IEEE journal of radio frequency identification最新文献

News From CRFID Meetings Guest Editorial of the Special Issue on RFID 2023, SpliTech 2023, and IEEE RFID-TA 2023 CRFID 会议新闻 RFID 2023、SpliTech 2023 和 IEEE RFID-TA 2023 特刊特邀编辑

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-11-11 DOI: 10.1109/JRFID.2024.3486488

Luca Catarinucci;Ultan Mc Carthy;Diego Masotti;Simon Hemour

引用次数: 0

IoT-Based Integrated Sensing and Logging Solution for Cold Chain Monitoring Applications 基于物联网的冷链监控应用综合传感和记录解决方案

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-11-06 DOI: 10.1109/JRFID.2024.3488534

Lalit Kumar Baghel;Radhika Raina;Suman Kumar;Luca Catarinucci

{"title":"IoT-Based Integrated Sensing and Logging Solution for Cold Chain Monitoring Applications","authors":"Lalit Kumar Baghel;Radhika Raina;Suman Kumar;Luca Catarinucci","doi":"10.1109/JRFID.2024.3488534","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3488534","url":null,"abstract":"Effective cold chain management is critical across various sectors to ensure the integrity of temperature-sensitive goods, ranging from pharmaceuticals to perishable produce. A key challenge within this domain is maintaining items within their required temperature range, typically between 2°C to 8°C, to prevent spoilage or loss of effectiveness. This paper introduces a cost-effective, integrated solution that combines sensors, controllers, and memory into a compact, power-efficient, and low-cost commercial Bluetooth-based temperature & humidity data logger. The proposed solution is particularly useful not only in safeguarding food and pharmaceuticals but also plays a crucial role in the specific context of vaccine storage, such as those for COVID-19, which demands rigorous temperature adherence to ensure efficacy during storage and transportation. Unlike existing solutions, the proposed solution is equipped with interactive algorithms that monitor and record real-time temperature & humidity data throughout the distribution chain. It features a groundbreaking seamless data logging capability, allowing for wireless data retrieval via Bluetooth-enabled devices such as mobile phones, computers, or laptops. The development and testing of the proposed solution have been conducted in our laboratory, ensuring end-to-end performance and efficiency that meet the stringent standards set by health organizations, including the World Health Organization (WHO). A comprehensive comparative analysis further validates the proposed design’s accuracy, cost-effectiveness, and power efficiency, demonstrating its potential to enhance cold chain management practices universally.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"837-846"},"PeriodicalIF":2.3,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Low-Cost Drone Detection and Classification Using Convolutional Neural Networks in Low SNR Environments 在低信噪比环境中使用卷积神经网络进行稳健的低成本无人机探测和分类

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-10-28 DOI: 10.1109/JRFID.2024.3487303

Stefan Glüge;Matthias Nyfeler;Ahmad Aghaebrahimian;Nicola Ramagnano;Christof Schüpbach

{"title":"Robust Low-Cost Drone Detection and Classification Using Convolutional Neural Networks in Low SNR Environments","authors":"Stefan Glüge;Matthias Nyfeler;Ahmad Aghaebrahimian;Nicola Ramagnano;Christof Schüpbach","doi":"10.1109/JRFID.2024.3487303","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3487303","url":null,"abstract":"The proliferation of drones, or unmanned aerial vehicles (UAVs), has raised significant safety concerns due to their potential misuse in activities such as espionage, smuggling, and infrastructure disruption. This paper addresses the critical need for effective drone detection and classification systems that operate independently of UAV cooperation. We evaluate various convolutional neural networks (CNNs) for their ability to detect and classify drones using spectrogram data derived from consecutive Fourier transforms of signal components. The focus is on model robustness in low signal-to-noise ratio (SNR) environments, which is critical for real-world applications. A comprehensive dataset is provided to support future model development. In addition, we demonstrate a low-cost drone detection system using a standard computer, software-defined radio (SDR) and antenna, validated through real-world field testing. On our development dataset, all models consistently achieved an average balanced classification accuracy of \u0000<inline-formula> <tex-math>$ge 85%$ </tex-math></inline-formula>\u0000 at SNR \u0000<inline-formula> <tex-math>$gt -12$ </tex-math></inline-formula>\u0000dB. In the field test, these models achieved an average balance accuracy of >80%, depending on transmitter distance and antenna direction. Our contributions include: a publicly available dataset for model development, a comparative analysis of CNN for drone detection under low SNR conditions, and the deployment and field evaluation of a practical, low-cost detection system.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"821-830"},"PeriodicalIF":2.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10737118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Overview of RFID Applications Utilizing Neural Networks 利用神经网络的 RFID 应用概述

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-10-18 DOI: 10.1109/JRFID.2024.3483197

Barrett D. Durtschi;Andrew M. Chrysler

{"title":"Overview of RFID Applications Utilizing Neural Networks","authors":"Barrett D. Durtschi;Andrew M. Chrysler","doi":"10.1109/JRFID.2024.3483197","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3483197","url":null,"abstract":"As Radio Frequency Identification (RFID) methods continue to evolve to higher levels of complexity, one form of machine learning is making its appearance. The use of Neural Networks (NN) in the RFID field is steadily increasing, and in the fields of localization and activity recognition, promising results are being shown from a variety of research. RFID applications fall primarily under two types of problems including regression and classification. We analyze RIFD localization techniques which fall under regression, and activity recognition which falls under classification. Many works don’t classify themselves as activity recognition methods, but because they fall under the classification category, we still consider them as activity recognition techniques. This research overviews the Neural Network models in the localization field based on whether they can perform independently of the environment in which they were tested. For activity recognition and accessory fields, the major methods involve tag-based and tag-free approaches. After the models are surveyed, a comparison study is given to examine what may be the cause for increased accuracy between different Neural Network models.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"801-810"},"PeriodicalIF":2.3,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A 920-MHz, 160-μW, 25-dB Gain Negative Resistance Reflection Amplifier for BPSK Modulation RFID Tag 用于 BPSK 调制 RFID 标签的 920MHz、160μW、25dB 增益负阻反射放大器

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-10-16 DOI: 10.1109/JRFID.2024.3481423

Takahiro Tsuji;Yoshiki Miyazaki;Tadashi Maeda

引用次数: 0

A Fully-Passive Frequency Diverse Lens-Enabled mmID for Precise Ranging and 2-Axis Orientation Detection in Next-Generation IoT and Cyberphysical Systems 用于下一代物联网和网络物理系统中精确测量和双轴方向检测的全被动式多频透镜 mmID

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-10-10 DOI: 10.1109/JRFID.2024.3477919

Marvin Joshi;Charles A. Lynch;Kexin Hu;Genaro Soto-Valle;Manos M. Tentzeris

{"title":"A Fully-Passive Frequency Diverse Lens-Enabled mmID for Precise Ranging and 2-Axis Orientation Detection in Next-Generation IoT and Cyberphysical Systems","authors":"Marvin Joshi;Charles A. Lynch;Kexin Hu;Genaro Soto-Valle;Manos M. Tentzeris","doi":"10.1109/JRFID.2024.3477919","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3477919","url":null,"abstract":"The rise and progression of the Internet of Things (IoT) have reshaped how devices connect and share information, leading to more intelligent and interconnected settings. In this realm, the incorporation of self-sustaining millimeter-wave Identification (mmID) devices present a compelling opportunity to elevate IoT implementations, especially concerning accurate positioning and monitoring capabilities. In this work, the authors introduce a novel lens-enabled passive mmID tailored for highly accurate localization and precise 2-axis orientation detection. Equipped with a frequency diverse pixel antenna array and integrated with a low-loss 3D lens for improved performance, the mmID demonstrates a peak monostatic RCS of −29.2 dBsm with a −10 dB angular coverage of ±55° across all cuts, translating to a solid angle coverage of 2.679 sr about boresight. A theoretical link budget analysis is provided for the lens-based mmID, projecting a maximum reading range of 868 m when utilizing the maximum allotted 75 dBm EIRP for 5G/mmWave frequencies. Employing a proof-of-concept (PoC) reader with 30 dBm EIRP, the proposed system demonstrates highly accurate localization, with a mean error of <2 cm at distances up to 45 m, and utilizes sensitive phase information to achieve an average phase-based ranging error within 1 mm across distances up to 20 m. Additionally, a novel signal processing methodology employing multi-output Classification Convolutional Neural Networks (CNN) is introduced to accurately discern the 2-axis orientation of the mmID, resulting in a mean error of <5° at ranges up to 30 m. By offering superior precision and versatility, the passive mmID solution emerges as a promising advancement for next-generation 5G/mmWave Cyber-Physical Systems (CPS) and IoT applications.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"788-800"},"PeriodicalIF":2.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142450982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Compact Slot-Based Bi-Directional UHF RFID Reader Antenna for Far-Field Applications 用于远场应用的紧凑型槽式双向 UHF RFID 阅读器天线

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-09-10 DOI: 10.1109/JRFID.2024.3457691

Amit Birwal;Akash Shakya;Saurav;Shalini Kashyap;Kamlesh Patel

{"title":"A Compact Slot-Based Bi-Directional UHF RFID Reader Antenna for Far-Field Applications","authors":"Amit Birwal;Akash Shakya;Saurav;Shalini Kashyap;Kamlesh Patel","doi":"10.1109/JRFID.2024.3457691","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3457691","url":null,"abstract":"This research introduces a novel circularly polarized compact antenna designed for universal ultrahigh-frequency (UHF) radio-frequency identification (RFID) handheld readers for Bi-directional RFID Far-field Applications. The antenna features a microstrip feed positioned at the center opposite a slot-based square ground. The ground plane is perturbed to include a thin horizontal and vertical stub on the left side, along with a thick rectangular slot at the right side of the square ground plane to achieve circular polarization. The simulated antenna provides a 3-dB axial ratio bandwidth (ARBW) of 42 MHz (831–873 MHz), a 10 dB impedance bandwidth of 15% (814–945 MHz), and a peak gain of 5.0 dBi. The antenna is fabricated on both layers of an affordable FR4 substrate, measuring \u0000<inline-formula> <tex-math>$81times 81times 1.6~{mathrm { mm}}^{3}$ </tex-math></inline-formula>\u0000 and its measurement results are in close agreement with simulated. The application of this antenna is made with a commercial UHF RFID reader module. The obtained read range and field of view confirm that this proposed antenna is a promising option for compact universal UHF RFID handheld reader applications and other Internet of Things (IoT) based applications.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"761-769"},"PeriodicalIF":2.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extending Near Field Communication Range for Ultra-Dense Internet of Things 为超密集物联网扩展近场通信范围

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-09-04 DOI: 10.1109/JRFID.2024.3453770

Omar Ansari;Hongzhi Guo

{"title":"Extending Near Field Communication Range for Ultra-Dense Internet of Things","authors":"Omar Ansari;Hongzhi Guo","doi":"10.1109/JRFID.2024.3453770","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3453770","url":null,"abstract":"The advent of 6G wireless systems promises a digital world that blends physical and virtual elements, revolutionizing our interaction with the physical environment. A critical step towards this digital world is the creation of digital twins of physical systems and objects. The Internet of Things (IoT) plays an important role in connecting and monitoring these physical entities. However, connecting all objects in our daily life is challenging due to high density and large number of devices. Near Field Communication (NFC), utilizing High Frequency (HF) band signals, emerges as a promising solution. NFC has a short communication range and high penetration efficiency, with a reliable wireless channel that does not compete for spectrum with typical cellular and local area networks. Nevertheless, its extremely short range limits its use in autonomous IoT applications. This paper explores two techniques to extend NFC’s communication range and reliability: the use of high-quality factor transmit/receive coils and high-quality factor relay coils. Additionally, the effect of tag coil coupling in a multi-tag IoT environment is examined. Analytical models are developed to evaluate these approaches, and the results are validated using COMSOL Multiphysics. The findings demonstrate a significant increase in NFC’s communication range, i.e., up to 0.9 – 1.3 m for 1 – 10 W transmit power, making it suitable for ultra-dense battery-free IoT operations.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"770-779"},"PeriodicalIF":2.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large Language Model-Powered Digital Traffic Engineers: The Framework and Case Studies 大型语言模型驱动的数字交通工程师：框架与案例研究

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-08-30 DOI: 10.1109/JRFID.2024.3452473

Xingyuan Dai;Yiqing Tang;Yuanyuan Chen;Xiqiao Zhang;Yisheng Lv

引用次数: 0

Passive and Battery-Free RFID-Based Wireless Healthcare and Medical Devices: A Review 无源和无电池 RFID 无线保健和医疗设备：综述

IF 2.3

IEEE journal of radio frequency identification Pub Date : 2024-08-28 DOI: 10.1109/JRFID.2024.3451230

Sadeque Reza Khan;Anne L. Bernassau;Marc P. Y. Desmulliez

{"title":"Passive and Battery-Free RFID-Based Wireless Healthcare and Medical Devices: A Review","authors":"Sadeque Reza Khan;Anne L. Bernassau;Marc P. Y. Desmulliez","doi":"10.1109/JRFID.2024.3451230","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3451230","url":null,"abstract":"Passive radio-frequency identification (RFID) technology has recently been applied to many battery-free wireless medical and healthcare (WMH) applications including wearable and implantable medical devices. The presence of the human body near RFID devices creates, however, several challenges in terms of design, fabrication, and testing of such WMH devices. The use of comparatively unsecured wireless links enabled by RFID communication may also jeopardize patient’s privacy as well as raise ethical concerns. With these factors in mind, this article provides a systematic review spanning two decades of the wide range of passive RFID applications in medical and healthcare devices based on the classification of RFID frequency bands. The strengths and limitations of these techniques are benchmarked against each other using performance metrics such as communication distance, tissue safety, size of the devices, as well as patient’s privacy and ethical implications. The article concludes by discussing the future opportunities and challenges raised by passive RFID for battery-free WMH devices. This comprehensive literature review aims to become a point of reference for experts and non-experts in the field.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"8 ","pages":"724-742"},"PeriodicalIF":2.3,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142152079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0