RFID System Research Articles

Performance Limit: Fuzzy Logic Based Anti-Collision Algorithm for Industrial Internet of Things Applications

Passive RFID has the advantages of rapid identification of multi-target objects and low implementation cost. It is the most critical technology in the Industrial Internet of Things information-gathering layer and is extensively applied in various industries, such as smart production, asset management, and monitoring. The signal collision caused by the communication between the reader/writer and tags sharing the same wireless channel has caused a series of problems, such as the reduction of the identification efficiency of the reader/writer and the increment of the missed reading rate, thus restricting the further development of RFID. At present, many hybrid anti-collision algorithms integrate the advantages of Aloha and TS algorithms to optimize RFID system performance, but these solutions also suffer from performance bottlenecks. In order to break through such performance bottleneck, based on the ISE-BS algorithm, we combined the sub-frame observation mechanism and the Q value adjustment strategy and proposed two hybrid anti-collision algorithms. The experimental results show that the two algorithms proposed in this paper have obvious advantages in system throughput, time efficiency and other metrics, surpassing existing UHF RFID anti-collision algorithms.

GLAC: High-Precision Tracking of Mobile Objects With COTS RFID Systems

GLAC: High-Precision Tracking of Mobile Objects With COTS RFID Systems

Can displaced Anguilla marmorata return to their original habitat? Daily tracking study of their homing behavior.

Anguilla marmorata collected in the Odana River lower reaches were passive integrated transponder-tagged displaced and released into the upper river reaches (54 up-transported eels), and eels collected in the upper reaches were tagged and released downstream (52 down-transported eels). Their movements were detected once per day for 10 days using a portable radio-frequency identification (RFID) system. The homing rate of the down-transported eels was 38.9%, compared to 3.7% for the up-transported eels, suggesting that eels inhabiting upstream areas have relatively high fidelity to their habitats and downstream eels have less fidelity.

Propagation Analysis of an RFID System in the UHF Band in the Honeycomb Frame of a Beehive.

In recent years, communication systems, including RFID, have been used in intelligent beehives for beekeeping. RFID systems in the UHF frequency band offer reading distances of tens of centimetres, allowing the localisation and identification of the queen bee inside the hive. With this purpose, this work proposes an analysis of an environment of propagation that consists of a honeycomb frame, where the reader is placed within the frame, and the tag is placed in different positions over it. A honeycomb frame consists of a wooden box containing a honey wax panel, supported by metallic wires. The environment is modelled theoretically using its S-parameters and simulated in CST Studio. An analysis of these results and empirical measurements is performed. The results show that a periodicity in the received power of the tag is found with respect to the distance to the reader when the tag is located in a direction parallel to the wire, where local maximum and minimum values are found. Additionally, when the tag is placed over a wire of the frame, a higher received power is obtained compared to the case where the tag is placed between two wires. Furthermore, it has been observed that the reading range has increased with respect to free space, covering the full frame.

An Ultra High Frequency Radio Frequency Identification Compatible Circular Polarized Microstrip Antenna Array

This study focuses on the development, simulation, and practical validation of a metal-only microstrip patch antenna and its array designed to increase gain. The antenna is specifically designed to meet the growing demand for reliable and efficient RFID systems in various fields, such as asset tracking, inventory management, and smart logistics. Our design utilizes a truncated patch with an air substrate to achieve high gain and circular polarization. The antenna's dimensions measure 468 × 188 × 31 mm³ and deliver impressive performance metrics, boasting a return loss |S11| of -18.21 dB and an estimated gain exceeding 10.6 dBi. These figures compare favorably with the simulated results, which indicate an |S11| of -20.8 dB and a total gain of 11.2 dBi. Our microstrip antenna array demonstrated consistent Circular Polarization quality throughout the radiation angle, with an Axial Ratio of less than 3 dB. This antenna has emerged as a compelling solution for UHF-band RFID technology to meet the demands of various real-world applications.

FABRICATION OF ORDERS BY SCARA ROBOT WITH RFID TECHNOLOGY

In today’s world of automation, recognizing and processing parcels in a particular area of zone is a crucial task. One such task is pick-and place operation, which is well- known for its challenges. The main theme of this operation is to sort products into different areas based on their representative fields. To address this issue, we have a SCARA robot that is known for its liner momentum motion of 4 degrees of freedom. This robot is well-suited for pick-and- place operations and can perform operations in two axes. Moreover, it is cost-effective and efficient. The SCARA robot is connected to the Arduino Mega, which is run by servo motors and controllers. The fabrication of an Arduino based Parcel diverter system involves the creation of a system that uses an Arduino Mega microcontroller to sort and divert parcels based on their destination. The system is designed to take input from Radio frequency identification device that detects the parcels and direct them to their appropriate destination using a series of mechanical diverters. The fabrication process includes the design and assembly of the mechanical components, the programming of the micro controller, and the integration of the sensors. The resulting system provides a reliable and efficient way to sort and direct parcels in a variety of industrial and logistical applications. Key Words: Conveyor, Arduino Mega, IR/Thermal sensors, stepper motor, micro step driver SCARA robot, RFID system, DC Vacuum pump and DC Motor.

RFID BASED BUS TICKETING SYSTEM

The main objective of this paper is to generate passenger tickets using RFID technology for the fare of a particular destination. The appropriate amount is deducted from the RFID card. In addition to that, in proposal system RFID has proven to be one of the most promising technologies in recent years and can be effectively employed in various applications since it is economical and widely used tool for tracking and locating purposes.Radio-frequency identification (RFID) is a technology that uses electromagnetic fields to automatically identify and track tags attached to objects .A small radio transponder, a radio receiver, and a radio transmitter make up an RFID system The RFID application, on the other hand, has become a popular tool for both tracking transit vehicles and the public ticketing system describes a design of IoT enabled real time bus tracking system There is an mobile app to recharge the RFID card.The message of money transaction is send to the users registered mobile number.The main aim of this project is to reduce the fraud in ticket transaction.The bus door will open only after scanning the RFID card.In this project we use IR sensor to detect the passengers entry and exit from the bus.When the passenger scan the RFID card then the LCD display shows the passengers information like their name,RFID card number,account balance.The ticket price is based on the distance travelled in the bus.This system also used to prevent the unfair ticket price for transportation.If the RFID card is missing then the passenger can able to block the RFID card to prevent unauthorized access.Public transportation is a significant role for methods among individuals. Key words—Radio Frequency Identification System (RFID), Infrared sensor (IR sensor).

Development and evaluation of RFID-integrated endoscopic clips for laparoscopic surgery marking.

As advancements in surgical instruments and techniques continue to evolve, minimally invasive surgery has become increasingly preferred as a means of reducing patient pain and recovery time. However, one major challenge in performing minimally invasive surgery for early gastrointestinal cancer is accurately identifying the location of the lesion. This is particularly difficult when the lesion is confined to the lumen of the intestine and cannot be visually confirmed from the outside during surgery. In such cases, surgeons must rely on CT or endoscopic imaging to locate the lesion. However, if the lesion is difficult to identify with these images or if the surgeon has less experience, it can be challenging to determine its precise location. This can result in an excessive resection margin, deviating from the goal of minimally invasive surgery. To address this challenge, researchers have been studying the development of a marker for identifying the lesion using a radio-frequency identification (RFID) system. One proposed method for clinical application of this detection system is to attach an RFID tag to an endoscopic hemostatic clip and fix it to the intended position, providing a stable marker for the inner wall of the organ. This approach has the potential to improve the accuracy and effectiveness of minimally invasive surgery for early gastrointestinal cancer. In the development of a marker for identifying gastrointestinal lesions using a radio-frequency identification (RFID) system, the shape of the clip and suitable materials for attaching the RFID tag were determined through finite element method (FEM) analysis. A prototype of the clip was then fabricated and ex-vivo experiments were conducted using porcine intestine to evaluate the stability of the clip in relation to its position. To further evaluate the performance of the RFID-integrated clip in vivo, the clip was placed in the gastric wall of the stomach of anesthetized porcine using an endoscopic instrument. The clip was then detected using a RFID detector designed for laparoscopic approach. And later, the accuracy of detection was confirmed by incising the lesion. The design and fabrication of a clip with varying thicknesses using STS316 and STS304 stainless steel were accomplished using the results of finite element method analysis. The stability of the clip was evaluated through ex-vivo experiments, showing it to be a viable option. In-vivo experiments were performed on anesthetized porcine, in which the RFID-integrated clip was placed in the gastric wall and detected using a custom-made RFID detector. The resection margin, measured at about 30 mm from the detector position, was accomplished with low error. These findings indicate the feasibility and efficacy of using an RFID-integrated clip as a marker in minimally invasive surgery for the identification of gastrointestinal lesions. The study evaluated the feasibility of using stainless steel clips for lesion detection in endoscopic surgery using computer-aided engineering analysis and ex-vivo experimentation. Results showed that STS304 was suitable for use while STS316L was not. The ex-vivo experiments revealed that the clip holding force and tissue retention length varied depending on the location of attachment. In-vivo experiments confirmed the accuracy and usefulness of the RFID lesion detection system. However, challenges remain for its use in clinical field, such as ensuring the stability of the clip and the safe attachment of the RFID tag, which requires further research for commercialization.

On Batch Writing in COTS RFID Systems

We study the batch writing problem in RFID systems, where the reader seeks the most time-efficient way to write information into a given subset of tags. The problem is analogous to the multicast problem in classical networks, but one-to-many transmission is not supported in COTS RFID systems. Driven by the technical challenge, this paper addresses the problem of designing batch writing algorithms for COTS RFID systems. We make three contributions. Firstly, we establish the minimal execution time for any batch writing algorithm, thus setting the theoretical performance limit. Secondly, we quantitatively compare and gauge the existing propositions applicable to our problem. Thirdly, we develop a novel batch writing algorithm with minimal 25% performance gain over the best state-of-the-art solution. Our key technicalities are designing an encoding scheme allowing the reader to efficiently perform batch writing and optimizing the batch writing sequence to minimize the overall execution time. We also perform extensive experiments to demonstrate the effectiveness of our algorithm.

High directivity microstrip patch antenna design using binary ebola search optimization for radio frequency identification application

Microstrip patch antenna has gained significant popularity in wireless communication field, because of its compact size, less profile, and ease of installation. It is widely used in various applications such as Radio-Frequency Identification (RFID) systems, where dependable and long-range communication is made possible by the great directivity and efficiency. In this manuscript, a High Directivity Microstrip Patch Antenna design using Binary Ebola Search Optimization for Radio Frequency Identification Application (MPA-RFID-BESO) is proposed.The design of microstrip patch antennas is the difficulty in achieving high directivity while maintaining compact size and low profile. This research explains design and application-specific optimisation of the Microstrip Patch Antenna (MPA) of biomedical utilizing Binary Ebola Search optimization (BESO) algorithm. Microstrip patch antenna is designed to function in double and multi band applications due to its low cost, light weight, and ease of installation. MPA is made with flawed ground construction to lessen cross-polarized radiation emitted by microstrip patches and to achieve the necessary radiation parameters. Here, the cost of the materials is reduced by using a liquid crystal polymer substrate, and aerial performance is enhanced by using the appropriate geometrical parameters. The small design of the BESO optimised improves the performance of antenna as 50 mm×50 mm compact size. The MATLAB program uses high frequency to do the simulation method. The proposed antenna design is a preferable option for applications involving Radio Frequency Identification (RFID). The performance metrics, such as radiation pattern, constant gain, directivity, bandwidth, and antenna efficiency and return loss are measured and compared to the existing techniques. The proposed MPA-BA-BESO design provides 10.51%, 12.85% and 16.04% higher bandwidth and 23.63%, 47.86% and 32.06% higher gain compared with existing designs, like Designing MPA utilizing Moth–Flame optimization approach (MPA-UWB-MFOA), Predicting Rectangular Patch Microstrip Antenna Dimension utilizing Machine Learning (MPA-ANN), Dual Band Antenna Design and Prediction of Resonance Frequency Utilizing Machine Learning Algorithms (DBAD-RF-CNN) respectively. The proposed technology serve as a better design alternative for microstrip patch antennas in communication systems to address biological applications.

Design of an RFID-Based Self-Jamming Identification and Sensing Platform

Commodity RFID tags backscatter stored electronic product code (EPC) to the reader, but do not have sensing capability. Existing works have made much effort on designing RFID-based sensing platform. But most of them either need intricate hardware design or rely on modification of the tag, which increases the cost or constrains the sensing capability. In this paper, we design a self-jamming identification and sensing platform (SJISP) consisting of SJISP nodes and a commodity RFID reader. A subtle design of the SJISP node is the adoption of a jammer radio module with the same frequency as the reader, controlled by the micro control unit (MCU) to decide whether to interfere with the query process of the RFID reader. The RFID tag is not readable if the jammer is turned on to generate interference signals. Otherwise, it is readable when the jammer is turned off. The sensing data is thus modulated by switching the jammer on and off for transmitting bit 0 and bit 1, respectively. The reader demodulates the data through the compatible EPC UHF Gen2 air interface protocol. To further save the energy of the SJISP node, we propose a prefix codebook based data delivery scheme, which leverages the difference of energy consumption (DEC) between transmitting bit 0 and bit 1. Our proposed scheme can save more than 50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> of the energy than common communication without codebook. Experimental results based on our prototyped system show that the designed SJISP can achieve an average packet reception rate (PRR) of over 99 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and is quite robust to environmental disturbance. Our designed platform provides a low-cost and compatible solution to extend the sensing capability of RFID system. A demo application with a temperature sensor and a light sensor embedded in two SJISP nodes respectively are developed to demonstrate how SJISP applies in real world scenario.

Automatic Bus Fare Collection System Using RFID

Abstract: India is the second largest populated country in the world so most of the people use public transport. During peak hours issuing tickets to each passenger manually is time consuming and tedious task and also a problem. The probability of ticket fraud is also high in this case. Since the tickets are made of papers it leads to deforestation and these tickets are of no use once when the passenger gets out of the bus. So in order to overcome all these difficulties we have a Smart ticketing system that is proposed using RFID to issue tickets to passengers. In order to ensure the passengers journey with no quarrels and mesh we employ this solution that replaces the traditional paper ticketing by electronic cards, vended through automated machine using smart cards, which improves the convenience and security of transaction. This project actually suggests a much more public friendly, automated system of ticketing with the use of RFID based tickets. Automatic Fare Collection System is implemented in this project through RFID (Smart) card. RFID card is given to the passenger and when passenger enters to the bus, he has to scan the card in the RFID reader. All the record will update automatically in the server continuously. RFID system through automated machine enables the passenger to predetermine the transport details. The control circuit is designed using arduino controller that will be interfaced with a DC motor to identify the distance travelled by the passenger to collect the fare amount. In addition a LCD is used for displaying the data.

RFID Tags for On-Metal Applications: A Brief Survey

Radio-frequency identification technology finds extensive use in various industrial applications, including those involving metallic surfaces. The integration of radio-frequency identification systems with metal surfaces, such as those found in the automotive sector, presents distinct challenges that can notably affect system efficacy due to metal’s tendency to reflect electromagnetic waves, thus degrading the functionality of conventional radio-frequency identification tags. This highlights the importance of conducting research into academic publications and patents to grasp the current advancements and challenges in this field, aiming to improve the applications of radio-frequency identification tags technology on metal. Consequently, this research undertakes a concise review of both the literature and patents exploring radio-frequency identification technology’s use for on-metal tags, utilizing resources like Google Scholar and Google Patents. The research categorized crucial aspects such as tag flexibility, operating frequency, and geographic origins of the research. Findings highlight China’s prominent role in contributing to metal-focused radio-frequency identification tag research, with a considerable volume of articles and patents. In particular, flexible tags and the Ultra-High Frequency range are dominant in both scholarly and patent documents, reflecting their significance in radio-frequency identification technology applications. The research underscores a vibrant area of development within radio-frequency identification technology, with continued innovation driven by specific industrial needs. Despite the noted advances, the presence of a significant percentage of no longer valid patents suggests substantial opportunities for further research and innovation in radio-frequency identification technology for on-metal applications, especially considering the demand for flexible tags and for solutions in systems that offer specialized characteristics or are tailored for specific uses.

A Novel Active RFID and TinyML based system for livestock Localization in Pakistan

Localization of livestock is a vital component of good livestock management in Pakistan. This abstract describes a unique method for livestock localization in Pakistan that makes use of Active RFID technology and Tiny Machine Learning (TinyML) approaches. The incorporation of Active RFID technology allows for precise and long-range livestock tracking, while TinyML provides on-device analysis and decision-making. This method has a number of advantages, including high precision, real-time localization, and less reliance on external infrastructure. Accurate triangulation-based localization is obtained by putting Active RFID tags on cattle and carefully positioning Active RFID anchors in specific regions. TinyML integration on resource-constrained microcontrollers within Active RFID tags allows for efficient on-device analysis of Active RFID signals. The suggested system has the potential to significantly improve livestock management practices in Pakistan, including animal tracking and monitoring, behavior analysis, and increased animal welfare. To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies

A constructive Steiner graph matching for Radio frequency identification device tag detection in wireless and internet of things environment

SummaryRadio frequency identification device (RFID) has emerged as one of the most potential building blocks for future IoT‐enabled technologies. Various applications like logistic monitoring use the RFID system to deal with the tagged objects. RFID‐based tracking approach is extremely solicited for appropriate logistic distribution because of the frequent tagged‐objects rearrangements. Nevertheless, with an RFID system, one of the most significant issues is resolving collisions between tags as they transfer data to the reader at the same time. This work investigates the core issue of locating all lost tags in RFID systems. The most significant factor in missing tag recognition is to reduce the time required for execution. A problem needs to be formulated to differentiate the tagged objects' motion state, that is, static or dynamic, to handle this issue. It tracks the moving objects with various existing localization approaches. Finally, a tag detection known as constructive Steiner graph matching (CSGM) detection is proposed to achieve time efficiency by utilizing RFID collision signals. Specifically, the physical‐layer features are considered for differentiating the positions. Experimental outcomes demonstrate that the anticipated model can attain better prediction accuracy by reducing inventory time compared to other approaches. Simulation findings show that the suggested approach performs exceptionally well in giving a significant performance boost in an RFID system. It minimizes the complexity of tracking the objects. The simulation outcomes illustrate that the algorithm's identification speed is substantially enhanced and ensuring high system efficiency. The simulation results of the proposed algorithm have been improved in terms of system efficiency (9.5%), success rate (6.3%), and identification speed (4%) compared to the conventional algorithm. The suggested CSGM technique's average waiting time is decreased by more than 45.372%, and its detection speed is increased by at least 38.219% compared to other existing algorithms.

Early larval exposure to flumethrin induces long-term impacts on survival and memory behaviors of adult worker bees Apis mellifera

Flumethrin has been supplied as an acaricide for Varroa mite control in world-wide apiculture due to its low lethal effects on honey bees. However, little is known about the effects of short-term flumethrin exposure in the larval stage on adult life stage of bees involving survival status, foraging and memory-related behaviors. Here, we found that exposure to flumethrin at 1 mg/L during larval stage reduced survival and altered foraging activities including induced precocious foraging activity, decreased foraging trips and time, and altered rotating day-off status of adult worker bees using the radio frequency identification system. Furthermore, larval exposure at 1 mg/L flumethrin influenced the correct proboscis extension responses of 7-day-old worker bees and decreased homing rates of 20-day-old worker bees, suggesting that 1 mg/L flumethrin exposure at larval stage could affect memory-related behaviors of adult bees; meanwhile, three genes related to memory (GluRA, Nmdar1 and Tyr1) were certainly down-regulated varying different flumethrin concentrations (0.01, 0.1, and 1 mg/L). Combined with transcriptomic sequencing, differentially expressed genes involved in olfactory memory of adult bees were completely down-regulated under flumethrin exposure. Our findings highlight the unprecedented impact of short-term exposure of insecticides on honey bees in long-term health monitoring under field conditions.

Review of Metal-Resistant Structures for Radio Frequency Identification Tag Antennas

Amidst the rapid expansion of e-commerce and the consequential surge in industries such as transportation, logistics, and supply chain management, there has been remarkable growth. Radio Frequency Identification (RFID) technology, along with its associated tags, plays a pivotal role in the transmission and tracking of crucial information within these sectors. However, the presence of metallic components within RFID systems poses a significant obstacle to efficient antenna transmission. Consequently, there is a pressing need for the development of RFID tag antennas endowed with metal-resistant properties. This paper undertakes a comparative analysis of existing designs and structures for metal-resistant RFID tag antennas, providing valuable insights into their prospective developmental trajectories and potential applications. Such analysis serves as a pertinent reference for research and engineering endeavors across related domains.

Online feeding behavior monitoring of individual group-housed grow-finish pigs using a low-frequency RFID electronic feeding system.

Early identification of animals in need of management intervention is critical to maximize animal health and welfare and minimize issues with productivity. Feeding behavior, captured by automated feeding systems, can be used to monitor the health and welfare status of individual pigs. Here, we present a framework for monitoring feeding behavior of grow-finish pigs in real time, using a low-frequency radio frequency identification (RFID) system. Using historical data, an autoregressive linear model for predicting daily time at the feeder was developed and utilized to detect anomalous decreases in feeding behavior associated with health status of the pig. A total of 2,826 pigs were individually monitored with our warning system over the entire grow-finish period, and health warnings were compared to caretaker diagnoses. The system detected 55.7% of the caretaker diagnoses, and on average these events were detected 2.8 d earlier than diagnosis by the caretaker. High numbers of potentially spurious health warnings, generated by the system, can be partly explained by the lack of a reliable and repeatable gold standard reference data set. Results from this work provide a solid basis for monitoring individual animals, but further improvements to the system are necessary for practical implementation.

Enhanced Security and Efficiency in Attendance Management: A Novel RFID and Arduino Integrated System

The advent of Radio Frequency Identification (RFID) technology has ushered in a new paradigm in the domain of automated attendance systems, offering a sophisticated yet user-friendly approach to personnel management. This paper presents a comprehensive study on the design and deployment of an RFID-based attendance system powered by the versatile Arduino platform, elucidating its operational tenets, system architecture, and practical implementations. At the heart of the system lies the MFRC522 RFID reader, which synergizes with an Arduino microcontroller to facilitate the identification and logging of attendance data. The system is enhanced by the inclusion of an SD Card Module for data storage and a Real-Time Clock (RTC) Module to ensure accurate timestamping of attendance events. The seamless integration of these components results in a robust mechanism that not only simplifies the attendance tracking process but also fortifies the security framework by leveraging unique identifiers for each user. The study spans the detailed process of assembling the hardware, crafting the software in the Arduino Integrated Development Environment (IDE), and meticulously testing the integrated system to affirm its efficacy. The resulting attendance system embodies a significant stride towards refining attendance management practices, eliminating the shortcomings of manual tracking while providing a scalable and reliable solution adaptable to various organizational settings.

A machine learning approach for package size estimation using UHF RFID interrogation signature

This paper introduces a new approach for performing package classification and sizing using Radio-Frequency Identification (RFID) systems. This technique is applicable when packages are labeled with or contain multiple RFID-tagged items. During the interrogation of the tags, received signal strength (RSS) statistics and other information, such as the frame count or the reading time, are collected by the reader and used to predict the package type from a set of candidate classes using an Artificial Neural Network (ANN). The primary challenge lies in acquiring sufficient training data for a target scenario to ensure reliable predictions. To address this, a two-phase training process based on transfer learning is adopted. Initially, a base model is developed using synthetic data generated from a detailed RFID simulator, designed to suit diverse scenarios, establish detailed link budgets, and comprehensively simulate the communication protocols. This model is then refined using a small dataset collected experimentally in the actual scenario. This method was validated in a real testbed with four different package types. The base model was trained using 1000 synthetic samples per package type (4000 in total), whereas the refined model was trained with a dataset consisting of only 25 real interrogation traces (samples) per package type (100 in total). The experimental samples were obtained using a software-defined radio unit, the Ettus B210 Universal Software Radio Peripheral (USRP) platform. This experiment achieved an accuracy of over 92%. In summary, this approach introduces a new feature to existing RFID setups, demonstrating potential for advanced package handling and cost optimization in the logistics sector.