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Designing and Implementing a Real Time Weapons Detection System on ODROID-XU4

机译:在ODROID-XU4上设计和实现实时武器检测系统

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Artificial Intelligence has got many applications in security and camera analytics. In recent times, there are 245 million IP cameras already installed globally. To make these IP Cameras intelligent, processing power is required. For which we may use a cloud or a local hardware which has pros and cons. But in general, selecting a local hardware to run an AI application is more difficult and almost a challenging task. According to latest statistics gun ownerships among civilians on a rise. Latest statistics say 393 million guns are owned by civilians in USA, 71 million guns are owned by civilians in India and 50 million guns are owned by civilians in China etc., which says threats due to guns are increasing globally. Existing weapon detection systems are costly and requires special equipment like special scanners, cameras etc. Weapon detection systems that are simple and accurate are required. Hence, in this paper, we proposed a design and implementation of weapon detection system in a simple ODROID-XU4 connected to a cheap IP HD camera and achieved an accuracy more than 99.8% in real time. So as to give an alert to the nearest police men if any weapon found on busy roads or in heavy buildings.
机译:人工智能在安全性和摄像机分析中有许多应用。最近,全球已经安装了2.45亿个IP摄像机。为了使这些IP摄像机智能化,需要处理能力。为此,我们可能会使用具有优点和缺点的云或本地硬件。但总的来说,选择本地硬件来运行AI应用程序更加困难,而且几乎是一项艰巨的任务。根据最新统计,平民中的枪支拥有量正在上升。最新统计数据显示,美国平民拥有3.93亿支枪,印度平民拥有7100万支枪,中国平民拥有5000万支枪,等等,这表明全球范围内枪支带来的威胁正在增加。现有的武器检测系统价格昂贵,并且需要特殊的设备,例如特殊的扫描仪,照相机等。需要简单而准确的武器检测系统。因此,在本文中,我们提出了一种在连接到廉价IP HD摄像机的简单ODROID-XU4中进行武器检测系统的设计和实现,其实时性达到了99.8%以上。以便在繁忙的道路上或重型建筑中发现任何武器时,向附近的警察发出警报。

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