Search Results (491)

In the field of the Internet of Things (IoT), technical solutions that enable information transmission with minimal energy consumption are of particular interest. Common solutions frequently used in the field of radio frequency identification (RFID) involve utilizing electromagnetic waves to power tags and employing backscattering for communication. Detecting the received signal in a coherent manner enables increased reliability in tag reading. This paper proposes a method for coherent signal detection in a bistatic backscatter communication system (BBCS), which includes coarse carrier frequency offset (CFO) from preamble and fine phase correction from data symbols. The proposed method outperforms the detection approach based on maximum likelihood estimation (MLE) of CFO from the preamble, particularly in scenarios with higher CFO values. The proposed detection method is well suited for implementation in software-defined radios, particularly in low-cost devices characterized by less stable oscillators. It is also shown that a preamble of six symbols is sufficient to perform a coarse CFO estimation. Since the analyzed system is equivalent to binary frequency-shift keying (FSK) modulation, the performance of FSK is presented as the theoretical upper bound in the results. Full article

Food loss and waste from the European Union’s dairy supply chain, particularly in the management of fresh milk, imposes significant environmental burdens. This study demonstrates that implementing Radio Frequency Identification (RFID)-enabled digital decision-support tools can substantially reduce these impacts across the region. A cradle-to-grave life cycle assessment (LCA) was used to quantify both the additional environmental burdens from RFID (tag production, usage, and disposal) and the avoided burdens due to reduced milk losses in the farm, processing, and distribution stages. Within the EU’s fresh milk supply chain, the implementation of digital tools could result in annual net reductions of up to 80,000 tonnes of CO₂-equivalent greenhouse gas emissions, 81,083 tonnes of PM_2.5-equivalent particulate matter, 84,326 tonnes of land use–related carbon deficit, and 80,000 cubic meters of freshwater-equivalent consumption. Spatial analysis indicates that regions with historically high spoilage rates, particularly in Southern and Eastern Europe, see the greatest benefits from RFID enabled digital-decision support tools. These environmental savings are most pronounced during the peak months of milk production. Overall, the study demonstrates that despite the environmental footprint of RFID systems, their integration into the EU’S dairy supply chain enhances transparency, reduces waste, and improves resource efficiency—supporting their strategic value. Full article

Radio Frequency Identification (RFID) technology is widely applied in various scenarios, including logistics tracking, supply chain management, and target monitoring. In these contexts, the malicious cloning of legitimate tag information can lead to sensitive data leakage and disrupt the normal acquisition of tag information by readers, thereby threatening personal privacy and corporate security and incurring significant economic losses. Although some efforts have been made to detect cloning attacks, the presence of missing tags in RFID systems can obscure cloned ones, resulting in a significant reduction in identification efficiency and accuracy. To address these problems, we propose the block-based cloned tag identification (BCTI) protocol for identifying cloning attacks in the presence of missing tags. First, we introduce a block indicator to sort all tags systematically and design a block mechanism that enables tags to respond repeatedly within a block with minimal time overhead. Then, we design a superposition strategy to further reduce the number of verification times, thereby decreasing the execution overhead. Through an in-depth analysis of potential tag response patterns, we develop a precise method to identify cloning attacks and mitigate interference from missing tags in probabilistic cloning attack scenarios. Moreover, we perform parameter optimization of the BCTI protocol and validate its performance across diverse operational scenarios. Extensive simulation results demonstrate that the BCTI protocol meets the required identification reliability threshold and achieves an average improvement of $24.01\%$ in identification efficiency compared to state-of-the-art solutions. Full article

The global coffee supply chain is a complex multi-stakeholder ecosystem plagued by fragmented records, unverifiable origin claims, and limited real-time visibility. These limitations pose risks to ethical sourcing, product quality, and consumer trust. To address these issues, this paper proposes a blockchain and IoT-enabled framework for secure and transparent coffee supply chain management. The system integrates simulated IoT sensor data such as Radio-Frequency Identification (RFID) identity tags, Global Positioning System (GPS) logs, weight measurements, environmental readings, and mobile validations with Ethereum smart contracts to establish traceability and automate supply chain logic. A Solidity-based Ethereum smart contract is developed and deployed on the Sepolia testnet to register users and log batches and to handle ownership transfers. The Internet of Things (IoT) data stream is simulated using structured datasets to mimic real-world device behavior, ensuring that the system is tested under realistic conditions. Our performance evaluation on 1000 transactions shows that the model incurs low transaction costs and demonstrates predictable efficiency behavior of the smart contract in decentralized conditions. Over 95% of the 1000 simulated transactions incurred a gas fee of less than ETH 0.001. The proposed architecture is also scalable and modular, providing a foundation for future deployment with live IoT integrations and off-chain data storage. Overall, the results highlight the system’s ability to improve transparency and auditability, automate enforcement, and enhance consumer confidence in the origin and handling of coffee products. Full article

The advancement of Internet of Things (IoT) technology has enabled battery-powered devices to be deployed across a wide range of applications; however, it also introduces challenges such as high energy consumption and security vulnerabilities. To address these issues, adiabatic logic circuits offer a promising solution for achieving energy efficiency and enhancing the security of IoT devices. Adiabatic logic circuits are well suited for energy harvesting systems, especially in applications such as sensor nodes, RFID tags, and other IoT implementations. In these systems, the harvested bipolar sinusoidal RF power is directly used as the power supply for the adiabatic logic circuit. However, adiabatic circuits require a peak detector to provide bulk biasing for pMOS transistors. To meet this requirement, a diode-connected MOS transistor-based voltage doubler circuit is used to convert the sinusoidal input into a usable DC signal. In this paper, we propose a novel adiabatic logic design that maintains low power consumption while optimizing energy and current fluctuations across various input transitions. By ensuring uniform and complementary current flow in each transition within the logic circuit’s functional blocks, the design reduces energy variation and enhances resistance against power analysis attacks. Evaluation under different clock frequencies and load capacitances demonstrates that the proposed adiabatic logic circuit exhibits lower fluctuation and improved security, particularly at load capacitances of 50 fF and 100 fF. The results show that the proposed circuit achieves lower power dissipation compared to conventional designs. As an application example, we implemented an ultrasonic transmitter circuit within a LoRaWAN network at the end-node sensor level, which serves as both a communication protocol and system architecture for long-range communication systems. Full article

Hydropower infrastructure has profoundly altered riverine connectivity, posing challenges to the migratory behavior of aquatic species. This study examined the post-passage migration efficiency of Schizothorax wangchiachii in a regulated river system, focusing on upstream and downstream reaches of the Songxin Hydropower Station on the Heishui River, a tributary of the Jinsha River. We used radio-frequency identification (RFID) tagging to track individuals after fishway passage and coupled this with environmental monitoring data. A Cox proportional hazards model was applied to identify key abiotic drivers of migration success and to develop a predictive framework. The upstream success rate was notably low (15.6%), with a mean passage time of 438 h, while downstream success reached 81.1%, with an average of 142 h. Fish exhibited distinct diel migration patterns; upstream movements were largely nocturnal, whereas downstream migration mainly occurred during daylight. Water temperature (HR = 0.535, p = 0.028), discharge (HR = 0.801, p = 0.050), water level (HR = 0.922, p = 0.040), and diel timing (HR = 0.445, p = 0.088) emerged as significant factors shaping the upstream movement. Our findings highlight that fishways alone may not ensure functional connectivity restoration. Instead, coordinated habitat interventions in upstream tributaries, alongside improved passage infrastructure, are crucial. A combined telemetry and modeling approach offers valuable insights for river management in fragmented systems. Full article

As a crucial characteristic waterfowl breed, the egg-laying performance of Lion-Headed Geese serves as a core indicator for precision breeding. Under large-scale flat rearing and selection practices, high phenotypic similarity among individuals within the same pedigree coupled with traditional manual observation and existing automation systems relying on fixed nesting boxes or RFID tags has posed challenges in achieving accurate goose–egg matching in dynamic environments, leading to inefficient individual selection. To address this, this study proposes YOLO-Goose, an improved YOLOv8s-based method, which designs five high-contrast neck rings (DoubleBar, Circle, Dot, Fence, Cylindrical) as individual identifiers. The method constructs a lightweight model with a small-object detection layer, integrates the GhostNet backbone to reduce parameter count by 67.2%, and employs the GIoU loss function to optimize neck ring localization accuracy. Experimental results show that the model achieves an F1 score of 93.8% and mAP50 of 96.4% on the self-built dataset, representing increases of 10.1% and 5% compared to the original YOLOv8s, with a 27.1% reduction in computational load. The dynamic matching algorithm, incorporating spatiotemporal trajectories and egg positional data, achieves a 95% matching rate, a 94.7% matching accuracy, and a 5.3% mismatching rate. Through lightweight deployment using TensorRT, the inference speed is enhanced by 1.4 times compared to PyTorch-1.12.1, with detection results uploaded to a cloud database in real time. This solution overcomes the technical bottleneck of individual selection in flat rearing environments, providing an innovative computer-vision-based approach for precision breeding of pedigree Lion-Headed Geese and offering significant engineering value for advancing intelligent waterfowl breeding. Full article

This paper presents a Virtualized Computational Radio Frequency Identification (VCRFID) solution that utilizes far-field UHF RF for sensing, computing, and self-powering at the edge. A standard UHF RFID system is asymmetric as it consists of a relatively large, complex “reader”, which acts as an RF transmitter and controller for a number of small simple battery-less “tags”, which work in passive mode as they communicate and harvest RF energy from the reader. Previously proposed Computational RFID (CRFID) solutions enhance the standard RFID tags with microcontrollers and sensors in order to gain enhanced functionality, but they end up requiring a relatively high level of power, and thus ultimately reduced range, which limits their use for many Internet-of-Things (IoT) application scenarios. Our VCRFID solution instead keeps the functionality of the tags minimalistic by only providing a sensor interface to be able to capture desired environmental data (temperature, humidity, vibration, etc.), and then transmit it to the RFID reader, which then performs all the computational load usually carried out by a microcontroller on the tag in prior work. This virtualization of functions enables the design of a circuit without a microcontroller, providing greater flexibility and allowing for wireless reconfiguration of tag functions over RF for a 97% reduction in energy consumption compared to prior energy-harvesting RFID tags with microcontrollers. The target application is Industry 4.0 where our VCRFID solution enables battery-less fine-grain monitoring of vibration and temperature data for pumps and motors for predictive maintenance scenarios. Full article

Printed electronics employ established printing methods to create low-cost, mechanically flexible devices including batteries, supercapacitors, sensors, antennas and RFID tags on plastic, paper and textile substrates. This review focuses on the specific contribution of screen printing to that landscape, examining how ink viscosity, mesh selection and squeegee dynamics govern film uniformity, pattern resolution and ultimately device performance. Recent progress in advanced ink systems is surveyed, highlighting carbon allotropes (graphene, carbon nano-onions, carbon nanotubes, graphite), silver and copper nanostructures, MXene and functional oxides that collectively enhance mechanical robustness, electrical conductivity and radio-frequency behavior. Parallel improvements in substrate engineering such as polyimide, PET, TPU, cellulose and elastomers demonstrate the technique’s capacity to accommodate complex geometries for wearable, medical and industrial applications while supporting environmentally responsible material choices such as water-borne binders and bio-based solvents. By mapping two decades of developments across energy-storage layers and functional electronics, the article identifies the key process elements, recurring challenges and emerging sustainable practices that will guide future optimization of screen-printing materials and protocols for high-performance, customizable and eco-friendly flexible devices. Full article

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. Full article

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. Full article

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 sensor. The sensor was placed near the conductor such that the Hall effect device was close to the surface of the conductor, and readings were acquired by the RFID reader. The sensitivity of the entire RFID sensor was 30 mV/mT, with linear behavior over a magnetic flux density range from 0 mT to $4.5$ mT. Full article

This paper proposes a three-point nonlinear calibration scheme for an ultra-low-power, high-precision temperature sensor to address the issue where the temperature error of a 0.8 μW sensor exceeds ±1 °C in RFID (Radio-Frequency Identification) temperature measurement systems. The proposed calibration scheme introduces a temperature-dependent nonlinearity coefficient to the traditional linear calibration, effectively compensating for the sensor’s nonlinear output characteristics. To minimize calibration costs, a scheme embedding the calibration algorithm into the reader is proposed, along with a dichotomy-based approach for efficient temperature calibration. The experimental results demonstrate that, within the temperature range of −30 °C to 90 °C, the temperature error of five sensor samples can be reduced from ±8 °C to between −1 °C and 0.6 °C. This solution has been successfully implemented in mass production. Full article

This article presents a comprehensive analysis of the technical characteristics of advanced versatile materials used in chipless radio-frequency identification (RFID) tags and antennas. The focus is on materials that are used as radiators and substrates. Crucial aspects include flexibility, weight, size, gain, environmental sustainability, efficiency, fabrication time and type, and cost. A comprehensive set of tables are presented that summarize and compare material properties. The materials include flexible high-tech ink substances, graphene, and liquid crystals, as well as metamaterials which possess properties that allow for an increased bandwidth. Printing techniques are discussed for high-performance high-resolution fabricated tags. This paper contributes by systematically comparing emerging materials for chipless RFID tags, highlighting their impact on performance and sustainability. It also provides practical guidance for material selection and fabrication techniques to enable next-generation wireless applications. It presents a broad understanding of various materials and their use. The paper provides direction for the deployment and utilization of inexpensive passive chipless RFID tags in future intelligent wireless networks. The advancement of chipless RFID is largely driven by the development of innovative materials, especially in the realm of advanced materials and smart materials, which enable the creation of more cost-effective, flexible, and scalable RFID systems. Full article

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. Full article