NeTS: Small: Handheld mm-Accurate Positioning for Wearables

NeTS：小型：手持式毫米级可穿戴设备精确定位

• 批准号: 1718435
• 负责人: Swarun Kumar
• 金额: $ 50万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718435&HistoricalAwards=false
• 关键词: NeTS; Small; Handheld; mm; Accurate

This proposal develops a system that can track wearables on a user's body with millimeter (mm) accuracy using a handheld device in the user's pocket. Unlike past work, it does so without the need for external infrastructure (e.g. cameras or antenna arrays) or inaccurate, bulky and battery-powered sensors on the body. The proposed work attaches tiny radio frequency identification (RFID) tags that are cheap (costing a few cents) and completely battery-free on to on-body devices or the user's clothing. It then monitors the locations of these tags from a handheld RFID reader in the user's pocket. Unlike past solutions that use bulky, many-antenna RFID readers to locate RFID tags, our approach needs only a single-antenna reader that is both compact and portable. The proposed work will be fully implemented and evaluated on commodity RFID hardware and tags; the solution opens up a rich set of applications. Consider medical tests such as Electroencephalogram (EEG) that can become truly 'wearable', with electrodes on the head positioned automatically without requiring time-consuming manual measurements by a physician. Or consider smart textiles that can now serve as gesture-based interfaces that track a user's movements relative to handheld devices. The proposed research presents three contributions: (1) It proposes a novel approach to disentangle wireless signals traversing different paths from RFID tags to a single-antenna RFID reader - a key challenge in positioning research. It achieves this without relying on bulky, multi-antenna arrays used in past literature. Its core idea is to use signals from teams of RFID tags to separate wireless signal components along different paths. (2) It investigates a solution to locate RFID tags relative to other tags whose positions are known. It seeks to do this using an algorithm that leverages similarity between the wireless signal paths experienced by the tag of interest and neighboring tags whose locations are known. (3) It fully integrates the system to target two applications: i) A wearable EEG system that tracks electrodes on the head using RFID tags attached to them. This eliminates the need for cumbersome manual measurements that doctors perform today before administering the test, allowing EEG to be truly portable. ii) A smart fabric with embedded RFID tags tracked by a mobile device to track the users movements both for continuous fitness monitoring and to create a gesture-based user interface.

该提案开发了一种系统，该系统可以使用用户口袋中的手持设备以毫米（mm）精度跟踪用户身体上的可穿戴设备。与过去的工作不同，它不需要外部基础设施（例如相机或天线阵列）或身体上不准确，笨重和电池供电的传感器。 这项拟议中的工作将廉价（成本仅为几美分）且完全无电池的微型射频识别（RFID）标签贴在身体设备或用户的衣服上。然后，它从用户口袋里的手持RFID阅读器监控这些标签的位置。与过去使用笨重的多天线RFID阅读器来定位RFID标签的解决方案不同，我们的方法只需要一个紧凑便携的单天线阅读器。拟议的工作将在商品RFID硬件和标签上全面实施和评估;该解决方案开辟了一系列丰富的应用。考虑像脑电图（EEG）这样的医疗测试，它可以变得真正的“可穿戴”，头部的电极可以自动定位，而不需要医生耗时的手动测量。或者考虑智能纺织品，它现在可以作为基于手势的界面，跟踪用户相对于手持设备的移动。提出的研究提出了三个贡献：（1）它提出了一种新的方法来解开从RFID标签到单天线RFID阅读器的不同路径的无线信号-定位研究中的一个关键挑战。它实现了这一点，而不依赖于笨重的，在过去的文献中使用的多天线阵列。它的核心思想是利用来自RFID标签组的信号来分离沿着不同路径的无线信号分量。(2)它研究了一种解决方案，以定位RFID标签相对于其他标签的位置是已知的。它试图使用一种算法来做到这一点，该算法利用感兴趣的标签和位置已知的相邻标签所经历的无线信号路径之间的相似性。(3)它完全集成了系统，以针对两个应用：i）可穿戴EEG系统，其使用附接到电极的RFID标签来跟踪头部上的电极。这消除了医生在进行测试之前进行繁琐的手动测量的需要，使EEG真正成为便携式。ii）具有嵌入式RFID标签的智能织物，所述嵌入式RFID标签由移动终端跟踪以跟踪用户运动，用于连续健身监测和创建基于手势的用户界面。

项目成果

Pushing the Range Limits of Commercial Passive RFIDs

• 发表时间: 2019
• 作者: Jingxian Wang;Junbo Zhang;R. Saha;Haojian Jin;Swarun Kumar