IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0299950.html

Early warning on safety risk of highly aggregated tourist crowds based on VGGT-Count network model

Author

Listed:
  • Jingjing Liu
  • Gengan Wu
  • Yao Liu

Abstract

In the era of mass tourism, more and more people are attracted by internet-famous site. With people’s demand for travel surged, tourists are getting together in one scenic spot with doubling numbers, which easily leads to high concentration of tourists with uncontrollable security risks. It needs to be highly valued by the tourism department. Monitoring and issuing warnings for crowd density in scenic areas with Highly Aggregated Tourist Crowds (HATCs) is an urgent challenge that needs to be addressed. In this paper, Highly Aggregated Tourist Crowds is taken as the research objective, and a VGGT-Count network model is proposed to forecast the density of HATCs. The experimental outcomes demonstrated a substantial improvement in counting accuracy for the ShanghaiTech B and UCF-QNRF datasets. Furthermore, the model allows for real-time monitoring of tourist attractions, enabling advanced prediction of high concentrations in scenic areas. This timely information can alert relevant authorities to implement preventive measures such as crowd control and flow regulation, thereby minimizing safety hazards.

Suggested Citation

  • Jingjing Liu & Gengan Wu & Yao Liu, 2024. "Early warning on safety risk of highly aggregated tourist crowds based on VGGT-Count network model," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-17, March.
    • Handle: RePEc:plo:pone00:0299950
    DOI: 10.1371/journal.pone.0299950
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0299950
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299950&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0299950?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Subramanian, Gayathri Harihara & Choubey, Nipun & Verma, Ashish, 2022. "Modelling and simulating serpentine group behaviour in crowds using modified social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Shiyu & Huang, Ping & Wang, Wei, 2022. "An optimization method for evacuation guidance under limited visual field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. Tian, Jiangtao & Li, Xingli & Guo, Qinghua & Kuang, Hua, 2024. "Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    3. Choubey, Nipun & Verma, Ashish & Chakraborty, Anirban, 2024. "An unsupervised group detection method for understanding group dynamics in crowds," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 655(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0299950. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.