Passive Radio Frequency Identification Tags Research Articles

Design of Provably Secure and Lightweight Authentication Protocol for Unmanned Aerial Vehicle systems

Drones also called Unmanned Aerial Vehicles (UAVs) have become more prominent in several applications such as package delivery, real-time object detection, tracking, traffic monitoring, security surveillance systems, and many others. As a key member of IoT, the group of Radio Frequency IDentification (RFID) technologies is referred to as Automatic Identification and Data Capturing (AIDC). In particular, RFID technology is becoming a contactless and wireless technique used to automatically identify and track the tagged objects via radio frequency signals. It also has drawn a lot of attention among researchers, scientists, industries, and practitioners due to its broad range of real-world applications in various fields. However, RFID systems face two key concerns related to security and privacy, where an adversary performs eavesdropping, tampering, modification, and even interception of the secret information of the RFID tags, which may cause forgery and privacy problems. In contrast to security and privacy, RFID tags have very limited computational power capability. To deal with these issues, this paper puts forward an RFID-based Lightweight and Provably Secure Authentication Protocol (LPSAP) for Unmanned Aerial Vehicle Systems. The proposed protocol uses secure Physically Unclonable Functions (PUFs), Elliptic-Curve Cryptography (ECC), secure one-way hash, bitwise XOR, and concatenation operations. We use Ouafi and Phan’s formal security model for analyzing security and privacy features such as traceability and mutual authentication. The rigorous informal analysis is carried out which ensures that our proposed protocol achieves various security and privacy features as well as resists various known security attacks. The performance analysis demonstrates that our proposed protocol outperforms other existing protocols. In addition, Scyther and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool simulation results demonstrates that there is no security attack possible within bounds. Therefore, our proposed LPSAP protocol achieves an acceptable high level of security with the least computational, communication, and storage costs on passive RFID tags.

Power Consumption Efficiency of Encryption Schemes for RFID

This paper provides a comparative analysis of AES (Advanced Encryption Standard) and Salsa20 algorithm implementations, focusing on power consumption efficiency in passive RFID (radio-frequency identification) tags and ultra-low-power devices. The main objective of this work is to determine which of these algorithms is more suitable to operate in these types of devices. For this purpose, ASIC (application-specific integrated circuit) implementations of AES and Salsa20 based on low-power approaches were developed and their power consumption was evaluated. The results demonstrate that Salsa20 power consumption is lower than AES (about 17%), indicating that Salsa20 is a much better choice than AES for passive RFID tags.

An improvised analysis of smart data for IoT-based railway system using RFID

RFID (radio frequency identification) is a progressively adopted technology in today’s automated world. Wireless technologies have enabled contactless payments, tracking, identifying, and many more features in a system that can be introduced to build a smart environment. This work overviews the usage of the IoT (Internet of Things) platform for tracking passengers and enabling online payments through wireless sensors and RFID technology in Chennai Suburban Railways. The tracking system consists of an RFID reader that can locate and track passive as well as mobile objects attached with passive RFID tags. The proposed system incorporates the installation of RFID readers at every entrance and exit of the railway station, and every passenger carries their own RFID tags. This not only enables online payments for passengers but also helps the government in tracking the crowd for demand monitoring. The new methodology creates a digital workspace and enforces lawful safety regulations both for the administration and the consumers. A prototype of the proposed system is implemented in real-time to understand the workings of the system. Data collection is done through RFID tags that act as transit cards and an analysis for consumer demand is done using the DBSCAN (Density-Based Spatial Clustering of Application with Noise) algorithm with a Randomized KD-tree for the analysis of spatial and temporal patterns. A new algorithm, the iDBSCAN (improved Density-Based Spatial Clustering of Application with Noise) algorithm is proposed for faster performance on the datasets.

RFID BASED SMART LIBRARY

Library circulation is low because of the tedious and time-consuming nature of the institution's traditional management. In addition to being waterproof and anti-magnetic, the Radio Frequency Identification (RFID) labels can be encrypted, have a huge storage capacity, and more. Using RFID as a foundation, we develop a comprehensive system architecture that takes into account the hardware and software requirements of the university library. The RFID system streamlines library operations by adding intelligence and automation. Using RFID middleware, the system is able to integrate RFID and library management in a natural way, resulting in a library management system that is both efficient and scalable. In order to demonstrate the system's overall functionality and each of its sub-functions, the use case diagram is a ground breaking concept. System for managing libraries and identifying books via radio frequency (RFID) The proposed system is based on RFID readers and passive RFID tags that are able to electronically store information that can be read with the help of the RFID reader. This system would be able to issue and return books via RFID tags and also calculates the corresponding fine associated with the time period of the absence of the book from the library database

Performance evaluation of a UHF passive RFID tag embedded in a carbon fibre-reinforced polymer

Data collection during the production process plays a key role in the management and control of goods within the company. In this work, the main focus is on the possibility of embedding radio frequency identification (RFID) technology in carbon-fibre reinforced polymer (CFRP) components to evaluate the readability of commercial Ultra High Frequency system by varying their covers, which is also partly in CFRPS. The samples produced and the tags used derived on previous studies, in which configurations with the tag housed inside were established and studied. Two RFID tags were studied that could withstand the harsh environmental conditions, i.e., high temperatures and pressure. This work was not carried out in an ideal environment to assess the theoretical capabilities of RFID sensors, but to understand and evaluate the readability limits of commercial RFID tags embedded in CFRPs. Therefore, an experimental campaign was undertaken to assess the downstream readability of the curing process of tags in laminated mock-ups. It was observed that the curing process had minimal effect on the readability of the tags. Free-space tests were carried out in proximity of metallic elements to determine the change of the reading distance obtained during the test, keeping the fixed antenna used constant.

Towards a Digital Twin Warehouse through the Optimization of Internal Transport

Through the construction of parametric simulation models in which possible storage space distributions and positioning logics are also considered as variables, it is possible to build scenarios that allow analyzing the changing reality of storage needs in order to minimize material movements in each case, optimize internal transportation, and increase the efficiency of production processes. This article shows a particular analysis of a restricted storage space in height, typical to when it comes to logistics associated with raw material in a “big bag” format made of recycled and easily deteriorated material. In conjunction, a location management solution based on passive RFID (radio-frequency identification) tags has been chosen. The process is carried out through simulations with object-oriented discrete event software, where the optimization of the internal transport associated with the layout is carried out considering network theory to define the shortest path between warehouse nodes. The combination of both approaches allows, on the one hand, the evaluation of alternatives in terms of distribution and positioning logics, while the implemented system enables the possibility of making agile changes in the physical configuration of this type of storage space.

A Multibranch U-Shaped Tunable Encoding Chipless RFID Strain Sensor for IoT Sensing System

Structural health monitoring (SHM) is essential for modern large buildings and infrastructure. Radio frequency identification (RFID) widen a new paradigm for SHM in the Internet of Things (IoT) era. This article introduces a low-cost intelligent RFID monitoring system for future IoT applications. Through adding a multiparameter sensing strategy to the passive RFID tags that can be deployed on a large scale to form a sensor network, which expands the coverage of IoT in key positions health monitoring of buildings. In this work, a novel chipless RFID strain sensing tag is designed to characterize the magnitude and direction of metal surface strain, and a low-cost detection method suitable for large mechanical structures is proposed. The traditional strain antennas focus on identifying the strain characteristics without the function of encoding, and there are limitations, such as the rigid measurement methods and the expensive measurement instruments. The tag designed in this article integrates both strain sensing and encoding functions, and has the advantages of small size, high data capacity, and information reading is not easily affected by environmental noise. This article proposes an economical and flexible tag spectrum extraction method, which realizes the intelligent collection and transmission of tag data by connecting lightweight vector network analyzer (VNA) with microcontroller. Combined with the IoT, this method can be well applied to the security assessment and damage detection of large infrastructure structures, which provides a new approach to modern building health monitoring applications from integrated tag design to intelligent detection and risk assessment schemes.

Utilizing Random Forest with iForest-Based Outlier Detection and SMOTE to Detect Movement and Direction of RFID Tags

In recent years, radio frequency identification (RFID) technology has been utilized to monitor product movements within a supply chain in real time. By utilizing RFID technology, the products can be tracked automatically in real-time. However, the RFID cannot detect the movement and direction of the tag. This study investigates the performance of machine learning (ML) algorithms to detect the movement and direction of passive RFID tags. The dataset utilized in this study was created by considering a variety of conceivable tag motions and directions that may occur in actual warehouse settings, such as going inside and out of the gate, moving close to the gate, turning around, and static tags. The statistical features are derived from the received signal strength (RSS) and the timestamp of tags. Our proposed model combined Isolation Forest (iForest) outlier detection, Synthetic Minority Over Sampling Technique (SMOTE) and Random Forest (RF) has shown the highest accuracy up to 94.251% as compared to other ML models in detecting the movement and direction of RFID tags. In addition, we demonstrated the proposed classification model could be applied to a web-based monitoring system, so that tagged products that move in or out through a gate can be correctly identified. This study is expected to improve the RFID gate on detecting the status of products (being received or delivered) automatically.

Design of A 20-Bit Chipless RFID Tag Utilizing Multiple Resonators in UWB Frequency Range

Radio frequency identification (RFID) is a growing technology for monitoring and recognizing objects, persons, or animals via wireless communications. Precisely, RFID can operate longer range and has an ability to be automated without human control. Chipless RFID tag basically is a RFID tag that does not require a microchip in the transponder. The major impediments in designing chipless RFID tag are data encoding and transmission. The passive chipless RFID tag can be fabricated on any substrate material without external operating circuit, which is different compared to a conventional chipped RFID tag. In this paper, 20 resonators are used to design a 20-bit chipless RFID tag, which operates at the ultra-wideband (UWB) frequency range between 3.00 and 10.00 GHz. It is found that the additional resonators can encode data and increase the chipless RFID tag's encoding capacity significantly. In sum, multiple resonators enable the chipless RFID tag to encode data at different operating frequencies.

Deployment of Smart Specimen Transport System Using RFID and NB-IoT Technologies for Hospital Laboratory

In this study, we propose a specimen tube prototype and smart specimen transport box using radio frequency identification (RFID) and narrow band-Internet of Things (NB-IoT) technology to use in the Department of Laboratory Medicine, King Chulalongkorn Memorial Hospital. Our proposed method replaces the existing system, based on barcode technology, with shortage usage and low reliability. In addition, tube-tagged barcode has not eliminated the lost or incorrect delivery issues in many laboratories. In this solution, the passive RFID tag is attached to the surface of the specimen tube and stores information such as patient records, required tests, and receiver laboratory location. This information can be written and read multiple times using an RFID device. While delivering the specimen tubes via our proposed smart specimen transport box from one clinical laboratory to another, the NB-IoT attached to the box monitors the temperature and humidity values inside the box and tracks the box's GPS location to check whether the box arrives at the destination. The environmental condition inside the specimen transport box is sent to the cloud and can be monitored by doctors. The experimental results have proven the innovation of our solution and opened a new dimension for integrating RFID and IoT technologies into the specimen logistic system in the hospital.

Displacement Estimation Using 3D-Printed RFID Arrays for Structural Health Monitoring.

Radio frequency identification (RFID) tags are small, low-cost, wearable, and wireless sensors that can detect movement in structures, humans, or robots. In this paper, we use passive RFID tags for structural health monitoring by detecting displacements. We employ a novel process of using 3D printable embedded passive RFID tags within uniform linear arrays together with the multiple signal classification algorithm to estimate the direction of arrival using only the phase of the backscattered signals. We validate our proposed approach via data collected from real-world experiments using a unipolar RFID reader antenna and both narrowband and wideband measurements.

An AOA and Orientation Angle-Based Localization Algorithm for Passive RFID Tag Array

This paper proposes an indoor localization algorithm based on AOA (Arrive of Angle) and orientation angle (OA) for passive UHF RFID (Ultra-High Frequency Radio Frequency Identification) tag array. By utilizing a uniform linear tag array (ULA), the AOA, which is defined as the angle of the reader relative to the tag array, can be estimated by the Multiple Signal Classification (MUSIC) algorithm. The relationship between AOA, OA of the tag array, and the direction angle (DA) between each reader antenna to the geometric center of the tag array is analyzed, and an OA retrieval method based on rotating the coordinate system is proposed to calculate DA. The tag array localization is finally acquired by the DA of each antenna. Simulation and experiment results show that the proposed algorithm can achieve decimeter-level localization accuracy. The proposed algorithm achieves a mean accuracy of 0.216 m, which is a significant improvement compared with the traditional AOA localization algorithm.

Data dense chipless RFID tag with efficient band utilization

One of the critical challenges in deploying radio frequency identification (RFID) is its cost of production. An approach to mitigate and be cost-effective is to design chipless, inexpensive electronic tags having a smaller size. Therefore, in this paper, a novel 22-bit passive chipless RFID tag with an enhanced radar cross-section (RCS) response is proposed. The tag design is loaded with ‘U’ and ‘Inverted-U’ shaped slots. The ‘U’ and ‘Inverted-U’ slots are etched on a metallic plate of size 39x40 mm2 for 22-bit data capacity and the tag can label 222 = 4,194,304 objects. The final tag design is optimized for Taconic TLX-0 and RT/duroid®5880 substrates. Each 'U' and 'Inverted-U' shaped loaded slot are of different lengths and thus yield resonance at a particular frequency. The presence of a dip corresponds to the '1′ bit and the '0′ bit is achieved in the data word by shortening the particular slot. A detuning correction scheme is proposed by placing the slots in a special arrangement. By opting for this approach not only the tag exhibits an improved RCS response but also, the effect of shorted slot representing '0′ on the neighboring dip is reduced. The proposed RFID tag can be deployed in tracking inventory, logistics, and low-cost business applications.

Efficient localization in warehouse logistics: a comparison of LMS approaches for 3D multilateration of passive UHF RFID tags

The Fourth Industrial Revolution, or Industry 4.0, aims at automating traditional manufacturing and industrial practices using modern smart technology. Autonomous mobile robots equipped with different sensors and employing different techniques have been proposed in the literature in the logistics and inventory warehouse management contexts. Efficient robot motion and planning depend on precise localization, mapping, and awareness of the environment. To properly localize items, recent attempts have been made employing radio frequency identification (RFID) in a 3D environment. This manuscript introduces four least mean squares methods to estimate the 3D positions of tags employing synthetic apertures and phase unwrapping. The proposed methods approach the localization problem solving a system of equations typical of multilateration methods to find the intersections of multiple hyperboloids. The novelty introduced here is the use of unwrapped phase distances to compute pseudo ranges for the multilateration problem. The use of such a technique is feasible thanks to precise mobile robot localization and custom navigation policies. All the analyzed methods are suitable for online localization due to reduced computation timings and have been tested on three different datasets. Two of them contain virtual data that has been generated by simulation, while the other one comes from an indoor experimental setup. Simulated tests show that combined antenna motions in 3D space (including Z-axis) improve the localization obtaining errors under the centimeter for 3D localization. Experimental tests obtained results as low as 13 cm of mean accuracy for 3D localization and 0.21 cm for 2D localization.

Self-aligning roly-poly RFID tag

Radio frequency identification (RFID) is a mature technology that allows contactless data readout via a wireless communication link. While numerous passive RFID tags are available on the market, accurate alignment between tags and readers is required in a vast majority of cases to mitigate polarization mismatches. We show that enhancing electromagnetic designs with additional mechanical degrees of freedom allows bypassing fundamental limitations and approach ideal performances. Here, we demonstrate a new miniature tag, accessible from any direction and immune to rotations in space. Our tag is made of a high permittivity ceramic resonator, inductively coupled to a metal ring, which contains an RFID chip. The structure is placed inside a spherical plastic holder. In this architecture, the ceramic resonator serves several functions. First, it allows reducing the device footprint without significant bandwidth degradation. Second, it acts as a bob, aligning the electromagnetic structure parallel to the ground, regardless of its initial orientation in space. The bob is designed to slide inside the plastic holder. This roly-poly effect relaxes the constraint on a mutual tag-reader orientation, including the polarization mismatch, and provides next to perfect long-range operation. Being only 55 mm in diameter, our device can be interrogated from a 12 m distance, regardless of the tag’s orientation in space. Introducing mechanical degrees of freedom into electromagnetic designs allows obtaining new functionalities, contributing to applications where a mutual orientation between transvers is required.

Chipless RFID Sensors for Wearable Applications: A Review

Radio frequency identification (RFID) is a quickly growing innovative wireless data capturing technology for automatic identification, product tracing, security investigation, automatic toll fee, vehicle tracking, and e-Health. Wearable sensing technology and on-body structures have achieved pervasive responses due to their fabulous potential in the Internet of Things (IoT), healthcare, and smart homes. Inexpensive chipless RFID tags for on-body sensing are the upcoming research for such wearable devices. Its sensing skill offers the unified real-time monitoring of vital signs. This paper reviews various chipless passive RFID tag sensors for wearable applications. The main goal of this research work is to study the basics of chipless RFID sensors and their working principles. Further, chipped RFID sensors are very costly for mass implementation. Hence, chipless tag sensors have grown into a cost-effective and maintenance-free substitute, fulfilling the requirements of the society for the emergent technologies, where lots of these sensors can be used. Understanding the importance in emerging applications, essential materials needed for different sensors, basic circuit models for chipped and chipless sensors, and challenges with limitation of recent chipless RFID sensors are also discussed in this article.

A new methods of mobile object measurement by using radio frequency identification

In this study, the mobile robot conducts tag of RFID and the antennas’ reader was scattered at the indoor-outdoor environment, which represents the novelty of the study, as this has not been done in the previous studies. This protects the mobile robot from weight increase reduces the consumption of the battery. Moreover, mobile object increase demands an increase in cheap passive Radio Frequency Identification tags in the system of navigation. Techniques of Signal processing utilize both accompanied by the theories of electromagnetics in locating the robot’s position. Numerous antennas usage provides a breadth of comparisons. In this work, have been provide a new RFID tracking approach that can also be used for interior positioning. This technique employs RSS to gather the signal intensity of reference tags before they are used. The next step is to send a signal. Setting up Power Level ranges via reference tags uses strength as a setting parameter. Then, based on the intensity of the signal, you can determine how far away you are. Reference tags are used to match the signal intensity of track tags. Finally, when track tags are installed in indoor locations, they can be used to monitor the movement of people. It will use the arithmetic mean of the positions of surrounding reference tags to determine the location. Values. According to preliminary results from an experiment, our approach is more precise than the antenna system. Approximately 10 to 20 lines.

BER-Aware Backscattering Design for Energy Maximization at RFID Passive Tag

AbsThe radio frequency identification (RFID) passive tag is wireless communication device with high energy sustainability, such that it uses the incident radio frequency (RF) signal to backscatter its information. This paper investigates the output load power maximization with optimal load impedances selection in the backscatter communication (BackCom) network. The considered BackCom system comprises a reader broadcasting an unmodulated carrier to the passive tag in the downlink. The tag backscatters its information signal to the reader with binary amplitude-shift keying (BASK) modulation in the uplink. We formulated an average output load power maximization problem by jointly optimizing the reflection coefficients while satisfying the minimum bit error rate (BER) requirement and tag sensitivity constraint. To simplify the problem, we transform the BER constraint to the modulation index constraint and reduce the 4 variables problem to 2 variables convex optimization problem. Using the Karush-Kuhn-Tucker (KKT) conditions, we design an algorithm to obtain the closed-form expression for the global optimal reflection coefficients that maximize the output load power. The simulation results provide insight into the impact of the information bit probability, tag sensitivity constraint, and BER on the achievable average load power. An overall gain of around 16% signifies the utility of our proposed design.

Hybrid Power Divider and Combiner for Passive RFID Tag Wireless Energy Harvesting

This paper presents three- and five-ports radio frequency (RF) hybrid power divider combiner (HPDC) designs with multiband characteristics operating at 2.4 GHz (ISM, IEEE 802.11b,g); 5.8 GHz (IEEE 802.11n, a and 802.11ac); and 6 GHz (IEEE 802.11ax) wireless standards for energy-efficient 5G-enabled passive Internet of Things (IoT) sensors; energy harvesting (E.H); passive radio frequency identification (RFID) tags; multiple-input multiple-output (MIMO) antenna beamforming; and data communication applications spanning DC to the 6-GHz frequency range. The presented HPDC designs operate at a centre-design frequency of 3 GHz on a Rogers RO4350 substrate. The designed novel HPDC demonstrates a good match between the ports, high isolation between the output ports, and equal power distribution between the output ports. Furthermore, the obtained return and isolation losses are less than −10 dB for the Wi-Fi 6E standards. The reported findings hold an excellent promise for RF energy harvesting and utilisation, adaptive intelligent energy-efficient data communication, and seamless ubiquitous satellite-cellular convergence connectivity applications.

A Dynamic Multi-ary Query Tree Protocol for Passive RFID Anti-collision

In this paper, a dynamic multi-ary query tree (DMQT) anti-collision protocol for Radio Frequency Identification (RFID) systems is proposed for large scale passive RFID tag identification. The proposed DMQT protocol is based on an iterative process between the reader and tags which identifies the position of collision bits through map commands and dynamically encodes them to optimize slots allocation through query commands. In this way, the DMQT completely eliminates empty slots and greatly reduces collision slots, which in turn reduces the identification time and energy costs. In addition and differently to other known protocols, the DMQT does not need to estimate the number of tags, reducing the protocol implementation complexity and eliminating the uncertainty caused by the estimation algorithm. A numerical analysis shows that DMQT has better performance than other algorithms for a number of tags larger than 300. Meanwhile, when the number of tags is 2000 and the tag identity (ID) length is 128 bits, the total identification time is 2.58 s and the average energy cost for a tag identification is 1.2 mJ, which are 16.9% and 10.4% less than those of state-of-the-art algorithms, respectively. In addition, a DMQT extension based on ACK command has also been presented to deal with capture effect and avoid missing identification.