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关键词： Authentication   Counterfeit detection   Fingerprints   Mean Squared Error (MSE)   Multiple Input Multiple Output (MIMO)   Physical Layer Security (PLS)   Structural Similarity Index (SSI)   Wavelets  

摘要： This paper presents a new method to tackle the security issues of chipless tag systems in Internet of Things (IoT) applications. The strategy aims to prevent the cloning of tags by utilizing the intrinsic natural randomness in the manufacturing process. This research presents a novel approach to generate fingerprints for chipless Radio Frequency Identification (RFID) tags using the unique backscattered electromagnetic (EM) responses, caused by inherent natural variations in resonator geometry, captured by a portable Multiple Input Multiple Output (MIMO) reader. Using twenty-two tags, one authentic and twenty-one counterfeits, two separate sets of fingerprints were generated using both Frequency Domain (FD) and Time Domain (TD) data, respectively. The clone detection model achieved an accuracy of 98.41% in a 35 dB noisy environment using fingerprints generated from FD data and 92.07% in a 50 dB noisy environment using fingerprints derived from TD data. This was obtained by utilizing similarity metrics such as Mean Squared Error (MSE) and Structural Similarity Index (SSI), offering a robust alternative to traditional tag authentication methods. The portability and affordability of the MIMO reader, combined with new opportunities for image-based identification, position this approach as a substantial advancement in the realm of authenticity verification for chipless RFID tags in the realm of IoT.

关键词： Humidity   Internet of Things (ioT)   Oxygen concentration   Robot   Screen printing   Sensor tag   Spray deposition   Temperature  

摘要： The increase in global population, climate change and the scarcity of resources are some of the reasons why the improvement of the agricultural sector has become a crucial issue for the future of our society. Recently, the growth of Internet of Things (IoT) has meant a revolution in many industries, including the agricultural sector, where the employment of this technology is considered the ideal formula to boost crop efficiency. In this work we present a complete high performance IoT solution, consisting of an innovative printed smart radio frequency identification (RFID) tag and an autonomous measuring system based on a robotic platform, designed for soil monitoring purposes. The smart RFID tags are employed to obtain soil parameters, crucial for the correct development of the crops: humidity, oxygen concentration and temperature. The tag is novelly developed on a humidity dependent and flexible transparent foil substrate. The former feature enables the direct measurement of relative humidity (RH) by a capacitive structure defined on the substrate while the latter characteristic allows the sensing of oxygen content via a membrane whose luminescence intensity changes with the influence of this parameter. Effects on the antenna response are measured when the tag is placed in soil environment at root depth to validate the excellent sensing behavior of the tag. Finally, to advance the scope of this work and to show the promising performance of the tags as part of a monitoring system in the field of smart agriculture, a robot equipped with an UHF reader and IoT features, capable of automating the finding and reading of the designed RFID tags, is designed. This robot sends the information via internet for its further processing, thus constituting a low-cost, large-scale and environmentally friendly solution, ideal for enhancing crops performance.

关键词： Authentication   IoT   Post-quantum cryptography   Security  

摘要： RFID technology is widely used for contactless identification and tracking across various sectors. However, the rise of quantum computing threatens classical cryptographic protocols. To address this, we propose a lightweight RFID protocol based on the Ring Learning With Errors (RLWE) problem, ensuring post-quantum security while maintaining efficiency for resource-constrained environments. The RLWE problem provides a strong foundation for constructing quantum-resistant cryptographic schemes. Formal security proofs using the random oracle model and Scyther tool confirm its robustness against attacks. Additionally, we evaluate the protocol's security, computation, and communication costs, demonstrating its feasibility for RFID systems. This work advances post-quantum cryptographic solutions for the Internet of Things (IoT) and other ubiquitous computing environments, ensuring long-term security and privacy.

关键词： chipless RFID   long range RFID   microwave barcode   radar cross section   Van Atta array  

摘要： This letter presents a new configuration of fully passive frequency-encoded chipless RFIDs with improved detectability at oblique angles of incidence and in the presence of clutter. The proposed architecture is comprised of a wideband Van Atta retrodirective array that rotates the polarization of the retransmitted signal by 90 degrees. The presence or absence of stopbands, generated by resonators along the feed lines, form a unique binary ID across frequency in the retrodirected signal. By using an array to point a cross-polarized beam toward the source, power transfer (and thus, range) is increased while reflections from surrounding objects are minimized. As a result, robust and affordable RFID tags may be designed for operation in cluttered environments with an optimal range of distances and angles. A prototype operating from 2.5 to 3.0 GHz is fabricated, and the monostatic radar cross section (RCS) is measured across frequency to demonstrate the retrodirective frequency-encoded chipless RFID concept.

关键词： Radiofrequency identification   Linear programming   Vectors   Symbols   Signal processing algorithms   Receiving antennas   Fluctuations   Encoding   Blind source separation   Antenna arrays   Mix source separation (MSS)   gradient descent algorithm   RFID   zero constant modulus criterion  

摘要： In this letter, we propose an efficient mix source separation (MSS) algorithm for collision resolution in radio frequency identification (RFID) systems equipped with an antenna array at the reader. We first introduce an approach that exploits the zero constant modulus (ZCM) criterion to separate colliding tags through gradient descent, without using pilot symbols. We show that the ZCM characteristic, considered alone, in the design of the objective function can lead to significant ambiguities in the determination of the beamformers used in the recovery of tag messages. To address this limitation, we propose a more sophisticated approach, relying on a hybrid objective function, incorporating a new ambiguity-raising criterion in addition to the ZCM criterion.

关键词： RFID sensors   Sleep disorder detection   Sport psychology   Athletes health monitoring   Machine learning  

摘要： Sleep disorders like sleep apnea and insomnia significantly impair athletes' recovery and performance. Sleep apnea, exacerbated in supine positions due to increased airway resistance, and insomnia, evidenced by fragmented sleep and restlessness, highlight the necessity of monitoring sleep postures. This study introduces a novel RFID-embedded smart mattress capable of non-invasive monitoring and detection of these disorders by capturing body postures and movements using passive RFID sensors. A multi-layered mattress design integrates advanced RFID technology with machine learning algorithms-Gaussian process regression (GPR) and linear regression (LR)-to classify postures and detect movement anomalies. Evaluated with data from five participants in supine and prone positions, the system achieved a posture recognition root mean square error (RMSE) of 0.42 and movement detection RMSE of 0.15. Data processing included standardization and Gaussian filtering for enhanced accuracy, with a 5-fold cross-validation framework ensuring robust performance. The results demonstrate the mattress's effectiveness as a cost-efficient, non-intrusive alternative to traditional polysomnography, offering insights for early detection and management of sleep disorders. This approach shows significant potential for sports psychology applications, enabling personalized recovery strategies and performance optimization. Future work will focus on expanding the dataset, integrating additional biometric sensors, and refining algorithms to improve diagnostic accuracy and real-time usability in clinical and home settings.

关键词： Antenna measurements   Artificial intelligence   Semiconductor device measurement   Continuous wavelet transforms   Chipless RFID   Training   Testing   Radiofrequency identification   Phase measurement   Data models   Chipless radio frequency identification (RFID)   classification   continuous wavelet transform (CWT)   convolutional neural networks (CNNs)   filtering   inverse Fourier transform (IFT)   machine learning  

摘要： In this work, we propose a novel approach for the detection of chipless radio frequency identification (RFID) signals. The method is based on the application of transformations to the measurement, in conjunction with the utilization of Artificial Intelligence (AI) algorithms. In the initial stage of the process, frequency-related features are measured. Subsequently, a time-frequency representation of these measurements is generated through the application of the inverse Fourier transform (IFT), a time-gating strategy, and the continuous wavelet transform (CWT). The resulting representation is then used as input to a shallow convolutional neural network (CNN), which is able to learn complex patterns while being able to generalize to new measurements. Furthermore, the proposed scheme incorporates a filtering process, based on the probabilities derived from the model, to filter out low-confidence predictions. To assess the performance of the proposed method, we consider a population of 16 tags. We collected 4800 measurements for the training phase and 2400 measurements for the testing phase in a real-world environment. These measurements are recorded on different days and within a distance range of 50-140 cm from the tag to the antenna. The proposed method exhibited accuracies of 94% in the 110-140 cm range, 99% in the 80-110 cm range, and 100% in the 50-80 cm range, showcasing its suitability for chipless RFID detection. All the code and datasets used in this work are publicly available on GitHub and the IEEE dataport, respectively.

摘要： Cashierless stores rely on computer vision and RFID tags to associate shoppers with items, but concealed items placed in backpacks, pockets, or bags create challenges for theft prevention. We introduce a system that turns existing RFID tagged items into material sensors by exploiting how different containers attenuate and scatter RF signals. Using RSSI and phase angle, we trained a neural network to classify seven common containers. In a simulated retail environment, the model achieves 89% accuracy with one second samples and 74% accuracy from single reads. Incorporating distance measurements, our system achieves 82% accuracy across 0.3–2m tag to reader separations. When deployed at aisle or doorway choke points, the system can flag suspicious events in real time, prompting camera screening or staff intervention. By combining material identification with computer vision tracking, our system provides proactive loss prevention for cashierless retail while utilizing existing infrastructure. © 2025, CC BY.

关键词： harmonic tag   dual-band   dual-polarized   doubler circuit   nonlinear circuit   annular ring antenna   RFID  

摘要： Radio frequency identification (RFID) technology has gained significant attention in various industry sectors due to its potential for efficient inventory management, asset tracking, and object localization. Different RFID technologies are available;resorting to harmonic signals is currently less used but, recently, has gained interest in research activity. In this study, we present the design, prototype realization, and performance evaluation of a dual-band dual-polarized harmonic tag. The tag incorporates a dual-band matching circuit utilizing a zero-bias Schottky diode HSMS-2850 connected to a perturbed annular ring patch antenna. The antenna, in fact, is able to radiate in cross-polarization at the higher frequency. Through a comprehensive design methodology, including simulation optimization and prototype fabrication, we demonstrate the successful implementation of the tag. Measurements to validate the impedance matching properties, radiation patterns, and backscattering capability of the tag are also shown.

关键词： circular polarization   dual band   electromagnetic band gap structures   metasurface   RFID  

摘要： This article proposes a hexagonal shaped circularly polarized (CP) antenna at ultra-high frequency (UHF) for radio frequency identification (RFID) and X-band applications. Initially, the antenna operates only in X-band and to convert this CP dual-band antenna asymmetric ground plane and four electromagnetic band gap structures are employed. A metasurface consisting of two complementary metamaterial structures is positioned above the patch at a 9 mm distance to enhance the gain and impedance bandwidth in both the bands. The presented antenna whose electrical dimension 0.48 lambda g x 0.48 lambda g x 0.02 lambda g achieves an impedance bandwidth of 796 MHz and of 4.24 GHz in UHF-RFID and X-band spectrum, respectively. The proposed antenna achieves circular polarization and has a bandwidth of 995 MHz and 796 MHz which spans 2.28-3.28 GHz and 10.44-11.24 GHz, respectively, with a 3 dB axial ratio. In addition to these, a stable radiation characteristic with an average gain of 6 dBi at both 2.45 GHz and 11.21 GHz are achieved which makes it suitable for RFID based real time logistic warehousing applications.