Smart Surveillance System using Deep Learning and RaspberryPi

Kshitij Patel, Meet Patel
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引用次数: 2

Abstract

Today, in the technological era of the 21st century, CCTV cameras have been proven to be very fruitful in our daily lives. From monitoring the baby in the bassinet to prevent some crimes, CCTV camera has become of vital importance. We as humans, always try to make things perfect around us. Using this article, we also have attempted to present our perspective to make these CCTV cameras more perfect. We have made an effort to enhance regular CCTV cameras using the vast field of deep learning and IoT. We have attempted to accomplish our goal by providing a protoStype for the smart surveillance system. We have tried to upgrade the regular CCTV cameras with some customized deep learning models developed by us. In this modified version, we have given the CCTV cameras the ability to detect fire and weapons. Also, we have tried to fulfil an ad-hoc requirement of Face Mask Detection considering the current situation of COVID19. For fulfilling our objective, we have provided an outline combining IoT (RaspberryPi) to deep learning using AWS EC2 Cloud Architecture. To make the surveillance system user-friendly, we have also taken account of the client-side interface. Considering all the above applications, we have successfully provided an archetype in this paper.
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使用深度学习和树莓派的智能监控系统
在21世纪科技时代的今天,CCTV摄像机已经被证明在我们的日常生活中是非常富有成效的。从监控摇篮里的婴儿到防止一些犯罪,闭路电视摄像机已经变得至关重要。作为人类,我们总是试图让我们周围的事情变得完美。利用本文,我们也试图提出我们的观点,使这些闭路电视摄像机更加完善。我们已经努力利用深度学习和物联网的广阔领域来增强普通的闭路电视摄像机。我们试图通过提供智能监控系统的原型来实现我们的目标。我们尝试用我们开发的一些定制的深度学习模型来升级普通的CCTV摄像机。在这个修改版本中,我们赋予了闭路电视摄像机探测火力和武器的能力。此外,考虑到covid - 19的当前形势,我们已努力满足口罩检测的临时要求。为了实现我们的目标,我们提供了一个大纲,将物联网(RaspberryPi)与使用AWS EC2云架构的深度学习相结合。为了使监控系统用户友好,我们还考虑了客户端界面。考虑到上述所有应用,本文成功地提供了一个原型。
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