English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 847822      Online Users : 529
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/16128


    Title: Next-Generation swimming pool drowning prevention strategy integrating AI and IoT technologies
    Authors: Kao, WC;Fan, YL;Hsu, FR;Shen, CY;Liao, LD
    Contributors: Institute of Biomedical Engineering and Nanomedicine
    Abstract: Drowning, as a leading cause of unintentional injury-related deaths worldwide, is a major public health concern. Swimming pool drowning is the main cause of most drowning incidents, and even with preventive measures such as surveillance cameras and lifeguards, tens of thousands of lives are lost to drowning every year. To address this issue, technology is being utilized to prevent drowning accidents and provide timely alerts for rescue. This paper explores the use of drowning prevention technology in embedded systems within enclosed environments, artificial intelligence (AI), and the Internet of Things (IoT) to decrease the likelihood of drowning incidents. Embedded systems play a critical role in such technology, enabling real-time monitoring, identification of dangerous situations, and prompt alerting. Due to their ease of installation and technical implementation, embedded devices are especially effective as drowning prevention devices. The image recognition capabilities of drowning prevention systems are enhanced through computer vision. Swimming pool drowning situations can be identified with the help of cameras and deep learning technologies, thereby increasing rescue efficiency. Finally, the IoT endows drowning prevention systems with comprehensive intelligence by connecting various devices and communication tools. Real-time alert transmission and analysis have become possible, enabling the early prediction of dangerous situations and the implementation of preventive measures, significantly reducing drowning incidents. In summary, the integration of these three types of drowning prevention technologies represents significant progress. The flexibility, accuracy, and intelligence of drowning prevention systems are enhanced through the incorporation of these technologies, providing robust support for safeguarding human lives and thus potentially saving tens of thousands of lives each year.
    Date: 2024-09-30
    Relation: Heliyon. 2024 Sep 30;10(18):Article number e35484.
    Link to: http://dx.doi.org/10.1016/j.heliyon.2024.e35484
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=2405-8440&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:001314516300001
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85203544285
    Appears in Collections:[廖倫德] 期刊論文

    Files in This Item:

    File Description SizeFormat
    ISI001314516300001.pdf5503KbAdobe PDF39View/Open


    All items in NHRI are protected by copyright, with all rights reserved.

    Related Items in TAIR

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback