Passive Ultra High Frequency Research Articles

Transparent RFID tag wall enabled by artificial intelligence for assisted living

Current approaches to activity-assisted living (AAL) are complex, expensive, and intrusive, which reduces their practicality and end user acceptance. However, emerging technologies such as artificial intelligence and wireless communications offer new opportunities to enhance AAL systems. These improvements could potentially lower healthcare costs and reduce hospitalisations by enabling more effective identification, monitoring, and localisation of hazardous activities, ensuring rapid response to emergencies. In response to these challenges, this paper introduces the TransparentRFIDTag Wall (TRT-Wall), a novel system taht utilises a passive ultra-high frequency (UHF) radio-frequency identification (RFID) tag array combined with deep learning for contactless human activity monitoring. The TRT-Wall is tested on five distinct activities: sitting, standing, walking (in both directions), and no-activity. Experimental results demonstrate that the TRT-Wall distinguishes these activities with an impressive average accuracy of 95.6%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$95.6\\%$$\\end{document} under four distinct distances (2, 2.5, 3.5 and 4.5 m) by capturing the RSSI and phase information. This suggests that our proposed contactless AAL system possesses significant potential to enhance elderly patient-assisted living.

Tag-free indoor fall detection using transformer network encoder and data fusion

This work presents a radio frequency identification (RFID)-based technique to detect falls in the elderly. The proposed RFID-based approach offers a practical and efficient alternative to wearables, which can be uncomfortable to wear and may negatively impact user experience. The system utilises strategically positioned passive ultra-high frequency (UHF) tag array, enabling unobtrusive monitoring of elderly individuals. This contactless solution queries battery-less tag and processes the received signal strength indicator (RSSI) and phase data. Leveraging the powerful data-fitting capabilities of a transformer model to take raw RSSI and phase data as input with minimal preprocessing, combined with data fusion, it significantly improves activity recognition and fall detection accuracy, achieving an average rate exceeding 96.5%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$96.5\\%$$\\end{document}. This performance surpasses existing methods such as convolutional neural network (CNN), recurrent neural network (RNN), and long short-term memory (LSTM), demonstrating its reliability and potential for practical implementation. Additionally, the system maintains good accuracy beyond a 3-m range using minimal battery-less UHF tags and a single antenna, enhancing its practicality and cost-effectiveness.

RETRACTED: Contactless human activity and sport action identification based on UHF RFID tag wall and AI

The existing approaches to activity assisted living(AAL) are complex, expensive, and intrusive, which reduce theirpracticality and end-user acceptance. However, advancements inconcomitant technology, such as artificial intelligence and wirelesscommunications, can be leveraged to improvise advanced AALsystems that can reduce healthcare costs and hospitalisations. Such systems can identify, monitor, and localize hazardousactivities to respond swiftly to unforeseen events. To addressthese issues, we present a Transparent RFID Tag Wall (TRTWall) that utilizes a passive ultra-high frequency (UHF) arrayof radio frequency identification (RFID) tags and deep learningbasedpredictive analytics for contactless human physical activitymonitoring. Specifically, we consider five different activities thatinclude sitting, standing, walking (in both directions), and noactivity. Our experimental results demonstrate that TRT-Wallcan accurately differentiate among five distinct activities withan average accuracy is 95.6%. This suggests that our proposedcontactless AAL system possesses the significant potential toenhance elderly patient-assisted living.

Novel printed passive ultra high frequency radio frequency identification antenna using meander technique

<p>In this paper, a novel radio frequency identification (RFID) antenna using a meander technique associated with a slotted patch is studied for RFID applications in the ultra high frequency (UHF) band [867.5-868 MHz]. The proposed RFID antenna is designed on a Kapton substrate with dielectric constant 3.5 and loss of 0.0027. It consists of two opposite meander line antennas of 8 turns each one and interconnected to ALIEH H3 microchip associated to two slotted patch’s with a global size 105×25×0.1 mm<sup>3</sup>. The proposed RFID antenna is designed and simulated using CST MWS as an electromagnetic solver. The results of the simulation show a return loss of -22.64 dB at 868 MHz, a reading distance of around 5 m, and a simulated input impedance of the antenna are 31.72+j109.68 Ω at the operating frequency 868 MHz.</p>

Read Range Investigation of RFID Tag on Human Chest

Radio Frequency Identification (RFID) technology for automatic identification, tracking, and monitoring of human is in great demand by the healthcare industry. The existence of passive tag with proximity to human body in general, represents an intrinsic challenge because of the high losses of body tissues A commercial passive ultra-high frequency (UHF) RFID tag with 860 MHz-960 MHz operating frequency range is modelled to study and analyze the effect on the read range parameter by placing the RFID tag in proximity to human body model (the chest) with respect to the placement of pocket position of any shirt The body model of the chest is consisting of three layers which are skin, fat and muscle. The commercial RFID tag that has been used for this study was INLAY-9662. The measurement is done on the commercial tag prior to modelling and simulation in the CST. Furthermore, the simulation was carried on two conditions: (1) in free-space, and (2) in proximity to human body. In addition, 1 mm, 3 mm and 10 mm have been set as the gap between the modelled tag and the chest model to examine the impacted read range at different distances. The results obtained have shown some variations when the distances are varied from the human chest. The read range were achieved at 0.5 m, 1.3 m and 2.4 m for 1 mm, 3 mm and 10 mm respectively. This study has shown the capabilities of human body to reduce the efficiency of the read range whenever RFID tags are placed in proximity to human body.

IoT-Enabled Vacant Parking Slot Detection System Using Inkjet-Printed RFID Tags

It is challenging for motorists to manually search for a parking slot in a crowded parking area. Conventional methods for locating vacant or occupied space are regarded as inefficient and unreliable. In this work, an Internet-of-Things (IoT)-enabled vacant parking slot detection system is developed and tested using low-cost inkjet-printed passive ultrahigh-frequency (UHF) radio frequency identification (RFID) tags. The working principle of the proposed system is to analyze the backscattered signal strength from the tags at the receiver side for vehicle presence/ absence detection in the parking slots. First of all, we propose a low-cost passive tag optimized to work in UHF RFID-band pasted on plastic material display for parking slots. The data collected by the RFID reader from the tags is sent over message queuing telemetry transport (MQTT) protocol via Scotland 5G-network to the MongoDB database using a Python module Pymongo for decision-making and display of vacant parking slots to the motorists. A Python-based web-app extracts data from the database and shows it on a web-app display using the embedded JavaScript template (EJS) for each slot. Experimental observations conducted at parking slots in the presence of vehicles indicate a drastic reduction in the received-signal-strength-index (RSSI) value at the receiver end, which implies that RSSI signal drop can be utilized for the detection of vehicle presence in the parking slot. The suggested approach aims to facilitate the economical and effective location of available parking slots. The test results for the proposed system are recorded and presented, demonstrating its significant performance and showing great accuracy for the tested scenarios.

Effect of flip-chip bonding parameters on the property of passive UHF RFID tags with screen-printed antenna on fabric

The substrate material plays an important role in industrialized flip-chip technology of the passive ultra-high frequency radio frequency identification with antenna printed on flexible film. This work presents the flip-chip fabrication and performance evaluation of ultra-high frequency radio frequency identification with screen-printed antenna on common woven fabrics. The antennas were manufactured by screen printing a stretchable silver-based conductor directly on a common woven nylon fabric. The electrical and mechanical connection between the screen-printed antennas and microchips was formed by flip-chip technology, which bridged the antenna with the microchip under a heating contactor with additive anisotropic conductive adhesives, and the effects of heating contactor parameters (contactor pressure, temperature and duration time) on the performance of radio frequency identification tag prototypes were investigated, and the influence mechanism was discussed in terms of the conductivity, the resonance frequency shift and the morphology. The experiment results show that the flip-chip bonding conditions set in the case of screen-printed antenna on nylon fabric is 0.7 N contactor pressure, 120°C heating temperature and 0.6 s heating duration time, different from the case of previous plastic-like thin film substrate, and this is mainly attributed to the compressive and rough surface of the fabric-based antennas. In addition, the flip-chip heating temperature should be consistent with that of screen-printed conductive ink to ensure a stable electrical connection between the antenna and microchip, as well as good performance of fabric-based ultra-high frequency radio frequency identification tags. These conclusions provide a tool for manufacturing large-scale fabric-based ultra-high frequency radio frequency identification tags and characterizing the process quality.

Passive RFID-Based Control Interface Integrated Into Clothing and Furniture

This paper presents an early prototype of a passive ultra-high frequency (UHF) radiofrequency identification (RFID) -based control interface. By using two types of gestures, hand tap and body movement, these tags are used as furniture-and clothing-integrated inputs. An extra tag, called a gesture initiator, is integrated into the system to prevent unintentional tag detection. After initiating the gesture tag, the user has a specific time to activate any input tag; otherwise, no output is triggered, and the user must reactivate the gesture initiator tag. Both gestures work by making a specific input tag non-detectable to an RFID reader. The prototype system was tested in an office environment in two test setups, furniture and clothing setups, where two testers successfully triggered applications-turning a light-emitting diode (LED) on or off, making a phone call, and sending a message-by using the two gestures. Next, extensive system reliability evaluation and improvement was carried out in versatile practical scenarios, where a tag can be accidentally blocked by the user or by someone else who passes by between the tag and the reader. The final results of this study suggest that the use of a gesture initiator tag significantly improves system reliability. This system can be integrated into clothing or furniture to control applications remotely and make a quick call or message without requiring a mobile phone at hand.

Research on the agile management system of workshop production resources

Industry 4.0 has a key technical point that the intelligent factory uses the ‘ raw materials ’ containing information to complete the production tracking. The high-performance real-time positioning system is an important part of the real-time tracking and positioning of materials in the industrial Internet of Things. Passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) technology has become the preferred solution for the industrial 4.0 material real-time positioning system. This paper first analyzes the RFID positioning technology, gives the process architecture of workshop manufacturing resource RFID real-time information-driven production line and the classification and management scheme of multi-source real-time manufacturing information, and realizes the RFID tracking and positioning of workshop manufacturing resource.

MIMO Radio Frequency Identification: A Brief Survey.

In this paper, we briefly look at the latest state-ot-the-art in the domain of multi-input multi-output (MIMO) radio frequency identification (RFID) systems while detailing the work done in the domain of anti-collision, range enhancements, bit error rate (BER) improvements and security. Various passive ultra-high frequency (UHF) RFID implementations are considered that employ multiple antennas at the reader and single or multiple antennas at each tag. We look at several recent works those explored MIMO for RFID receivers. When using MIMO at the backscatter channel, significant improvements can be achieved in the BER as well as range extension. With the extra reliability and increased throughput, such systems can be deployed in many important applications like large tag reading scenarios and accurate tracking. Increased throughput is directly dependent on estimation of tag quantity in a bulk reading environment and usually estimators designed for single antenna systems under-perform in such settings causing low signal to noise ratio (SNR) when employed in MIMO systems where tag signal overlapping can happen more often. One of the key challenges is to keep the design of the RFID tag simple, cutting cost and power requirement when employing anti-collision schemes. We provide a brief survey in some of the recent developments related to MIMO RFID systems, the protocols and algorithms used, and improvements achieved.

Graphene-biopolymer-based RFID tags: A performance comparison

Flexible films fabricated using two different conductive pastes based on mixtures of graphene and biopolymers have been used to fabricate passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tags consisting of a dipole antenna and a microchip on a paper substrate. The preparation of these composite materials, in addition to the design, manufacturing and characterization of the tags are presented. A comparison of the fabricated tags is carried out, focusing on the most relevant parameters for real applications: read range, dimensions and mechanical robustness. Read ranges from 7.2 m to 9.1 m were reached with conductivities from 1.01 × 104 S/m to 2.04 × 104 S/m, respectively. The results demonstrated that these low-cost materials can be used for mid-range applications, constituting a low-cost and environmentally friendly alternative unlike commercial metal-based tags.

UHF RFID tag localization using pattern reconfigurable reader antenna.

Passive ultra high frequency (UHF) radio frequency identification (RFID) tags have the potential to find ubiquitous use in indoor object tracking, localization, and contact tracing. We propose a machine learning-based method for RFID indoor localization using a pattern reconfigurable UHF RFID reader antenna array. The received signal strength indicator (RSSI) values (from 10,000 tags) recorded at the reader antenna units are used as features to evaluate the machine learning models with a train-test split of 75%-25%. The training and testing data is generated by a wireless ray tracing simulator. Five machine learning models: random forest regressor, decision tree regressor, Nu support vector regressor, nearest regressor, and kernel ridge regressor are compared. Random forest regressor has the lowest localization error both in terms of average Euclidean distance (AED) and root-mean-square error (RMSE). For random forest regressor, localization error results show that 90% of the tags are within 1 meter of their true position, and 67% are within 50 cm of their true position based on Euclidean distance.

Efficient Modeling of On-Body Passive UHF RFID Systems in the Radiative Near-Field

A novel method is presented to accurately determine the operational range of an on-body, passive ultrahigh-frequency (UHF) radio frequency identification (RFID) system operating in the radiative near field, based on its far-field radiation patterns. To this end, an efficient algorithm based on 3-D multipole expansion of the electromagnetic fields is formulated. By combining the new operator with the simulated or measured stand-alone far-field radiation patterns of the on-body RFID system, a comprehensive and accurate range determination is obtained. Compared with commercial software tools and measurements, we prove the accuracy and improved speed of the novel technique.

A Novel UHF RFID Sensor Based Crack Detection Technique for Coal Mining Conveyor Belt

This paper presents the design and analysis of a novel passive Ultra High Frequency (UHF) radio frequency identification (RFID) based sensor for crack detection in coal mining conveyor belts. The proposed sensor is built on an interdigital capacitor (IDC) based resonator integrated with a commercial UHF RFID chip. The paper illustrates the theoretical sensing principles of the sensor along with its design requirements. To enable the operation of the conveyor belt sample in the UHF band, a dielectric characterization of the belt is performed. This characterization helps obtain the material parameters of the belt, such as the dielectric constant and loss tangent. A thorough analysis of the proposed sensor in terms of simulation and experiment is also exemplified in this paper. Both simulated and experimental studies cater to a robust sensor performance for detecting cracks in the conveyor belt environment. The simulated analysis illustrates the variation of different sensing parameters, including impedance, gain, and backscattered power, with respect to different crack widths, orientations, and locations. The experimental results of fabricated sensor prototypes eventually manifest the backscattered power variation of the sensor into the change of received signal strength indicator (RSSI). An extensive analysis of the experimentally obtained results demonstrates that the proposed sensor can reliably and efficiently detect the presence and growth of cracks along with their variation in widths and orientations. The validation of simulated results through experiments essentially lays the basis for adopting machine learning based crack characterization in the future.

Intermittent Magnetic Field Monitoring System Based on Passive RFID Sensor Tags

The monitoring of magnetic fields is extremely important in many industrial environments, e.g., power grids. Despite of its importance, the existing monitoring methods either are large in size, require high power consumptions and manual observation, or although integrated in small wireless devices, need the use of batteries, increasing maintenance costs. This paper proposes an intermittent magnetic field monitoring system based on passive ultra-high frequency (UHF) radio frequency identification (RFID) technology. A magnetic field magnitude sensor has been integrated into a micro-controller unit (MCU) based tag, and the standard RFID communication protocol ISO/IEC 18000-6 Type C has been partially modified to allow faster sensed data transfer, especially for multiple tag situations rarely considered in the open literature. Static or 50 Hz magnetic field sensing accuracy lower than 3% have been experimentally measured with reasonable tag charging times and read distances, making possible for example to monitor magnetic fields on more than 10 locations simultaneously with a 60 s of updating time with a tag read range of 3 m.

Passive Ultra High Frequency RFID sensor with reference tag for crack detection of aluminum alloy structure

It can be ensured safe and reliable operation of a metallic structure by monitoring the positions which are easy to crack. Because the channel changes with the environment, a tag sensor in the ultra high frequency (UHF) is vulnerable to interference. This paper aims to investigate the reliability of passive RFID sensor systems with a reference tag for crack detection of aluminum alloy structures when the condition of reading distance and surrounding environment changes. The impedance and gain of tags are simulated, which provides theoretical basis for experimental analysis. With an increase of crack depth, the impedance of the sensor tag shifts to the low frequency direction, and the reference tag changes slightly. When dual tags are placed orthogonally, the gain of the sensor tag changes greatly, which means that it is more sensitive to crack depth. The backscatter power of the sensor tag shows a decline trend, and the power of the reference tag remains unchanged. The sensor features a linear response with the variation of crack depth. The sensitivity of crack characterization is better when dual tags are placed orthogonally.

Development, fabrication and evaluation of passive interface gloves

Previously, glove-integrated communication based on gestures, hand movement and finger touch had a complex operating system and an active power source was needed. This paper introduces batteryless and maintenance-free interface gloves. Our solution is based on passive ultra-high frequency (UHF) radio frequency identification (RFID) technology, comprising four electro-textile antenna parts and three RFID microchips (each with a unique ID). The three RFID microchips have unique IDs, which can be activated by the gentle touch of the human finger and used to control the surrounding technology. The aim is to evaluate the reliability of different conductive materials and microchip attachment methods. The antennas are fabricated from two different materials: a stretchable and a non-stretchable commercial electro-textile. Further, two types of microchip attachment methods are used with both antenna materials: a conductive silver epoxy and embroidery with conductive multifilament silver-plated thread. The developed interface gloves are tested by six users in a home and in an office environment, where they achieve 93–100% success rates. Especially those glove interfaces with the antennas fabricated from the non-stretchable electro-textile and the antenna-microchip interconnections embroidered with conductive thread showed good read ranges (80–110 cm). The gloves also show practical functionality, when tested with a mobile reader in practical identification and access control application. These results are very encouraging, especially when considering that the interface glove, being maintenance-free and cost-effective, promises versatile and interesting applications for customizing user-friendly augmentative and alternative communication solutions, easy controlling of ambient assisted-living applications, and providing simple identification and access control for increased safety and comfort.

A Synthetic Aperture UHF RFID Localization Method by Phase Unwrapping and Hyperbolic Intersection

The use of radio frequency identification (RFID) technology for the traceability of products throughout the production chain, warehouse management, and the retail network is spreading in the last years, especially in those industries in line with the concept of Industry 4.0. The last decade has seen the development of increasingly precise and high-performance methods for the localization of goods. This work proposes a reliable 2-D localization methodology that is faster and provides a competitive accuracy, concerning the state-of-the-art techniques. The proposed method leverages a phase-distance model and exploits the synthetic aperture approach and unwrapping techniques for facing phase ambiguity and multipath phenomena. Trilateration applied on consecutive phase readings allows finding hyperbolae as the localization solution space. Analytic calculus is used to compute intersections among the conics that estimate the tag position. An algorithm computes intersections quality to select the best estimation. Experimental tests are conducted to assess the quality of the proposed strategy. A mobile robot equipped with a reader antenna localizes in 2-D the tags placed in an indoor scenario and reconstructs the map of the environment through a simultaneous localization and mapping (SLAM) algorithm. <i>Note to Practitioners</i>&#x2014;A localization technology based on passive ultrahigh-frequency (UHF) radio frequency identification (RFID) is an enabling technology for intelligent warehouses, logistics, and retails. For this reason, this work presents a novel method to estimate the tag location with high accuracy. A reader antenna is mounted on an autonomous mobile robot that can move in an indoor or outdoor environment due to a simultaneous localization and mapping (SLAM) algorithm. The motion of the antenna generates a synthetic aperture. The system receives the phase measurements from the RFID tags and generates a distance model through phase unwrapping. In such a way, the possible locations of the tags in the environment are generated, creating conics. The trilateration step is performed analytically, intersecting the obtained conics. The resulting estimations are very accurate and not computation expensive. Therefore, the proposed approach can be employed in any application where localizing objects is fundamental even when reduced computational power is available, e.g., in warehouses where the products are at known heights, or where the items are placed on a fixed infrastructure, such as high-shelves logistics, to produce the inventory of the tagged objects within each shelf.

Recent Advances in Passive UHF-RFID Tag Antenna Design for Improved Read Range in Product Packaging Applications: A Comprehensive Review

Radio frequency identification (RFID) is a rapidly developing technology, and RFID sensors have become important components in many common technology applications. The passive ultra-high frequency (UHF) tags used in RFID sensors have a higher data transfer rate and longer read range and usually come in unique small and portable application designs. However, these tags suffer from significant frequency interference when mounted on metallic materials or placed near liquid surfaces. This paper presents the recent advancements made in passive UHF-RFID tag designs proposed to resolve the interference problems. We focus on those designs that are intended to improve antenna read range as well as scalability designs for miniaturized applications.

The potential of industry 4.0 Cyber Physical System to improve quality assurance: An automotive case study for wash monitoring of returnable transit items

The aim of the research outlined in this paper is to demonstrate the implementation of a Cyber-Physical System (CPS) within the Automotive Industry for the monitoring and control of Returnable Transit Items (RTIs) toward improved quality assurance and process compliance. The socio-technical issues encountered during the real-world implementation are discussed to inform future design Automotive RTI’s are utilised in the transportation of both components and subsequently assembled products at the beginning and end of life stages. The implemented system utilises passive Ultra-High Frequency (UHF) Radio Frequency IDentification (RFID) tags for the identification of metal RTIs via associated plastic separators, whilst a distributed network of RFID portals was integrated within the RTI working environment to capture and characterise their movements. The requirements, design process and resulting architecture are presented alongside the results and lessons learnt from an implementation within the automotive industry. Through the integration of business processes, analytics and tacit domain knowledge, a real-time model of the state of RTIs was developed to support decision making by a range of stakeholders. This research contributes to the knowledge of CPSs requirements identification, design, deployment and the challenges faced within real world asset monitoring and traceability within the automotive industry. Areas for future research to support the next generation of RTI traceability, monitoring and control systems are presented.