Traditional Radio Frequency Identification Research Articles

Comprehensive Review on Multiresonator-Based Chipless RFID Tag

This study reviews the multi-resonator-based chipless radio frequency identification technology. Radiofrequency (RF) waves are used in a wireless data collecting technique called radio frequency identification or simply RFID to automatically identify things. RFID is a promising technology that enables the identification and tracking of objects. Because of its benefits, including cheaper cost, smaller size, and higher security, chipless Radio Frequency Identification (RFID) technology has become more and more attractive as a potential alternative to traditional RFID technology. Chipless RFID labels are minimal expense labels since they are not outfitted with ASIC. RFID transmits data between the RFID transponder, a device that carries data, and the interrogator using radio frequency (RF) waves. The system is completely passive and does not require any kind of outside power source to run. The major advantage of spectral signature-based chipless RFID is that it can encode data in both magnitude and phase. A transponder's essential parts are its transmitter, receiver, and multi-resonators. As a result, this article will evaluate different multi-resonator types, explore numerous chipless RFID applications, and discuss the basic operation of an RFID system. Additionally, this research studies the various coding systems because information coding is an essential part of this technology.

Review on Recent Advances and Applications of Passive Harmonic RFID Systems.

Radio frequency identification (RFID) has gained significant attention because it provides a highly versatile platform for identifying, tracking, and monitoring objects. An emerging trend in this technology is the use of nonlinear RFID, such as passive harmonic tags, which have been demonstrated to be effective against clutters, echoes, crosstalk, and other electromagnetic interferences. This article presents a comprehensive review of recent advances and applications of passive harmonic RFIDs and integrated systems. A passive harmonic RFID exploits the frequency orthogonality of the transmitted (fundamental tone) and received (harmonics) radio-frequency (RF) signals to enable robust interrogation in noisy and cluttered environments, not possible with traditional passive linear RFIDs. This review article evaluates passive harmonic RFID systems in comparison to traditional systems and highlights their pros and cons. Several state-of-the-art chipless and chip-based harmonic RFIDs are presented, and their novel applications in identification, tracking, sensing, and biotelemetry are discussed. The review summarizes the key successes and challenges of passive harmonic RFID systems and provides insights into their future development, implementation, and optimization.

Radio Frequency Identification target location based on the Unmanned Aerial Vehicle

Due to the complex environment, the traditional Radio Frequency Identification (RFID) localization algorithm is cumbersome, the system localization accuracy is low, and the calculation time is relatively complex, an RFID localization algorithm based on sequential Kalman filtering has been proposed in this paper. Through the flight of sequential points, The Unmanned Aerial Vehicle (UAV) with the reader collects the Received Signal Strength Indication (RSSI) data dealt with mixed filtering of the target in the scene, after obtaining the coordinates according to the three-ball intersection method, and then using the Unscented Kalman Filter (UKF) algorithm to generate the estimation equation, thereby determining the position trajectory information to estimate. The results show that compared with other positioning methods the system has higher mobility and improved positioning accuracy with an average of 13.15%. At the same time, due to the real-time and flexibility of drones, this system can also be applied to more diverse scenarios. And the algorithm operation time is 1.15 s and it is suitable for UAVs scenarios.

UHF RFID Indoor Localization Algorithm Based on BP-SVR

With the widespread of Internet of Things (IoT), Radio Frequency Identification (RFID) technology is used in various fields. In the complex indoor environment, the traditional RFID indoor localization algorithm cannot give superior performance. Because a large number of antennas cannot be deployed in practical applications, the dimension of the signal strength feature vector obtained is relatively low, and it is not easy to fully describe the information in the environmental field. Thus, must adopt the appropriate antenna placement structure, the phase difference information can be effectively used as the feature. In this paper, a method of indoor localization algorithm based on Back Propagation–Support Vector Regression (BP-SVR) is proposed, which takes the signal strength and phase difference of the RFID tag as the feature inputs and uses the hidden layer of the neural network to enhance the dimensionality of the data. Moreover, the Sequential Minimal Optimization (SMO) algorithm is used to increase the rate of model learning. The method was valid in a 2D scene. Experimental results show that the method has an average positioning error of 9.5cm in the indoor area of 6m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 8m.

RFID-based 3D human pose tracking: A subject generalization approach

Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosensory games, and human-computer interaction. However, vision-based pose tracking techniques usually raise privacy concerns, making human pose tracking without vision data usage an important problem. Thus, we propose using Radio Frequency Identification (RFID) as a pose tracking technique via a low-cost wearable sensing device. Although our prior work illustrated how deep learning could transfer RFID data into real-time human poses, generalization for different subjects remains challenging. This paper proposes a subject-adaptive technique to address this generalization problem. In the proposed system, termed Cycle-Pose, we leverage a cross-skeleton learning structure to improve the adaptability of the deep learning model to different human skeletons. Moreover, our novel cycle kinematic network is proposed for unpaired RFID and labeled pose data from different subjects. The Cycle-Pose system is implemented and evaluated by comparing its prototype with a traditional RFID pose tracking system. The experimental results demonstrate that Cycle-Pose can achieve lower estimation error and better subject generalization than the traditional system.

A collision-aware mobile tag reading algorithm for RFID-based vehicle localization

With the development of radio frequency identification (RFID) technology, RFID systems on roads (RSR) have recently been put forward to localize not only manned vehicles but also autonomous vehicles. In such an RFID-based localization infrastructure, passive RFID tags with road-related information are deployed on road surfaces, and any vehicle equipped with an RFID reader can interrogate the tags to obtain its locations. However, like traditional RFID systems, reader collisions could occur when many vehicles (readers) continuously move in and out of a tag’s reading range, significantly degrading tag reading performance. Although many anti-collision algorithms have been devised to improve tag reading efficiency, none can be applied in highly mobile and dynamic road environments. In this paper, we propose an adaptive mobile tag reading algorithm, which can effectively reduce reader collisions and improve tag reading efficiency for reliable vehicle localization under various traffic scenarios. Extensive simulation and experiment have verified the feasibility and the effectiveness of our proposed scheme. Particularly, the field tests demonstrate that, with moderate vehicle density and sparsely deployed tags, our proposed algorithm can satisfy the tag reading requirements specified by the upper-layer localization system with a probability as high as 0.976.

A Novel Antenna for UHF RFID Near-Field Applications

This paper proposed a novel antenna for ultra-high frequency (UHF) radio frequency identification (RFID) near-field applications with uniform distribution of the electric field along the x-axis (Ex), and the y-axis (Ey). The proposed antenna adopted a spiral structure to achieve broadband and multi-polarization. The novel antenna achieved good impedance matching within 860–960 MHz. Using a ground plate, the proposed antenna achieved low far-field gain and a maximum gain of less than −11 dBi. The component of the excited electric field Ex and Ey parallel to the antenna surface was uniformly distributed, and there was no zero point. The proposed antenna achieved a 100% read rate of tags parallel to its surface in the reading area of 150 mm × 150 mm × 220 mm. Simulation results were consistent with the results of real-world measurements, and the proposed antenna was suitable as a reader antenna in near-field applications. The polarization mode of RFID tags is mostly linear polarization, and the placement of tags in practical applications is diversified. Compared with the traditional RFID reader antenna, the proposed antenna achieves uniform electric field distribution parallel to the antenna surface, but the single-direction electric field has zero-reading points, which is easy to cause the misread of tags. The RFID tags can be read more accurately. To verify the scalability of the reading area of the spiral antenna unit, it was used for array design, and simulations were conducted using 1 × 2, 2 × 2, 1 × 4, and 2 × 4 arrays. The component distribution of the electric field excited by the four array antennas in the x and y directions was uniform and the reading area was controllable. Therefore, the proposed spiral antenna has the expandability of the reading area and can meet the needs of different application scenarios by changing the number of array units. With the array extension, the matching network also extends, and the impedance characteristics of the array antenna are somewhat different, but they also meet the application requirements.

Super lightweight mobile RFID authentication protocol for bit replacement operation

In the traditional RFID (Radio Frequency IDentification) system, a secure wired channel communication is used between the reader and the server. The newly produced mobile RFID system is different from the traditional RFID system, the communication between the reader and the server is based on a wireless channel, and the authentication protocol is suitable for traditional RFID systems, but it cannot be used in mobile RFID systems. To solve this problem, a mutual authentication protocol MSB (Most Significant Bit) for super lightweight mobile radio frequency identification system is proposed based on bit replacement operation. MSB is a bitwise operation to encrypt information and reduce the computational load of communication entities. Label, readers, and servers authenticate first and then communicate, MSB may be used to resistant to common attacks. The security analysis of the protocol shows that the protocol has high security properties, the performance analysis of the protocol shows that the protocol has the characteristics of low computational complexity, the formal analysis of the protocol based on GNY logic Gong et al. (1990) provides a rigorous reasoning proof process for the protocol.

Design of Multi-Functional Access Control System

Facial recognition is a biometric recognition technology that verifies identity using information about human facial features so it is used for access control systems. Current access control systems are implemented using traditional Radio Frequency Identification (RFID) technology or keys. Users must carry an access card or key and the access card or a key can be forgotten, lost or copied by others to use an access control system. This study proposes a multi-function facial recognition access control system that uses Python and Intelligence RFID. The system's facial recognition scheme uses Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) facial recognition algorithms. This addresses a problem with current facial recognition technology, which achieve good results for different facial models under different lighting conditions. To render the system more user-friendly and versatile, the system requires swiping and a password. The Intelligence RFID access control function uses a high frequency (13.56 MHz) and the ISO/IEC14443-3 protocol is used for data communication between the access card and the card reader. Using a dynamic binary search algorithm, the password is saved and read using an EEPROM. This study uses a combination of software and hardware to allow double confirmation, which increases the stability and accuracy of the system. The system designed in this paper not only improves security, but also has more flexible functions than other access control systems. This is a good example of other systems trying to implement more flexible validation.

Plus Shaped Chipless RFID Tag

Chip-less radio frequency identification (RFID) technology is capable for detecting, identification, and chasing for the future Internet of Things (IoT) systems and applications. The chipless RFID technology gives us the impression as a rising substitute of the traditional RFID tags and barcodes by encoding data from tags employing the radio frequency waves. The paper presents the design as well as simulation of chip-less Plus shaped RFID tags. The structure is composed of Rogers RT/Duroid 5880 by means of a substrate having the physical dimensions 40mm x 40mm over which eight resonators are placed. This tag is compact, and the resonators are closely placed. The tag is designed using Ansys Electronics Desktop.

A Physical Layer Security Enhancement Scheme under the Ambient Backscatter System

In this paper, we proposed a scheme that Injects artificial noise from the tag end (IANT) to enhance the physical layer security of the ambient backscatter communication (ABC) system. The difference between the ABC system and the traditional radio frequency identification system is whether it uses the radio frequency (RF) signals in the environment to supply energy and modulation information for passive tags. In the IANT scheme, we select the best tag to communicate with the reader according to the channel quality between tags and reader, and at the same time select another tag to generate artificial noise that affects the receiving effect of the eavesdropper. This paper uses the method of generating noise copies in the reader to reduce the interference of artificial noise on the signal received by the reader. The simulation results show that with the increase in channel quality between tags and reader and the increase in the number of tags, the proposed IANT scheme is significantly superior to the contrast scheme in terms of system achievable secrecy rate, effectively enhancing the physical layer security of the ABC system.

RFID Implementation in Supply Chain Management

A network that is based on a traditional telecommunications network and the Internet is known as the internet of things (IoT). The devices in such networks connect peers and form advanced collaborations. radio frequency identification (RFID) has become a hot topic in recent years with the development of the IOT. However, the traditional RFID reader systems have some drawbacks, such as: single node failure, limited effective reading distance of the reader, and slow reading speeds. The proposed system describes how to estimate the location of an object using RFID technology. This article also incorporates a peer-to-peer (P2P) system to locate individual objects in a supply chain management network, which enables scalable indexing of objects in large distributed traceable networks.

SKINNY-Based RFID Lightweight Authentication Protocol

With the rapid development of the Internet of Things and the popularization of 5G communication technology, the security of resource-constrained IoT devices such as Radio Frequency Identification (RFID)-based applications have received extensive attention. In traditional RFID systems, the communication channel between the tag and the reader is vulnerable to various threats, including denial of service, spoofing, and desynchronization. Thus, the confidentiality and integrity of the transmitted data cannot be guaranteed. In order to solve these security problems, in this paper, we propose a new RFID authentication protocol based on a lightweight block cipher algorithm, SKINNY, (short for LRSAS). Security analysis shows that the LRSAS protocol guarantees mutual authentication and is resistant to various attacks, such as desynchronization attacks, replay attacks, and tracing attacks. Performance evaluations show that the proposed solution is suitable for low-cost tags while meeting security requirements. This protocol reaches a balance between security requirements and costs.

A Multitag Cooperative Localization Algorithm Based on Weighted Multidimensional Scaling for Passive UHF RFID

Radio frequency identification (RFID) technology, which is one of the important implementation ways of Internet-of-Things (IoT), has achieved much attention in indoor localization areas. Passive ultrahigh frequency (UHF) RFID tag localization has a great development recently. Most of traditional passive UHF RFID localization algorithms can only achieve the position of one tag at a time while multitag localization is desired in many RFID applications. In this paper, we proposed the weighted multidimensional scaling (WMDS) based on received signal strength (RSS) method and the tag-to-tag communication system to achieve multitag cooperative localization. The targets are marked with passive UHF RFID tags. RSS method is used to determine the distance between readers and target tags through channel models. We can also obtain the estimated distances between target tags by the tag-to-tag communication system. The estimated locations of the tags are determined by the calculation of Euclidean distance matrix through a few iterations. Simulation results show that the WMDS algorithm achieves higher localization accuracy than traditional algorithms and the cooperation between tags improves the localization accuracy.

Self-powered smart active RFID tag integrated with wearable hybrid nanogenerator

Radio frequency identification (RFID) technology is essential to construct the Internet of Things (IoT), which is significant to promote the blooming development of the new-generation information technology. RFID tags are widely used in many identification fields due to the non-contact, low-power-consumption and rapid feature for target recognition. However, the working distance of traditional passive RFID tags is extremely short at millimeter level in a limited direction range, since the power supply is passively delivered by an external electromagnetic radiation source. Moreover, the information transmission of traditional passive RFID tags is simplex in only one direction from RFID tag to the monitor, and in other words, the pre-stored information in passive RFID tags can only be passively detected by the monitor. Herein, a self-powered smart active RFID tag integrated with wearable hybrid nanogenerator is developed to overcome these drawbacks above. A new power supply strategy for RFID tags were proposed by the integration of a wearable nanogenerator based on the triboelectric-electromagnetic hybrid mechanisms, which can effectively convert the biomechanical energy into electricity to sustainably power RFID tags. The fabricated triboelectric-electromagnetic hybrid nanogenerator (TEHN) showed a remarkable performance with the maximum power density of 6.79 W/m2. A new transistors-controlled power management module (PMM) circuit of automatic parallel-series transformation of capacitors was proposed and also integrated to enhance the charging capability of TEHN by shortening 50% charging time. The integration of TEHN and PMM enable this active RFID tag to work autonomously with a 330-fold enhancement of working distance up to 33 m, and its working direction range is overcome to be omnidirectional. Furthermore, the developed active RFID tag can work in duplex communication mode to exchange the information with the monitor. This all-in-one self-powered smart active RFID tag was successfully demonstrated to remotely control the automatic door and be a wearable microsystem for ultra-large-area target recognition, which show an attractive potential in many application fields.

LILAC: computable capabilities based high performance protocol for CRFID

Compared with traditional radio frequency identification (RFID), computational RFID (CRFID) tag has more powerful computing capability, but it shows poor performance when it follows EPC Class-1 Generation-2 protocol especially transmitting large amounts of data. In fact, the operation of the CRFID tag entirely depends on the state of energy. For this point, this study proposes an optimised protocol called LILAC. LILAC allows tags to select the communication time slot according to their current voltage value measured by using an analogue-to-digital converter rather than randomly selecting, the authors proposed a more reasonable time slot mapping algorithm for LILAC that increases the success rate of tag responding. In addition, they design a data transmission format that can be retransmitted to improve the uplink throughput. Finally, they implemented LILAC on a CRFID platform and practically measured several parameters to compare with the existing well-known protocol. The results of experiments show that LILAC increases the maximum communication distance by more than half in the access phase and doubles the goodput of the backscatter link in both the inventory and access phase.

Multimodal student attendance management system (MSAMS)

Abstract Effective student attendance management in higher educational institutions represents a big challenge for faculty members that need fast and accurate approaches. The traditional attendance manual approach is prone to spoofing and wasting a lot of faculty/students time and poor accuracy especially in the case of large student numbers. This paper presents an effective solution for the real-time student attendance management problem in large lecture halls. Fast response time and high accuracy imply using high-speed technologies and processes for student identification. In this paper, Radio Frequency Identification (RFID) and novel face recognition and identification approaches have been proposed and evaluated. A multimodal approach for student identification combined the power of both the traditional RFID approach and Multi-Scale Structural Similarity (MS-SSIM) index. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the state-of-the-art approaches at a rate between 2% and 5%. In addition, it decreased the time three times if compared with the state-of-the-art techniques, such as Extreme Learning Machine (ELM). Finally, it achieved an accuracy of 99%.

Cloud-based radio frequency identification authentication protocol with location privacy protection

With the development of the Internet of things and cloud storage, a large number of objects access to the Internet through radio frequency identification technology, cloud-based radio frequency identification system attracts more attention because it can reduce the costs of system maintenance by renting the cloud storage service on demand. Especially, it is very suitable for the small- and medium-sized enterprises. However, the security and privacy issues of the cloud-based radio frequency identification system are more serious than traditional radio frequency identification systems. The link between the reader and the cloud is no longer secure, and the cloud service provider is not trusted. Both the location privacy of the reader and the data privacy of the radio frequency identification system are not able to be exposed to the cloud service provider. In this article, a cloud-based radio frequency identification authentication protocol is proposed. It considers not only the mutual authentication between the reader and the tag, but also the security of data transmission between the reader and the cloud database. In particular, in order to solve the reader’s location privacy problem, the proposed scheme introduces MIPv6 network framework without adding additional infrastructure. The experimental verification with AVISPA tool shows that the protocol satisfies the mutual authentication property. Compared with other cloud-based schemes, the proposed protocol has obvious advantages in deployment cost, scalability, real-time authentication, and the tag’s computational complexity.

An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor.

The Global Positioning System (GPS) is widely used in outdoor environmental positioning. However, GPS cannot support indoor positioning because there is no signal for positioning in an indoor environment. Nowadays, there are many situations which require indoor positioning, such as searching for a book in a library, looking for luggage in an airport, emergence navigation for fire alarms, robot location, etc. Many technologies, such as ultrasonic, sensors, Bluetooth, WiFi, magnetic field, Radio Frequency Identification (RFID), etc., are used to perform indoor positioning. Compared with other technologies, RFID used in indoor positioning is more cost and energy efficient. The Traditional RFID indoor positioning algorithm LANDMARC utilizes a Received Signal Strength (RSS) indicator to track objects. However, the RSS value is easily affected by environmental noise and other interference. In this paper, our purpose is to reduce the location fluctuation and error caused by multipath and environmental interference in LANDMARC. We propose a novel indoor positioning algorithm based on Bayesian probability and K-Nearest Neighbor (BKNN). The experimental results show that the Gaussian filter can filter some abnormal RSS values. The proposed BKNN algorithm has the smallest location error compared with the Gaussian-based algorithm, LANDMARC and an improved KNN algorithm. The average error in location estimation is about 15 cm using our method.

Towards balanced energy charging and transmission collision in wireless rechargeable sensor networks

By integrating sensing and computing capabilities into the traditional radio frequency identification (RFID) tags, the wireless identification and sensing platform (WISP) opens up a new research area referred to as wireless rechargeable sensor networks (WRSNs). Since WISPs need to be fully charged and then can start communication with the reader, thus the energy charging and transmission collision of WISPs are different from those of RFID tags. If the reader power is large, WISPs will be charged fast and start data transmission almost at the same time, which results in heavy transmission collision and the communication delay would be extremely large. However, if the reader power is small, WISPs will be charged slow and start data transmission one by one even without collisionh between any two WISPs, but the charging period of the whole network would be extremely large. Therefore, this paper aims at determining an optimal reader power towards balanced energy charging and transmission collision, such that the total duration for all WISPs to be fully charged and completely communicated is minimized. Firstly, we investigate on dynamic reader power with transmission collision avoidance, and static reader power towards balanced energy charging and transmission collision. Then, we derive the optimal reader power in three cases: (i) One reader and ray-uniformly distributed WISPs; (ii) one reader and randomly distributed WISPs; and (iii) multiple readers and randomly distributed WISPs. Finally, the theoretical analysis is verified through extensive evaluations.