IDEAS home Printed from https://ideas.repec.org/a/hin/jnlamp/7592180.html
   My bibliography  Save this article

Construction and Application of Video Big Data Analysis Platform for Smart City Development

Author

Listed:
  • Xu Wu
  • Guifeng Yan
  • Xintian Xie
  • Yan Bao
  • Wei Zhang
  • Miaochao Chen

Abstract

With the progress of society and the rapid development of science and technology, daily data volume also shows an exponential upward trend. From the research report of the Internet data center, we can see that the growth rate of data will change from the original slow growth to a sharp rise within 10 years. This shows that the era of big data has arrived, and video data plays an important role in it. Video comes from all aspects of life. As a typical unstructured data, video has the characteristics of large memory, and with the leap of society, this characteristic is becoming increasingly obvious. Taking video data analysis as the starting point, this paper proposes a long-term and short-term memory neural network integrating attention mechanism and verifies it in the experimental data set. The experiment shows that this method has superior performance in model accuracy and work efficiency. Therefore, the application of this method to the construction and application of video big data analysis platform is an important step to promote the development of smart cities.

Suggested Citation

  • Xu Wu & Guifeng Yan & Xintian Xie & Yan Bao & Wei Zhang & Miaochao Chen, 2022. "Construction and Application of Video Big Data Analysis Platform for Smart City Development," Advances in Mathematical Physics, Hindawi, vol. 2022, pages 1-10, September.
  • Handle: RePEc:hin:jnlamp:7592180
    DOI: 10.1155/2022/7592180
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/amp/2022/7592180.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/amp/2022/7592180.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/7592180?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
    ---><---

    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:hin:jnlamp:7592180. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.