Mokdong
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.3
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    • pp.167-175
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    • 2022
  • With the recent expansion of electric kickboards and bicycle sharing services, more and more people use them. In addition, the rapid growth of the delivery business due to the COVID-19 has significantly increased the use of two-wheeled vehicles and personal mobility. As the accident rate increases, the rule related to the two-wheeled vehicles is changed to 'mandatory helmets for kickboards and single-person transportation' and was revised to prevent boarding itself without driver's license. In this paper, we propose a wearable smart safety equipment, called SafetyHelmet, that can keep helmet-wearing duty and lower the accident rate with the communication between helmets and mobile devices. To make this function available, we propose a safe driving assistance function by notifying the driver when an object that interferes with driving such as persons or other vehicles are detected by applying the YOLO v5 object detection algorithm. Therefore it is intended to provide a safer driving assistance by reducing the failure rate to identify dangers while driving single-person transportation.