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A visual sensor network for parking lot occupancy detection in Smart Cities

机译:智能城市停车场占用检测的视觉传感器网络

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Technology is quickly revolutionizing our everyday lives, helping us to perform complex tasks. The Internet of Things (IoT) paradigm is getting more and more popular and is key to the development of Smart Cities. Among all the applications of IoT in the context of Smart Cities, real-time parking lot occupancy detection recently gained a lot of attention. Solutions based on computer vision yield good performance in terms of accuracy and are deployable on top of visual sensor networks. Since the problem of detecting vacant parking lots is usually distributed over multiple cameras, adhoc algorithms for content acquisition and transmission are to be devised. A traditional paradigm consists in acquiring and encoding images or videos and transmitting them to a central controller, which is responsible for analyzing such content. A novel paradigm, which moves part of the analysis to sensing devices, is quickly becoming popular. We propose a system for distributed parking lot occupancy detection based on the latter paradigm, showing that onboard analysis and transmission of simple features yield better performance with respect to the traditional paradigm in terms of the overall rate-energy-accuracy performance.
机译:技术正在迅速彻底改变我们的日常生活,帮助我们执行复杂的任务。东西互联网(物联网)范式越来越受欢迎,是智能城市发展的关键。在智能城市的背景下,IOT的所有应用中,实时停车位占用率最近获得了很多关注。基于计算机视觉的解决方案在准确性方面产生良好的性能,可在视觉传感器网络顶部部署。由于检测空置停车批量的问题通常在多个摄像机上分布,因此要设计用于内容采集和传输的adhoc算法。传统的范例包括获取和编码图像或视频并将其传输到中央控制器,该中心控制器负责分析此类内容。一种新的范式,它将部分分析到传感设备,很快就变得流行。我们提出了一种基于后者范式的分布式停车位占用检测系统,表明在整体速率 - 能量准确性表现方面,简单特征的板载分析和传输产生了更好的传统范式的性能。

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