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关键词： 无芯片   RFID   手势识别   谐振结构   天线  

摘要： 手势识别是一种利用简单手势实现人机交互的技术,在虚拟现实、医疗诊断等场景中应用广泛。近年来无芯片RFID手势识别传感器以其低成本、可穿戴性以及能对目标物体进行实时监测等优势得到了人们的普遍关注。因此设计一种能独立监测手指状态的传感器,具有重要的应用价值。 本论文研究了一种对手指不同关节弯曲情况进行独立监测的传感器,对其工作原理和设计方法进行了介绍。通过对其编码单元(谐振结构)及通信单元(收发天线)的有效设计实现了手势识别。主要工作内容如下: (1)仿真了一款用于识别三指六关节的分截模型谐振结构,其由一根主传输线和三个分别位于不同手指上的分截的短截线谐振单元构成,分截间隙设计在手指一二关节连接处。谐振结构尺寸为73×71.8×1.2mm3,工作频段为3-6GHZ,六个谐振频率与手指关节弯曲情况相关,通过判断谐振频点的出现与否实现对手指关节共27个状态的识别。 (2)设计了一款用于识别两指四关节的组合模型谐振结构,该谐振结构由一根主传输线和位于两根手指的四个短截线谐振单元构成,介质板为棉布,导电材料为铜箔。谐振结构整体尺寸为74.5×65×1.2mm3,工作频段为3-4GHz,四个短截线的谐振点分别为3.11GHz、3.355GHz、3.619GHz和3.965GHz。通过控制每根手指上两根短截线的长度以及与主传输线的间隙,完成对每根手指两关节四个状态的识别,并通过实验验证了其状态组合。 (3)设计了一对用于实测验证的共面波导超宽带缝隙天线。天线介质层为棉布,导电材料为铜箔,整体尺寸为82×80×1.1mm3,工作频段覆盖3-4GHz,具有全向辐射特性,最大增益可以达到6dBi左右,符合设计需求。 (4)设计了一对匹配谐振结构的微带超宽带单极子天线。天线为六边形贴片,介质层为棉布,导电材料为铜箔,整体尺寸为55×46×1.2mm3,工作频段覆盖3-4GHz,具有全向辐射特性,最大增益可以达到3dBi左右,达到设计预期。

关键词： Internet of things  

摘要： An autonomous parking system is the essential innovation for stress free car parking in smart cities. The efficient use of resources is a key goal of smart cities, and their integration with technology has improved productivity and dependability for urban infrastructure. In this paper, an efficient automated parking system integrating Internet of Things (IoT) and radio frequency identification (RFID) technologies is proposed. The proposed system is integrated with IoT in which the consumers can book the parking spots before arriving to the destination—drastically reducing the time taken by the consumers in searching for the parking slot. The proposed system effectively saves time for the consumers and also significantly provides solutions for all the parking-related issues faced by the management of flats, theaters, malls, hospitals, etc. In management perspective, this system will provide better use of their resources and reduce the amount of labor needed to maintain these parking lots. The automated parking system overcomes the important issue of jamming near the gates of parking spots by improving the check-in and check-out process of vehicles. The RFID tags given to the drivers reduce the time for vehicle identification as it is done automatically. The proposed system avoids long queues at the gates, unnecessary traffic jams near the gates, reduces the waiting time, and ensures security by allowing only the registered users identified through RFID tags. Thus, the proposed system will be a sophisticated system for the consumers, drivers, and a boon to mall owners and management. © 2024 by Begell House, Inc.

关键词： 物流   管理信息系统   射频识别   企业物流管理   数据分析  

摘要： 近年来,随着物流行业的迅速发展,企业对物流信息管理系统的需求也越来越高。RFID技术作为一种先进的物流管理工具,被广泛应用于企业的物流管理过程中。X企业自2016年开始推进物流管理信息系统的开发和应用,基本满足各个货站的货物处理流程的单货信息管理,但是由于X企业的市场扩张和企业发展较快,现有的物流管理信息系统不能降低人工录入的差错率和货物在运输过程中的全程跟踪记录,在发生或人为差错造成的丢失和错运的紧急情况时无法紧急处理和确定责任人。为彻底改变目前物流运输中存在的管理问题,X企业与SW公司合作成立信息科技部进行基于RFID技术的物流信息管理系统的开发与应用。该系统要求可以在外网条件下使用,做到应用功能完善、数据资源共享、用户使用方便、维护成本降低等。以提升企业物流信息管理效率。通过对RFID技术在企业物流管理中的应用进行探讨,并结合优化企业物流信息管理系统的研究,提出了一系列提升企业物流信息管理效率的措施。同时,本文还将重点探讨RFID技术在企业物流信息管理中的作用。通过本研究的结论,将为X企业物流信息管理系统的优化提供一定的参考和借鉴。 本文以X公司的物流管理现状为切入点,深入剖析了其库存管理、配送及发货流程,实现了这些环节的实时、精准和可视化分析。特别关注了运输管理和配送管理的挑战。文中详细论述了如何选择适宜的电子标签读写设备,并提出了控制系统与管理体系的一般构想。随后,以RFID技术为关键,我们设计并实施了一套创新的企业物流管理系统,该系统重塑了企业的运营流程,有效地应对了当前面临的难题。 综上所述,基于RFID技术的企业物流信息管理系统在优化企业物流信息管理方面具有重要的意义。它能够提高物流信息的透明度和准确性,实现物流过程的实时监控和问题的及时处理,同时还能够实现物流流程的自动化和智能化,提高物流运作的效率和质量。因此,进一步研究和优化基于RFID技术的企业物流信息管理系统具有重要的实践价值和应用前景。

关键词： 物联网   RFID   无源感知   人体行为识别   深度学习  

摘要： 得益于物联网的快速发展,人体行为识别技术已经在众多领域得到了广泛应用。基于无线射频识别(Radio Frequency Identification,RFID)的人体行为识别技术因其保护隐私和使用成本低等优势近年来引起了国内外学者的关注。而现有的基于RFID的人体行为识别技术中存在随意部署RFID标签、未去除采集的标签数据中存在的干扰和只考虑使用相位或接收信号强度指示(Received Signal Strength Indicator,RSSI)数据进行识别等问题,本文针对这些问题从实际的应用场景出发提出了相应解决方案。本文的主要研究内容包括: (1)为了满足纠正青少年不良坐姿的实际应用场景需求,本文提出一种基于无源RFID标签的动态坐姿识别方法。该方法从提高识别准确率的角度出发将五个无源RFID标签分别部署在用户脊柱和肩部用于采集标签的相位和RSSI数据,然后利用预处理操作去除原始数据受到的干扰,随后将相位数据和RSSI数据分别转换成更适合坐姿识别的多普勒频移数据和RSSI差值数据,最后将这些数据输入至深度残差神经网络中完成识别。实验结果表明,本文提出的坐姿识别方法对六种不良坐姿达到了99.17%的识别准确率,超过了现有的其它基于RFID的坐姿识别方法。 (2)为了满足发现老年人跌倒行为的实际应用场景需求,本文提出一种基于无源RFID标签的跌倒检测方法。该方法在高识别准确率的基础上为避免标签间的感应耦合现象只将一个无源RFID标签粘贴于用户胸部用于采集标签的相位数据,然后通过预处理模块消除原始数据中存在的干扰,紧接着将相位数据转换为更适合跌倒检测的角频率数据,最后提取用户的运动区间并利用DTW-KNN算法检测用户是否发生跌倒行为。实验结果表明,本文提出的跌倒检测方法能对包含跌倒行为在内的七种行为达到98.89%的识别准确率,超过其它用于比较的基准方法。

摘要： 随着航空货运业务的不断增长，消费者对于物流服务质量要求的不断提高，航空公司需要不断优化航空货运服务，提升客户满意度。同时，航空公司本身也亟待进一步提升科技含量，提高货运工作的经济效益。射频识别技术（Radio Frequency Identification,RFID）作为一种新型的自动识别技术，被广泛应用于航空领域，为航空业带来了新质生产力，对服务质量和经济效益都会带来显著的提升。这种技术如何更好地在航空货运领域发挥作用是一个值得思考的问题。

关键词： Magnetic coupling   coils   HF RFID   NFC   rotating magnetic field  

摘要： Benefiting from advantages such as miniaturization, lightweight design, and cost-effectiveness, 13.56 MHz High Frequency Radio Frequency Identification (HF RFID) and Near Field Communication (NFC) tags have found increasing applications across various fields like biomedical, tracking, and logistics, bringing a lot of convenience to the industries and commercials, as well as decreasing the medical and employment pressure. Nevertheless, the smaller the tag, the less likely it is to be fixed in orientation. As the detection of such tags relies on magnetic coupling, the orientation sensitivity is high, and some nulls of detection are introduced inside the considered volume of interest in practical applications. It is essential to optimize the magnetic field vectorial distribution generated by the NFC reader. This paper uses a combination of two paralleled tuned coils (RLC resonator model) in series to be the RFID/NFC reader coils. In such a system, the currents feeding the coils are in quadrature. The system is made of two-phase coils. Additionally, each coil is composed of two sub-coils placed on opposite surfaces of a cube, for the prototype of this system presented in the paper. CST simulations have been analyzed and a 3D printed cube structure with copper tapes has been realized, to validate the idea experimentally. Detection tests were performed with a commercial HF RFID reader and an ISO15693 NFC tag.

关键词： Radio frequency identification (RFID)  

摘要： Chipless Radio Frequency Identification (RFID) technology offers a cost-effective and durable alternative to chipped tags for identification and tracking applications. By eliminating the need for an integrated circuit, chipless tags are cheaper and can withstand harsher environments. This opens doors to not only track items throughout a supply chain or monitor valuable assets, but also integrate basic sensors for functionalities like environmental monitoring or smart agriculture. However, limitations in data capacity, read range, and decoding complexity currently hinder their full potential. This paper explores the application of machine learning techniques to improve the interrogation process and enhance the reliability of chipless RFID systems. The effectiveness of machine learning in optimising chipless RFID systems hinges on the richness and variety of training data. A robust dataset encompassing diverse tag characteristics, environmental factors, and reader configurations is paramount. Nevertheless, gathering real-world RFID data can be difficult. To address this, a data collection procedure has been specifically designed to gather backscattered information from the chipless tags at multiple orientations and distances. Four binary combinations of a 5-bit RFID tag based on frequency-selective surfaces operating in the 2–8 GHz range are considered for generating the database. The dataset is then used to train and validate various classification models, including support vector machine (SVM), k-nearest neighbour (k-NN), Decision Tree (DT), Naive Bayes classifier, and Logistic Regression (LR). The proposed Support Vector Machine model is able to identify the tag at a distance of up to 70 cm from the interrogator, with multiple rotational degrees of freedom. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Drug formulation   sensitivity   backscatter   RFID performance   pharmaceutical supply chain  

摘要： Radio Frequency Identification (RFID) is a burgeoning technology pivotal for optimizing intricate supply chains. Although its potential benefits in healthcare and pharmaceuticals are substantial, RFID implementation in these sectors has been slow-moving. Surprisingly, limited research has probed RFID performance on pharmaceutical products and their packaging. This study aims to explore the influence of diverse liquid drug formulations on RFID performance, utilizing a pre-optimized Ultra High Frequency (UHF) RFID tag. Five distinct drug formulations, encompassing water, saline, and lipids, were studied, alongside deionized (DI) water and empty vials as control subjects. The products were transferred to separate vials, each affixed with a pre-optimized UHF RFID tag. Performance evaluations, including Threshold Sweep, Orientation Sweep, and Population Analysis, were conducted to assess tag readability, focusing on sensitivity, backscatter, and theoretical read range. The results underscore how the composition of different pharmaceutical drug formulations significantly impact RFID tag readability in a controlled, reflection-free environment. These findings provide valuable insights for designing intelligent packaging to enhance the readability of RFID-tagged pharmaceutical products.