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关键词： Memristors  

摘要： Current RFID circuits, designed primarily for basic low-power communication and data storage, are not suitable to meet the computational needs of future AI-based IoT applications. While effective for simple identification tasks, these systems fall short in supporting advanced data processing and on-chip intelligence. Next-generation neuromorphic RFID circuits are expected to dynamically adapt based on external inputs and emulate biological neuron activity, paving the way for intelligent, low-power, and autonomous devices. This paper explores the potential of neuromorphic RFID systems driven by memristor-based architectures, leveraging ReRAM technology and crossbar arrays. ReRAM offers key advantages, including reduced energy consumption, essential for enabling local processing and real-time decision-making in intelligent RFID nodes. To demonstrate this potential, a 2W2 crossbar circuit was designed and simulated in LTspice using Bioleks memristor model. The analysis examined the circuits response to read and EPC-like inputs, state variable dynamics, and digital output behavior. Operating at microwatt-level power consumption and capable of processing sensor signals, the proposed architecture shows promise as a foundational building block for future low-power, intelligent, and autonomous RFID systems. © 2017 IEEE.

关键词： electronic label   Gaussian filter   power material storage   real-time positioning   RFID technology  

摘要： In order to overcome the problems of time-consuming and low positioning accuracy of traditional warehousing positioning methods, a real-time positioning method for electric power materials warehousing based on RFID technology was proposed. First, the weight centre between the electrical materials to be measured is determined by the trilateral measurement method to complete the distance measurement of the stored electrical materials. Secondly, based on the measured distance, calculate the weight proportion of the electrical material storage location, and set the electrical material storage label with the help of Gaussian filter. Finally, RFID technology is introduced to analyse the collision probability of electronic labels of warehousing materials. With the help of time stamp calculation, the collision of electronic labels is avoided and the warehousing position of materials is completed. The experimental results show that the positioning accuracy of this method is high, and the highest positioning accuracy is 92%. © 2025 Inderscience Enterprises Ltd.

关键词： UHF devices  

摘要： In conventional chipless RFID systems, antennas and separate resonator tags work interdependently—resonator tags rely on antennas for data transmission, while antennas alone cannot perform RFID operations without them. This research introduces, for the first time, a standalone identification antenna (SIDA), eliminating the need for supplementary resonator tags to independently perform chipless RFID functions in the far-field. SIDA is designed as a planar monopole antenna in the ultra-high frequency (UHF) range, employing a new mechanism of notch element concentration on its patch. Intermingled coupling resonators (ICRs) are utilized as notch elements to generate multi-resonating coding bits in far-field radiation. SIDA prototypes are fabricated on Rogers RO4003C substrate with distinctive 6-bit multi-resonating codes (111111 and 111101) within the 0.78–1.38 GHz range. By eliminating the need for separate resonator tags, SIDA significantly improves conventional retransmission (ReTx)- and received signal strength (RSS)-based chipless RFID operations. Both in ReTx and RSS systems, SIDA is applied as resonator tag-free far-field chipless RFID sensor for the simultaneous detection of partial discharge (PD) defect in high-voltage (HV) systems and RF identification of PD-affected HV equipment. Experimental performances prove SIDA’s suitability as far-field chipless RFID sensor and its prospect in multi-purpose smart sensing uses by eliminating the need for additional resonator tags. © 1963-2012 IEEE.

关键词： RFID技术   传统装配行业   应用措施  

摘要： 装配行业作为制造业的关键环节，其生产效率、质量控制和供应链管理直接影响到企业的市场竞争力，信息技术的应用成为提升装配行业运营效率和管理水平的核心手段。本文主要探讨RFID技术在传统装配行业的应用现状、面临的挑战以及未来的发展趋势，通过对RFID技术的基本原理和在装配行业中的具体应用进行分析，旨在为相关领域的研究和实践提供参考。

关键词： Coils   Magnetic fields   Three-dimensional displays   Medical services   Monitoring   Near field communication   Biomedical monitoring   Radiofrequency identification   Magnetic field measurement   Implants   Magnetic coupling   HF   NFC/RFID   rotating magnetic field  

摘要： Near Field Communication (NFC) technology has been explored in the application field of biomedical sciences. NFC's inherent capabilities, such as battery-less short-range communication and secure data transfer, make it an ideal candidate for various biomedical monitoring applications. In healthcare, NFC facilitates patient identification, access control, and secure data transmission between medical devices. Additionally, NFC-enabled smart wearable devices enhance real-time health sensors data collection. A novel NFC 3D cylinder reader coil structure applied in the realm of biomedical sciences is introduced in this paper. The newly designed coil structure generates a planar rotating magnetic field, significantly improving the likelihood of successful tag identification. This enhancement in the coils' magnetic field distribution facilitates efficient communication between NFC tags and the reader. CST simulation for the generated magnetic field has been done for design optimization. A tube with overlapped copper tape is built for experimental tag detection validation. The 3D cylinder reader coil structure enhances communication in healthcare systems.

关键词： Reliability   Physical unclonable function   Security   Power demand   Resistance   Monitoring   Integrated circuit reliability   Ring oscillators   Real-time systems   Cloning   PUF   security   IoT   power consumption   temperature   robust  

摘要： For Radio Frequency Identification (RFID) security, reliable keys are essential. Physical Unclonable Functions (PUFs) prevent physical cloning, but they are sensitive to environmental variations and vulnerable to Machine Learning (ML) attacks. In this paper, a security system is proposed that aims to generate keys with high reliability and resistance to ML attacks. The entire system can be integrated into RFID tags. For reliable key generation, the proposed approach utilizes a two-step structure comprising a Coarse PUF and a Fine PUF, along with modified Ring Oscillator (RO) PUFs featuring varying ring counts. This design enhances resistance to machine learning (ML) attacks through challenge obfuscation. To further improve security against ML attacks, real-time power consumption is monitored using a novel analog circuit, and a hardware algorithm is developed based on the monitored power data. The proposed PUF (128-bit key generator) is implemented on an FPGA from the Xilinx family, specifically the Zynq-7 model. The robustness of the proposed PUF is evaluated through voltage and temperature variation tests. Experimental results demonstrate a Bit Error Rate (BER) of 3.42x10(-5) , with uniqueness and uniformity values of 49.77% and 50.27%, respectively. While a conventional PUF exhibits a vulnerability of 91.23%, the implementation of the proposed system and hardware algorithm reduces this vulnerability to 50.17%. The obtained results confirm that the proposed system offers a significantly more secure and robust solution compared to other competitors.

关键词： Human activity recognition   Radiofrequency identification   Monitoring   Gyroscopes   Accelerometers   Wearable sensors   Data collection   Wearable devices   Temperature sensors   Magnetometers   wearable sensors   smartphone sensors   RFID   deep learning   machine learning  

摘要： Human activity recognition (HAR) has garnered significant attention across diverse domains such as fitness enhancement, safety, elderly care, clinical monitoring, and smart environments. However, despite its potential, HAR faces challenges like handling noisy and diverse data, ensuring real-time performance, maintaining user privacy, and achieving high accuracy across varying contexts and activities. A primary challenge of HAR lies in maintaining consistency and accuracy during data collection amidst varied activities and environments. This review article provides a comprehensive overview of the advancements in AI-enhanced HAR methods, with a focus on radio frequency identification system, wearable devices, and smartphone sensor technologies. We delve into the frameworks of these technologies, detailing processes like data collection, preprocessing, and the application of machine learning and deep learning algorithms. Additionally, we outline the advantages and drawbacks of these techniques and provide a brief comparison between them.

关键词： Microphones  

摘要： As one of the most essential accessories, headsets have been widely used in common online conversations. The metal coil vibration patterns of headset speakers/microphones have been proven to be highly correlated with the speaker-produced/microphone-received sound. This paper presents an online conversation eavesdropping system, RFSpy, which uses only one RFID tag attached on a headset to alternately sense metal coil vibrations of headset speaker and microphone for eavesdropping on speaker-produced and microphone-received sound. In some accessible scenarios, assuming attackers secretly attach a small, battery-free RFID tag under one ear cushion of an eavesdropped user's headset without being noticed. Meanwhile, RFID readers are camouflaged as decorations placed in/out of rooms to transmit and receive RF signals. When the eavesdropped user talks with other users online through the headset, RFSpy first activates the RFID tag to capture the metal coil vibration patterns of headset speaker and microphone upon RF signals. Then, RFSpy reconstructs sound spectrograms from the RF signal-based vibration patterns for not only trained words but also untrained (i.e., out-of-vocabulary) words utilizing designed SSR network. Finally, RFSpy converts the sound spectrograms to conversation content through sound recognition API. Extensive experiments demonstrate that RFSpy can eavesdrop on online conversations with out-of-vocabulary words effectively. © 2002-2012 IEEE.

关键词： Location awareness   Antennas   Trajectory   Deformation   Radar tracking   Radiofrequency identification   Accuracy   Reliability   Measurement   Robustness   Localization   phase ambiguity   radio frequency identification (RFID)   synthetic aperture radar (SAR)   trajectory deformation error (TDE)  

摘要： Radio frequency identification (RFID) technology has become a powerful tool across industries, yet reliable RFID localization remains a significant challenge due to phase ambiguity. When RF signals complete multiple $2\pi $ phase cycles, they create multiple possible distance measurements, making it difficult to determine a tag's precise location. Existing works either deploy more antennas or impose additional constraints to mitigate the ambiguity effect. Addressing this critical obstacle, this article proposes the TDE-Loc, an innovative 2-D RFID localization system that overcomes phase ambiguity with minimal deployment requirements and no extra constraints, thus enhancing the reliability and precision of RFID-based applications. We propose a novel tracking algorithm, synthetic aperture radar (SAR) hologram of displacement (HD), which leverages synthesized displacements to achieve accurate and robust trajectories using only two antennas. Moreover, we designed a global unimodal metric, named the trajectory deformation error (TDE), to evaluate the trajectory deformation caused by wrong initial positions and find the actual initial position without ambiguity. We build a prototype of TDE-Loc and evaluate it across various environments. It outperforms existing systems in both tracking and localization with fewer antennas and deployment requirements. TDE-Loc can track the tag with only two antennas and achieves 1.69 and 6.35 cm in median and 90th percentile error, respectively. When enhanced with a third antenna, the system delivers precise localization, with median and 90th percentile errors of 3.63 and 5.37 cm.

关键词： Lung cancer  

摘要： In this study, we developed a Radio Frequency Identification (RFID) sensor to monitor respiratory rates. The sensor utilizes a passive RFID tag enhanced with a metamaterial-inspired structure to boost its maximum gain value. This gain increased from -0.39 dBi to 0.57 dBi. Monitoring of the respiratory rate was conducted by analyzing variations in the Received Signal Strength Indicator (RSSI), which were influenced by respiratory movements. The RSSI data collected from the RFID tag readings were processed using the Daubechies wavelet of order 5 (db5) with three levels of signal decomposition, resulting in signals with reduced noise. These measurements were particularly effective when the participant was at rest, with the RFID tag positioned over the abdomen. The maximum reading range obtained was 1.04 m. The respiratory rates derived from the RSSI variations were validated against a vital signals monitor, confirming that they fell within the expected frequency variation range of the multiparameter monitor. © 2025 SBMO/SBMag.