教学课程资源库 更多>>

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： Indoor spatial layout optimization   living behaviours   nursing homes   RFID   older adults  

摘要： Due to the increasingly ageing population throughout the world, the demand for nursing homes has soared. However, without adequate consideration of older adults' physical and mental characteristics, the indoor spatial layouts of most nursing homes fail to match the residents' special living behaviours and needs. This study thus sought to optimize the indoor spatial layout of nursing homes, using the data of older adults' real-time living behaviours in a nursing home, which were collected by radio frequency identification (RFID) technology. The genetic algorithm was adopted to make the indoor spaces match the residents' specific needs. The results indicated that the overall optimal indoor spatial layout could be obtained by exchanging functions of the recreation room and a suite and leaving other functions assigned to their original spaces. Older adults' living behaviours on different floors and bedroom types could affect the optimal spatial layout results. The location of the elevator hardly affected spatial layout optimization results. The results of this study are expected to provide suggestions for both architects and management staff, informing their understanding of older adults' behaviours and helping them optimize indoor spatial layouts based on the residents' behaviours and needs, improving residents' quality of life in nursing homes.

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： RFID   Reader antenna   Microstrip structure   Sequential phase feed   Circular polarization  

摘要： A wideband, circularly polarized (CP) reader antenna is presented for 2.45 GHz RFID systems. To achieve circular polarization, the antenna features a circular radiating patch on the top layer, fed by a sequential phase feed network located on the bottom layer. An air gap is introduced between the two layers to minimize dielectric loss, thereby enhancing directivity and radiation efficiency, which in turn increases overall gain. Cylindrical copper wires passing through the air gap connect the bottom feed network to the top patch layer. By implementing incremental phase variations across the four outputs of the feed network, the antenna achieves a-10 dB impedance bandwidth of 650 MHz (2.02-2.67 GHz) and a circular polarization axial ratio (CP AR) bandwidth of 150 MHz (2.366-2.527 GHz). The antenna exhibits a peak gain of 8.4 dBiC and maintains a symmetric radiation pattern at 2.45 GHz. The physical dimensions of the antenna are 70 x 70 x 13.2 mm3. The design provides a 3 dB axial ratio beamwidth of 91 degrees and a half-power beamwidth of 63.9 degrees in the X-Z plane and 64 degrees in the Y-Z plane. An equivalent circuit analysis is performed to better estimate the antenna's performance. The design is experimentally verified and compared with simulation results. The proposed antenna is particularly suitable for mobile RFID applications operating at 2.45 GHz, such as inventory management, asset tracking, access control, electronic toll collection, and medication distribution.

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.

关键词： Radio frequency identification (RFID)  

摘要： Radio Frequency Identification (RFID) is a widely used technology for identifying and locating objects equipped with low-cost RFID transponders (tags). UHF (Ultra High Frequency) RFID operates in frequency bands around 900 MHz and supports communication distances of up to 15 m between the reader and the tag. Reliable motion detection is therefore a highly relevant feature in modern logistics – for example, to determine whether a tag is actually placed on a conveyor belt or merely in its vicinity. A promising approach for accurate motion detection is the use of the Doppler effect. Some state-of-the-art UHF-RFID readers already support Doppler shift measurements. However, their measurement accuracy is insufficient for many applications. In this paper, we propose an optimized method for the precise Doppler shift estimation using existing RFID systems – an essential step toward enabling RFID-based motion detection in future logistics. Further, we also derive the theoretical bounds for Doppler-based motion detection in UHF-RFID systems based on the Cramer-Rao Lower Bound. These bounds analyze the influence of tag signal strength, signal duration, and the intervals between multiple tag replies on the performance of motion detection and speed estimation algorithms. In addition, we establish theoretical limits that account for hardware constraints in current UHF-RFID readers. The results of this work provide valuable insights into the limitations of Doppler-based motion detection and support system-level performance optimization. They enable prediction of achievable performance based on reader noise figure, aiding in the design and tuning of RFID systems. Copyright © 2025, The Authors. All rights reserved.

关键词： RFID   beehive   simulation   modelling   propagation   measurements  

摘要： The last few years have seen the introduction of new technologies in beekeeping, including RFID. Using readers and miniaturized tags, RFID systems work in the UHF frequency band, allowing reading distances to reach tens of centimeters. This work analyzes the propagation inside a full beehive, composed of 10 frames supported by a wooden structure. Each frame contains a layer of beeswax supported by metallic wires. The methodology employed involves measuring Received Signal Strength Indicator (RSSI) values and simulating the environment using CST Studio. The results show that tags located along the frame's wires have more coverage than tags in the center positions, revealing coupling of the microtag antenna with the wire. Furthermore, obtaining coverage through simulations represents a more restrictive approach than through measurements. Frame selectivity is also observed, as most of the coverage is found within the three frames closest to the reader antenna. This result shows that RFID systems can find application in the identification and location of the queen bee in a hive.

关键词： deep neural networks   Levenberg-Marquardt algorithm   high-salinity wastewater   real-time monitoring   dielectric constant   sodium chloride solution   RFID tags   Cole-Cole model   slit cylinder capacitor model   wireless frequency   flow rate   parameter estimation  

摘要： Accurate parameter estimation is essential for effective monitoring and treatment of high-salinity industrial wastewater. Traditional methods such as spectroscopy, ion chromatography, and electrochemical analysis offer high sensitivity but are often complex, costly, and unsuitable for real-time monitoring. This research integrates Deep Neural Networks (DNNs) with the Levenberg-Marquardt (LM) algorithm to develop an advanced RFID-based sensing system for real-time monitoring of sodium chloride solutions in wastewater. The DNN extracts essential features from raw data, while the LM algorithm optimizes parameter estimation for enhanced precision and stability. Experimental results show that the dielectric constant sample variance at various flow rates under wireless frequency is 0.08509, while the sample total variance is 0.06807, both below 0.1. Additionally, the sample standard deviation and total standard deviation are both below 0.3, at 0.26090 and 0.29169, respectively. These findings confirm that the proposed system is robust against flow rate variations, ensuring accurate, real-time monitoring and supporting sustainable industrial practices.