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Vision and Crowdsensing Technology for an Optimal Response in Physical-Security

机译:视觉和人群感知技术可实现物理安全性的最佳响应

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Law enforcement agencies and private security companies work to prevent, detect and counteract any threat with the resources they have, including alarms and video surveillance. Even so, there are still terrorist attacks or shootings in schools in which armed people move around a venue exercising violence and generating victims, showing the limitations of current systems. For example, they force security agents to monitor continuously all the images coming from the installed cameras, and potential victims nearby are not aware of the danger until someone triggers a general alarm, which also does not give them information on what to do to protect themselves. In this article we present a project that is being developed to apply the latest technologies in early threat detection and optimal response. The system is based on the automatic processing of video surveillance images to detect weapons and a mobile app that serves both for detection through the analysis of mobile device sensors, and to send users personalised and dynamic indications. The objective is to react in the shortest possible time and minimise the damage suffered.
机译:执法机构和私人安全公司致力于利用其所拥有的资源(包括警报和视频监控)来预防,检测和应对任何威胁。即便如此,在学校中仍然存在恐怖袭击或枪击事件,武装人员在这些场所四处走动,那里有暴力活动并招致受害者,这表明了当前系统的局限性。例如,他们强迫安全代理连续监视来自已安装摄像机的所有图像,附近的潜在受害者直到有人触发一般警报时才意识到危险,这也不会向他们提供有关如何保护自己的信息。 。在本文中,我们提出了一个项目,该项目正在开发中,目的是将最新技术应用于早期威胁检测和最佳响应。该系统基于对视频监视图像的自动处理,以检测武器和移动应用程序,该应用程序既可以通过分析移动设备传感器来进行检测,又可以向用户发送个性化的动态指示。目的是在尽可能短的时间内做出反应,并尽量减少遭受的损害。

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