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Towards ICT based mobility support system with in the COVID-19 era: poster abstract

Published:16 November 2020Publication History

ABSTRACT

Our objective is to achieve a city where everyone can move safely and comfortably by developing and implementing ICT-based mobile support system at the actual transport hub. Our system uses cameras installed at the transport hub to detect people who have difficulty moving, and notifies this information to the transportation staff in real time to help them move more smoothly. This system makes it possible to aggregate and provide information on places that is useful for COVID-19 measures, such as measuring the congestion of places and the social distances of the people who gather there.

References

  1. Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao. 2020. YOLOv4: Optimal Speed and Accuracy of Object Detection. CoRR abs/2004.10934 (2020). arXiv:2004.10934 https://arxiv.org/abs/2004.10934Google ScholarGoogle Scholar
  2. Labour Ministry of Health and Welfare of Japan. 2020. How to Avoid the 3Cs. Retrieved Sep 24, 2020 from http://japan.kantei.go.jp/ongoingtopics/COVID19CASFlyer/PROffice3CGuide_en.pdfGoogle ScholarGoogle Scholar

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  1. Towards ICT based mobility support system with in the COVID-19 era: poster abstract

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      • Published in

        cover image ACM Conferences
        SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems
        November 2020
        852 pages
        ISBN:9781450375900
        DOI:10.1145/3384419

        Copyright © 2020 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 16 November 2020

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        • poster

        Acceptance Rates

        Overall Acceptance Rate174of867submissions,20%

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