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Ferret: RFID Localization for Pervasive Multimedia

机译:雪貂:普及多媒体的RFID本地化

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摘要

The pervasive nature of multimedia recording devices enables novel pervasive multimedia applications with automatic, inexpensive, and ubiquitous identification and locationing abilities. We present the design and implementation of Ferret, a scalable system for locating nomadic objects augmented with RFID tags and displaying them to a user in real-time. We present two alternative algorithms for refining a postulation of an object's location using a stream of noisy readings from an RFID reader: an online algorithm for real-time use on a mobile device, and an offline algorithm for use in post-processing applications. We also present methods for detecting when nomadic objects move and how to reset the algorithms to restart the refinement process. An experimental evaluation of the Ferret prototype shows that (ⅰ) Ferret can refine object locations to only 1% of the reader's coverage region in less than 2 minutes with small error rate (2.22%); (ⅱ) Ferret can detect nomadic objects with 100% accuracy when the nomadic distances exceed 20cm; and (ⅲ) Ferret works with a variety of user mobility patterns.
机译:多媒体记录设备的无处不在的性质使得新颖的无所不在的多媒体应用具有自动,廉价且无处不在的识别和定位能力。我们介绍了Ferret的设计和实现,Ferret是一种可扩展的系统,用于定位带有RFID标签的游牧物体,并将其实时显示给用户。我们提出了两种备选算法,这些算法可使用来自RFID阅读器的一连串嘈杂读数来完善对象位置的假设:一种在移动设备上实时使用的在线算法,以及一种用于后处理应用的离线算法。我们还提供了用于检测游牧对象何时移动以及如何重置算法以重新启动精炼过程的方法。对Ferret原型的实验评估表明:(ⅰ)Ferret可以在不到2分钟的时间内将对象位置缩小到阅读器覆盖区域的1%,错误率很小(2.22%); (ⅱ)当游牧距离超过20厘米时,雪貂可以100%准确地检测到游牧物体; (ⅲ)雪貂可以使用各种用户移动性模式。

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