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关键词： RFID-based monitoring   Respiration monitoring   Heart rate monitoring   Driving scenarios  

摘要： The health status of drivers directly affects traffic safety, particularly as fatigue or sudden illness can lead to serious traffic accidents. Existing monitoring methods are challenging to apply effectively in complex in-vehicle environments. This paper presents VeHealth, a wireless in-vehicle monitoring system based on Commercial Off-The-Shelf RFID devices that can continuously monitor respiration rate (RR) and heart rate (HR) in real driving scenarios. The system collects amplitude and phase information from RFID signals through tags installed on the chest, abdomen, and inside the vehicle, utilizing a BPNN-Optuna model for RR and HR predictions. Results based on the experimental data of 14 volunteers show that VeHealth achieves prediction accuracies of 95.8%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$95.8\%$$\end{document} and 97.3%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$97.3\%$$\end{document} for RR and HR, respectively. By designing an optimal RFID antenna layout, the monitoring range is improved, minimizing environmental noise and vehicle interference, thereby validating the system's effectiveness and reliability under various driving conditions.

关键词： 5G/6G network   network performance   radiofrequency identification   resource optimization  

摘要： In the rapidly evolving landscape of 5G/6G networks, efficient resource optimization is critical to addressing the escalating demands for high-speed, low-latency, and energy-efficient communication. This study explores the integration of Radio Frequency Identification (RFID) technology as a novel approach to enhance resource management in 5G networks. The motivation behind this research lies in overcoming persistent challenges such as spectrum congestion, high latency, and inefficient load balancing, which impede the performance of traditional resource allocation methods. To achieve this, RFID tags were embedded in critical network components, including user devices, base stations, and Internet of Things (IoT) nodes, enabling the collection of real-time data on device status, location, and resource utilization. RFID readers strategically placed across the network continuously captured this data, which was processed by a centralized controller using a custom-designed optimization algorithm. This algorithm dynamically managed key network resources, including spectrum allocation, load balancing, and energy consumption, ensuring efficient operation under varying network conditions. Simulations were conducted to evaluate the performance of the RFID-based model against traditional 4G dynamic resource allocation techniques. The results demonstrated substantial improvements in key performance metrics. The proposed system achieved a 25% increase in spectrum utilization, a 30% reduction in average latency, a 15% boost in network throughput, and a 20% decrease in overall energy consumption. These gains highlight the effectiveness of the RFID-based optimization model in meeting the stringent performance requirements of 5G networks, particularly in high-density deployments. This study provides a scalable, cost-effective solution for optimizing resource management in 5G and lays the groundwork for future advancements in 6G networks. By leveraging real-time data and intelligent re

关键词： Complex conjugate impedance match   Loop antenna   Metallic circular tag   Radio frequency identification(RFID)   Circular polarization  

摘要： In this paper layout of long detection range radio frequency identification tag antenna mountable on metallic surface is presented. This tag antenna layout consists of two non-connected L-shaped load bars and two sectorial patches electrically connected through seven pairs of vias and conducting rear-plane to form a loop antenna. This proposed tag antenna can be tuned in wide range for impedance matching and introduces circular polarization. The tag antenna characteristics are also measured on metal plate. The results show that maximum detection range of the specimen, placed on metallic plate found to be 8.4 ms. The measured 10 dB bandwidth of circular tag antenna is 17 MHz (906-923 MHz) with simulated 3 dB axial ratio bandwidth of 13 MHz. This circular tag antenna is simulated with 4 W EIRP reader.

关键词： Steel-concrete interface   Relative humidity   RFID   MEMS sensor   Reinforcement spacer  

摘要： Moisture at the steel-concrete interface (SCI) can influence the durability of reinforced concrete but a fundamental understanding of its effects on corrosion initiation and propagation remains inconclusive. This is partly due to a lack of reliable, non-destructive monitoring techniques. This study introduces a novel approach leveraging 3D-printed reinforcement spacers with embedded RFID-MEMS sensors to enable in situ, real-time relative humidity monitoring at the SCI. Concrete specimens with different water-to-cement ratios (0.40, 0.55) and curing ages (3, 14 days) were exposed to 50 degrees C and 65 % RH, 21 degrees C to produce varying degrees of porosity and moisture content. The results show that precise measurements with a maximum difference of +/- 2 % can be obtained for exposure humidity up to 90 % RH. However, a reduction in precision occurred above 93 % RH due to condensation effects. Crucially, this work demonstrates the first successful integration of RFID-MEMS sensors in 3D-printed spacers to quantify SCI moisture states non-destructively, providing actionable insights for corrosion risk assessment tailored to concrete composition and environmental exposure.

关键词： Interference   Feature extraction   Radiofrequency identification   Authentication   Accuracy   Security   Logic gates   Training   Physiology   Legged locomotion   Gait recognition   RFID   continuous user identification   tags  

摘要： Continuous user identification could facilitate large-scale identity-based services, potentially including access control, security management, personalized services, and beyond. Although current RFID-based user identification systems demonstrate effective performance in single-user scenarios, they exhibit a lack of robustness and accuracy when extended to multi-user environments. In this paper, we propose RF-UI, a low-cost continuous user identification system that can tolerate different interference factors (e.g., appearance changes, inconsistent walking paths). The intuition underlying our design is that when multiple users traverse the radio gate sequentially, the received signal is dominated by the user traversing the radio gate. We develop an algorithm that utilizes phase energy fluctuation to separate signals from different users and extract valid gait-related patterns by applying neighborhood energy sliding windows. Then, we construct a Joint Similarity Matrix (JSM) for characterizing gait features that are robust against various interference factors. Finally, RF-UI achieves cost-effective data augmentation through the deployment of only a few additional tags. Extensive experiments show that RF-UI achieved an accuracy of 94% under various interference factors and maintained a high accuracy of 92.8% in continuous user identification.

关键词： Wireless communication   Wireless sensor networks   Location awareness   Imaging   Tomography   Noise   Image reconstruction   Adaptation models   Databases   Vectors   Density-based spatial clustering of applications with noise (DBSCAN)   device-free localization (DFL)   multi-target localization   passive UHF RFID   radio tomographic imaging (RTI)  

摘要： Device-free localization (DFL) is a promising technique for localizing targets without any auxiliary devices. Passive ultra high frequency radio frequency identification (pUHF RFID) based radio tomographic imaging (RTI) emerges as a particularly favorable DFL approach due to its inherent advantages. However, accurately localizing multiple targets remains a challenge for it. To address the challenge, we propose a novel unsupervised link analysis based movement superposition RTI (ULA-MSRTI), including movement superposition RTI (MSRTI) model and the unsupervised link analysis (ULA) scheme. MSRTI models the influence of target movement on wireless signals at every moment. Then, we design the ULA scheme to determine received signal strength (RSS) variations of target-affected links required for MSRTI. Firstly, the scheme adopts statistical analysis to remove wireless links that are mainly affected by noise. Then, we design an adaptive selection algorithm based on density-based spatial clustering of applications with noise to eliminate wireless links affected by burst signals and self-environmental multipath. After that, the scheme matches RSS variations of remaining links with the single-target database to recover RSS variations of target-affected links at one moment. Finally, we input recovered RSS variations into MSRTI to obtain the locations of multiple targets. The experiment shows that ULA-MSRTI's performance improves by an average of over 14.6% compared to other methods, and ULA-MSRTI is the insensitive to the locations of multiple targets.

关键词： Aerosol Jet Printing (AJP)   Critical Temperature Indicator (CTI)   intelligent label   Polyaniline (PANI) ink formulation   Radio Frequency Identification (RFID)  

摘要： Temperature plays a crucial role in influencing the quality of a package, especially in the cold supply chain. By using intelligent packaging to detect the exposure to heat, the status of these products can be retrieved. Critical Temperature Indicator (CTI) and Radio Frequency Identification (RFID) technology are integrated to monitor and communicate the package status by combined visual and electronic detection. Hereby, this work presents the development of an intelligent label integrating a polyaniline (PANI)-based sensor and a RFID antenna, both fabricated using Aerosol Jet Printing (AJP). The label is specifically made of a CTI which changes color upon an external trigger, and an RFID antenna that allows verifying the status of the device electronically;both components are printed on a paper label toward the development of an "intelligent label". The future applications use temperature as the triggering mechanism. The work primarily focuses on the design, fabrication, and testing of this device as a proof-of-concept. Particularly, the recipe of the own-developed PANI, the establishment of best printing strategies, and the identification of the intelligent label performance are described. By emphasizing manufacturing strategies, this work provides a foundation for scalable, printed devices tailored for smart monitoring applications.

关键词： Antennas   Couplings   Antenna measurements   Radiofrequency identification   Metals   Training   Microstrip antennas   Data mining   Artificial intelligence   Antenna theory   Tag antenna   metal-tolerant   characteristic mode analysis (CMA)   broadband  

摘要： In this letter, a broadband metal-tolerant tag antenna for ultrahigh frequency (UHF) radio frequency identification (RFID) systems is presented. In the antenna design, three coupling patches are loaded on the top, and both sides of the feeding patch are separated by long coupling gaps. Two characteristic modes of the tag antenna are identified by employing characteristic mode analysis (CMA) to achieve broadband performance. Furthermore, an equivalent circuit model (ECM) for the antenna is established. The measured results show that its operating bandwidth is 51 MHz (888 MHz to 939 MHz). When mounted on a 200 mm x 200 mm metal plate, the tag antenna achieves a maximum reading distance of approximately 10.4 m at 915 MHz and maintains a reading distance of at least 7.1 m throughout the entire US UHF band (902 MHz to 928 MHz). Also, the antenna mounted on a 300 mm x 300 mm metal plate is measured and demonstrated.

关键词： location measurement   RFID multi-tag   image denoising   deep learning  

摘要： Most of the traditional radio frequency identification (RFID) multi-tag realizes identification by using electromagnetic communication. However, with the increasing number of RFID multi-tags and the increasing complexity of electromagnetic interference in RFID application environments, only using traditional electromagnetic approach to realize RFID multi-tag localization cannot meet RFID application requirements. Therefore, in this paper, a novel Swin Transformer fusing residual shrinkage network and convolution integrated in U-Shaped network (STRSC-UNet) image denoising method for computer vision enhanced RFID multi-tag measurement and localization is proposed. Firstly, an RFID multi-tag localization system embedded with computer vision is designed for RFID tag image acquisition. Secondly, a novel STRSC-UNet denoising method, which introduces the Transformer method in high-level vision into the field of low-level vision, is proposed for tag image denoising. Subsequently, based on the denoised images, scale-invariant feature transform matching algorithm is used for tag recognition to obtain homonymous image points. Finally, the spatial forward intersection method is used to realize RFID multi-tag localization. Four different baseline models are used to compare with the proposed denoising model. The experimental results show that compared with other benchmark methods, the image quality of STRSC-UNet is improved by at least 0.17 dB. Further localization experimental results demonstrate that, by using the proposed STRSC-UNet denoising method, the localization accuracy of RFID multi-tag system can be effectively enhanced.

关键词： multi-antenna   positioning algorithm   bolt loosening   fault location   UHF RFID reader   IoT  

摘要： Bolt connections are the most common form of connection in hydroelectric generator units. The manhole of spiral case in hydroelectric generator unit is highly susceptible to loosening and fatigue of the bolts due to long-term exposure to hydraulic vibrations, which can lead to bolt breakage and pose significant safety risks. To address the issue of bolt loosening fault localization in the manhole of spiral case in hydroelectric generator unit, a passive bolt loosening fault localization system based on the Internet of Things (IoT) and multi-antenna radio frequency identification (RFID) is designed. First, a tag identification model for multi-antenna RFID is developed, and an optimization control scheme for the multi-antenna system is proposed. Second, an improved virtual reference elimination (VIRE) algorithm for bolt loosening fault localization is proposed, integrating cubic spline interpolation and dynamic threshold (Th). The positioning accuracy of the algorithm is verified by modifying simulation parameters. Finally, a passive bolt loosening fault localization hardware system using multi-antenna RFID is constructed, and upper and lower machine testing programs are developed to achieve precise fault localization of the bolt loosening using the multi-antenna system. Experimental results demonstrate that the IoT-based multi-antenna RFID passive bolt loosening fault localization system can achieve rapid and stable detection of bolt loosening faults. The positioning accuracy of the proposed improved VIRE algorithm is enhanced by 99.15% and 30.95% compared to the LANDMARC and VIRE algorithms, respectively. This system offers a novel approach for the localization of bolt loosening faults in the manhole of spiral case of hydroelectric generator unit under complex operating conditions.