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

机译:视觉传感器网络,用于智能城市中的停车场占用检测

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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:技术正在迅速改变我们的日常生活,帮助我们执行复杂的任务。物联网(IoT)范式正变得越来越流行,并且是智慧城市发展的关键。在智能城市环境下的物联网的所有应用中,实时停车场占用率检测最近引起了很多关注。基于计算机视觉的解决方案在准确性方面具有良好的性能,并且可以部署在视觉传感器网络之上。由于检测空闲停车场的问题通常分布在多个摄像机上,因此将设计用于内容获取和传输的自组织算法。传统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,该中央控制器负责分析此类内容。一种将分析的一部分移至传感设备的新颖范例正在迅速普及。我们提出了一种基于后一种范式的分布式停车场占用率检测系统,该系统表明,就整体速率-能量-精度性能而言,车载分析和简单特征的传输相对于传统范式具有更好的性能。

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