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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.

关键词： LANDMARC   RFID   weighted factor   tennis   robot  

摘要： With the quick advancement of technology, tennis ball-picking robots have been maturely applied. However, currently, automatic tennis ball-picking robots often have low accuracy in positioning. To improve the accuracy of tennis automatic robot positioning, a weighted factor and virtual reference label improved indoor positioning algorithm is proposed, combined with radio frequency identification (RFID) technology. This method is applied to the automatic tennis ball-picking robot and constructs a tennis automatic ball-picking robot model based on improved indoor positioning algorithm and RFID technology. Comparing the effectiveness of the proposed improved algorithm, it was found that the precision and average accuracy of the algorithm were 0.983 and 94.6%, respectively, which were better than the comparison algorithms. In addition, an effectiveness comparison analysis was conducted on the tennis automatic robot model based on this algorithm, and it was found that the positioning effectiveness of the model was significantly better than the comparison model. Moreover, a positioning comparison experiment was conducted on the model, and the results showed that the positioning accuracy of the model was better than that of the comparison model. The above outcomes illustrate that the improved algorithm proposed in the study and the tennis automatic ball-picking robot model based on this algorithm have good practical value, which is conducive to improving the accuracy of the robot's image target positioning.

关键词： RFID tags   Gesture recognition   Glass   Accuracy   Smart glasses   Feature extraction   Internet of Things   Hands   Contrastive learning   Privacy   gesture recognition   radio frequency identification (RFID)   smart glasses   wireless sensing  

摘要： Smart eyeglasses are emerging as a new medium for human-computer interaction. Existing solutions typically rely on cameras or touchpads, raising privacy invasion concerns or requiring users to physically interact with the glass frames. Here, we present RF-Sauron, a novel mid-air gesture interaction system for eyeglasses, based on radio frequency identification (RFID). The design of our RF-Sauron system involves embedding a conformal RFID tag into the eyeglass frame, where the received signals change with user gestures. We optimize the radiation gain of the tag to avoid view blockage while preserving a long working range. To discriminate different gestures, we propose an adaptively weighted multichannel fusion network to extract their respective distinctive features. To allow efficient adaptation of the pretrained network to new users, we also introduce a novel diagonal dot-product attention in our contrastive learning framework to uncover the feature similarities of different users. The proposed RF-Sauron system was evaluated through extensive experiments, demonstrating an average recognition accuracy of 98.86% across 20 users and a cross-user accuracy of 98.75%.

关键词： Electronic product code (EPC) GEN-2   inaccuracy   one-point calibration   power conversion efficiency (PCE)   power dynamic range (PDR)   read and write protection mechanism   thermometry   time-domain digital quantization   ultra-high frequency (UHF)   ultralow-power radio frequency identification (RFID)  

摘要： This article presents an ultralow-power radio frequency identification (RFID) with an embedded CMOS temperature sensor (TS). The thermometry working flow of the Query01-Query00-Ack sequence is introduced, which is compatible with the electronic product code (EPC) GEN-2 standard. A 2k-bit multitime programmable (MTP) nonvolatile memory (NVM) array with a standard CMOS process is used to store tag information, tag identification (TID), EPC, initialization parameter, and TS data. The proposed rectifier can achieve a wide power dynamic range (PDR) of 21.5 dB with peak power conversion efficiency (PCE) of 65%@-15 dBm under a 100-k Omega load. A protection mechanism for reliable reading and writing is presented to ensure proper tag initialization and avoid the ghost tag phenomenon. Time-domain digital quantization is adopted to convert the signal that period varies with temperature into a digital signal for low power consumption. The TS achieves a resolution of 0.16 degrees C and inaccuracy of +0.42 degrees C/ -0.83 degrees C after one-point calibration at 0 degrees C in the temperature range from -20 degrees C to 30 degrees C. When the TS is powered at 1 V, it can achieve 0.234 nJ of energy per conversion in a conversion time of 1.8 ms. The passive RFID TS occupies an area of 0.5579 mm(2) in the 0.13- mu m CMOS process. At the frequency of similar to 910 MHz, measured tag sensitivity can reach -22 dBm, and the 3-dB bandwidth is 51.5 MHz.

关键词： belief function theory   collisions   DFSA   estimation   RFID  

摘要： Radio frequency identification (RFID) technology has revolutionized various industries by enabling automatic identification and tracking of objects. However, in practical RFID systems, collisions occur when multiple tags are present within the coverage area of a single reader, resulting in communication interference and inaccurate tag count estimation. An accurate estimation of the number of tags in RFID systems is crucial for efficient tag identification and system performance. In this paper, we propose a new accurate ultrahigh frequency (UHF) RFID tag quantity estimation technique based on belief function theory, also known as Dempster-Shafer theory (DST). DST offers a robust framework for reasoning under uncertainty and has demonstrated its effectiveness in addressing intricate information-fusion challenges. The proposed technique, operating at the physical layer, uses belief functions and mass assignment principles to model the uncertainty associated with tag collisions, enabling accurate estimation. By merging evidence from multiple sources, such as time delays and signal power levels, the method improves the reliability of the estimation process. The simulation results demonstrate that the proposed technique achieves superior performance in terms of the estimation error and success rate, outperforming other estimation methods reported in the literature. Moreover, the experimental results corroborated the simulation results and demonstrated the capability and effectiveness of DST in addressing the challenges of collisions in RFID technology.

关键词： magnetic field sensing   RFID   RF power harvesting   HVdc transmission   HVdc system monitoring  

摘要： High-voltage direct-current (HVdc) transmission lines are gaining more attention as an integral part of modern power system networks. Monitoring the dc current is important for metering and the development of dynamic line rating control schemes. However, this has been a challenging task, and there is a need for wireless sensing methods with high accuracy and a dynamic range. Conventional methods require direct contact with the high-voltage conductors and utilize bulky and complex equipment. In this paper, an ultra-high-frequency (UHF) radio frequency identification (RFID)-based sensor is introduced for the monitoring of the dc current of an HVdc transmission line. The sensor is composed of a passive RFID tag with a custom-designed antenna, integrated with a Hall effect magnetic field device and an RF power harvesting unit. The dc current is measured by monitoring the dc magnetic field around the conductor using the Hall effect device. The internal memory of the RFID tag is encoded with the magnetic field data. The entire RFID sensor can be wirelessly powered and interrogated using a conventional RFID reader. The advantage of this approach is that the sensor does not require batteries and does not need additional maintenance during its lifetime. This is an important feature in a high-voltage environment where any maintenance requires either an outage or special equipment. In this paper, the detailed design of the RFID sensor is presented, including the antenna design and measurements for both the RFID tag and the RF harvesting section, the microcontroller interfacing design and testing, the magnetic field sensor calibration, and the RF power harvesting section. The UHF RFID-based magnetic field sensor was fabricated and tested using a laboratory experimental setup. In the experiment, a 40 mm-diameter-aluminum conductor, typically used in 500 kV HVdc transmission lines carrying a dc current of up to 1200 A, was used to conduct dc current tests for the fabricated senso

关键词： Resource allocation  

摘要： In the rapidly evolving landscape of 5G and B5G (beyond 5G) 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/B5G 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/B5G and lays the groundwork for future advancements in 6G networks. By leveraging real-tim

关键词： metamaterial   microstrip antenna   RFID   zero-index metamaterial  

摘要： This article introduces a new high-gain linearly polarized (LP) antenna utilizing zero-index metamaterial (ZIM). The design comprises of a rectangular radiating patch and a 2 x 2 square-shaped metamaterial (MTM) structure. Through the MTM, a zero-index antenna is created, fabricated, and tested. The realized gain of the suggested design is higher with the MTM due to ZIM's focusing effect. The overall dimensions of the antenna are 0.24 lambda(0 )x 0.016 lambda(0), where lambda(0) is the free-space wavelength. The proposed antenna includes a ground plane measuring 0.49 lambda(0 )x 0.49 lambda(0). The antenna's gain has been observed to increase, approximately from 3.95 to 5.61 dBi. The successful completion of the propagation test under various conditions, along with a reading distance of 7 cm in the ISM band, validates the potential use of the structure as a short-range RFID reader. The suggested antenna, loaded with an MTM superstrate, offers a minimized overall thickness, particularly in comparison to the use of ZIM superstrates for enhancing the gain in antennas documented in previous literature.