NeTS: Medium: New Technologies for Next-generation Infrastructural Tagged Systems

NeTS：中：下一代基础设施标记系统的新技术

• 批准号: 1409797
• 负责人: Shigang Chen
• 金额: $ 91.49万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1409797&HistoricalAwards=false
• 关键词: NeTS; Medium; New; Technologies; Next

Barcode systems have brought a revolution in the retail industry by speeding up the checkout process with a laser scanner that reads the product ID from barcode printed on each item and retrieves its price automatically from a database. However, there is a serious limiting factor: barcodes can only be read in a very close range with direct sight, which makes it impossible to batch-access objects that are piled on store racks or in shopping carts. RFID (radio-frequency identification) technologies remove this limitation by integrating simple communication/storage/computation capacities in attachable tags, whose IDs can be read wirelessly over a distance, even when obstacles exist between tags and the RFID reader. Today, RFID tags are ubiquitously available in retail products, library books, debit cards, passports, driver licenses, car plates, medical devices, etc. The current application model treats tags simply as ID carriers and deals with each tag individually for the purpose of identifying the object that the tag is attached to, which may be a vehicle passing through a toll booth, a wild animal under monitoring, a luggage being transported in an airport, or a commercial product through the chain of manufacturing, assembly and shipping. Going beyond the current model, the uniqueness of this project is to change the traditional individual view to a collective view that treats universally-deployed tags together as a new wireless infrastructure, on which novel applications can be developed for large-scale automated warehouse management, cyber-physical data collection, sophisticated inventory control, and even transportation traffic monitoring on the streets of a city. Such a new wireless platform can be further enhanced by integrating miniaturized sensors into tags for real-time information collection, by exploiting the mobility of tags, by supporting security functions, etc. These developments will greatly expand not only the scope of applications but also fundamental research into the next-generation infrastructural tagged systems. The proposed research has the potential of making significant practical impact, given the wide applicability of tag technologies in industries and customer markets. Moreover, as part of the project, new educational materials will be developed to timely incorporate research results into graduate courses. The research activities include the following: First, this project makes the case that a small number of carefully-chosen tag primitives have the potential of not only solving some existing problems much more efficiently, but also handling many open problems that have not been studied before. In particular, three fundamental primitives, called logical mixmap, tag ordering and tag selection, will be thoroughly investigated with the objective of producing generic tags that are simple yet versatile in their ability to support different application needs. Second, while most prior work focuses on optimizing time efficiency, this project brings in a new dimension, application-level energy efficiency, for systems that use tags with internal power sources. The proposed research will design energy-efficient solutions and provide means to control energy-time tradeoff. Finally, should tags be pervasively deployed, people's privacy would become a serious concern. Next-generation tags will help improve the quality of people's lives, but meanwhile can reveal location if people carry them in their pockets or by their cars. To address such concerns, this project will study privacy-preserving information collection and authentication in future tagged systems. In summary, the results from this project will advance our understanding of tagged system design in terms of versatility, energy efficiency and privacy protection. The expected outcome includes a set of fundamental primitives (designs, analysis, evaluation, and implementation) that together provide optimized solutions for a large number of interesting applications.

条码系统通过激光扫描仪加速结账流程，为零售行业带来了一场革命，该扫描仪可以从打印在每件商品上的条码中读取产品 ID，并从数据库中自动检索其价格。然而，存在一个严重的限制因素：条形码只能在非常近距离的直视范围内读取，这使得无法批量访问堆放在商店货架或购物车中的物体。 RFID（射频识别）技术通过将简单的通信/存储/计算功能集成到可附加标签中，消除了这一限制，即使标签和 RFID 阅读器之间存在障碍物，也可以远距离无线读取其 ID。如今，RFID 标签在零售产品、图书馆图书、借记卡、护照、驾驶执照、车牌、医疗设备等中随处可见。当前的应用模型将标签简单地视为 ID 载体，并单独处理每个标签，以实现以下目的：识别标签所附着的物体，该物体可能是经过收费站的车辆、受到监控的野生动物、在机场运输的行李，或者是经过制造、组装和运输链的商业产品。超越当前的模式，该项目的独特之处在于将传统的个人视图转变为集体视图，将普遍部署的标签一起视为新的无线基础设施，在其上可以开发用于大规模自动化仓库管理的新颖应用程序，网络物理数据收集、复杂的库存控制，甚至城市街道上的交通流量监控。这种新的无线平台可以通过将小型传感器集成到标签中以进行实时信息收集、利用标签的移动性、支持安全功能等来进一步增强。这些发展不仅将极大地扩展应用范围，而且将从根本上扩展。研究下一代基础设施标记系统。鉴于标签技术在行业和客户市场中的广泛适用性，拟议的研究有可能产生重大的实际影响。此外，作为该项目的一部分，将开发新的教材，以便及时将研究成果纳入研究生课程。研究活动包括以下内容：首先，该项目证明少量精心选择的标签原语不仅有潜力更有效地解决一些现有问题，而且可以处理许多以前没有研究过的开放问题。特别是，将彻底研究三个基本原语，即逻辑混合映射、标签排序和标签选择，目的是生成简单但通用的通用标签，以支持不同的应用程序需求。其次，虽然大多数先前的工作都集中在优化时间效率，但该项目为使用带有内部电源的标签的系统带来了一个新的维度，即应用程序级能源效率。拟议的研究将设计节能解决方案并提供控制能源时间权衡的方法。最后，如果标签被普遍部署，人们的隐私将成为一个严重的问题。下一代标签将有助于改善人们的生活质量，但同时如果人们将它们放在口袋里或放在车里，它也可以泄露位置。为了解决这些问题，该项目将研究未来标记系统中的隐私保护信息收集和身份验证。总之，该项目的结果将增进我们对标签系统设计在多功能性、能源效率和隐私保护方面的理解。预期结果包括一组基本原语（设计、分析、评估和实现），它们共同为大量有趣的应用程序提供优化的解决方案。

项目成果

Smart Cities on Wheels: A Newly Emerging Vehicular Cognitive Capability Harvesting Network for Data Transportation

车轮上的智慧城市：新兴的数据传输车辆认知能力收集网络

• DOI: 10.1109/mwc.2017.1700151
• 发表时间: 2017
• 期刊: IEEE Wireless Communications
• 影响因子: 12.9
• 作者: Haichuan Ding;Chi Zhang;Ying Cai;Yuguang Fang
• 通讯作者: Yuguang Fang

Missing-Tag Detection With Unknown Tags

未知标签的缺失标签检测

• DOI: 10.1109/tnet.2020.2984706
• 发表时间: 2020
• 期刊: IEEE/ACM Transactions on Networking
• 作者: Zhang, Youlin;Chen, Shigang;Zhou, You;Fang, Yuguang
• 通讯作者: Fang, Yuguang

A UHF RFID-Based System for Children Tracking

• DOI: 10.1109/jiot.2018.2841809
• 发表时间: 2018-12-01
• 期刊: IEEE INTERNET OF THINGS JOURNAL
• 影响因子: 10.6
• 作者: Pang, Yawei;Ding, Haichuan;Chen, Shigang
• 通讯作者: Chen, Shigang

Access Point Recruitment in a Vehicular Cognitive Capability Harvesting Network: How Much Data Can Be Uploaded?

• DOI: 10.1109/tvt.2018.2803762
• 发表时间: 2018-02
• 期刊: IEEE Transactions on Vehicular Technology
• 影响因子: 6.8
• 作者: Haichuan Ding;Chi Zhang;B. Lorenzo;Yuguang Fang

Monitoring Bodily Oscillation With RFID Tags

• DOI: 10.1109/jiot.2019.2892000
• 发表时间: 2019-01
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Youlin Zhang;Shigang Chen;You Zhou;Yuguang Fang;Chen Qian