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A Smart Emergency Notification System for Road Accident, Fire, and Injury Cases

机译：道路事故，火灾和伤病例的智能紧急通知系统

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摘要

In this article, a system Smart Emergency Notification System (SENS) is proposed for both emergency responders and the community. SENS detects single/multiple emergency case(s) (i.e. road accident, fire, and injury) automatically from images sent by a smartphone via the Internet by the proposed promising approach; afterward, it notifies the police, fire brigade, and/or ambulance. The SENS has three modules: the mobile application SENSdroid, the Web application WebSENS, and the software agent NotiSENS, which uses the proposed approach. This approach is as follows. First, a dataset that contains accident, fire, and injury images was constructed; their labels were obtained for training; the trained results, Google Cloud Vision API, and cosine similarity measurement were used to detect the emergency case(s) for an input image. Based on the test results, the approach has 84% sensitivity, 92% specificity, and 88% accuracy. It is possible to say that SENS would have a positive effect on helping the harmed person, supporting the staff on duty, protecting the person who can be harmed, and/or saving Nature. Additionally, this system would have high usability because of its easy-to-use features and high rates of smartphone and Internet users. It is believed that SENS could be an efficient and useful system. (C) 2020 Society for Imaging Science and Technology.
机译：在本文中，为紧急响应者和社区建议了一个系统智能紧急通知系统（SENS）。 SENS通过互联网通过互联网通过互联网发送的图像自动检测单/多次紧急情况（即道路事故，火灾和伤害）;之后，它通知警察，消防队和/或救护车。该SENS有三个模块：移动应用程序Sensdroid，Web应用程序Websens和软件代理商指出，它使用所提出的方法。这种方法如下。首先，构建了一个包含事故，火灾和伤害图像的数据集;他们的标签获得培训;培训的结果，Google Cloud Vision API和余弦相似度测量用于检测输入图像的紧急情况。基于测试结果，该方法具有84％的灵敏度，92％的特异性和88％的准确性。可以说，SENS对帮助受伤的人提供积极影响，支持员工值班，保护可能受到伤害的人和/或储蓄性质。此外，由于其易于使用的功能和高智能手机和互联网用户，该系统将具有高可用性。据信，SENS可能是一个有效和有用的系统。 （c）2020年影像科技协会。

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  • 来源
    《Journal of Imaging Science and Technology》 |2020年第3期|30506.1-30506.10|共10页
  • 作者

    Yildiz Emre Rifat; Bitirim Yiltan;

  • 作者单位

    Eastern Mediterranean Univ Dept Comp Engn Fac Engn Via Mersin 10 TR-99628 Famagusta North Cyprus Turkey;

    Eastern Mediterranean Univ Dept Comp Engn Fac Engn Via Mersin 10 TR-99628 Famagusta North Cyprus Turkey;

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