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首页> 外文期刊>Communications Surveys & Tutorials, IEEE >Ubiquitous Localization (UbiLoc): A Survey and Taxonomy on Device Free Localization for Smart World
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Ubiquitous Localization (UbiLoc): A Survey and Taxonomy on Device Free Localization for Smart World

机译:无处不在的本地化(UbiLoc):关于智能世界中无设备本地化的调查和分类法

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摘要

The "Smart World" envisioned by technology will be achieved by the penetration of intelligence into ubiquitous things, including physical objects, cyber-entities, social-elements or individuals, and human thinking. The development of Smart World is enabled by diverse applications of wireless sensor networks (WSNs) into those components identified as things. Such a smart-world will have features controlled significantly by the location information. Control and Policy information of Smart World services, often addressed as location-based services (LBSs), are governed by location data. Localization thus becomes the key enabling technology for Smart World facilities. It is generally classified as active and passive techniques in nature. Active localization is a widely adopted localization scheme where the target is detected and tracked carries a tag or attached device. The other category, Passive methods, defines targets to be localized as free of carrying a tag or device, hence also referred to as device-free localization (DFL) or sensor-less localization. The passive approach is a well suited for the development of diverse smart world applications with ubiquitous localization. DFL schemes fall into a wide range of application scenarios within the Smart World ecosystem. A few notable examples are occupancy detection, identity definition, positioning, gesture detection, activity monitoring, pedestrian and vehicle-traffic flow surveillance, security safeguarding, ambient intelligence-based systems, emergency rescue operations, smart work-spaces and patient or elderly monitoring. In this paper, the revolution of DFL technologies have been reviewed and classified comprehensively. Further, the emergence of the Smart World paradigm is analyzed in the context of DFL principles. Moreover, the inherent challenges within the application domains have been extensively discussed and improvement strategies for multi-target localization and counting approach are discussed. Finally, current trends and future research directions have been presented.
机译:技术所设想的“智能世界”将通过将情报渗透到无处不在的事物中来实现,这些事物包括物理对象,网络实体,社会要素或个人以及人类思维。通过将无线传感器网络(WSN)应用于识别为事物的那些组件中,可以实现智能世界的发展。这样的智能世界将具有由位置信息显着控制的功能。通常被称为基于位置的服务(LBS)的智能世界服务的控制和策略信息由位置数据控制。因此,本地化成为智能世界设施的关键启用技术。实际上,它通常被分为主动技术和被动技术。主动定位是一种广泛采用的定位方案,在该方案中,目标被检测并被跟踪携带标签或连接的设备。另一类,无源方法,将要定位的目标定义为不携带标签或设备,因此也称为无设备定位(DFL)或无传感器定位。被动方法非常适合开发具有普遍存在的本地化的各种智能世界应用程序。 DFL方案属于Smart World生态系统中的广泛应用场景。几个著名的例子是占用检测,身份定义,定位,手势检测,活动监视,行人和车辆流量监视,安全保护,基于环境情报的系统,紧急救援行动,智能工作区以及病人或老人监视。本文对DFL技术的革命进行了全面回顾和分类。此外,在DFL原则的背景下分析了“智能世界”范式的出现。而且,已经广泛讨论了应用领域内的固有挑战,并讨论了用于多目标定位和计数方法的改进策略。最后,介绍了当前的趋势和未来的研究方向。

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