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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.

Radio Frequency Identification (RFID) adalah komunikasi nirkabel yang terdiri dari 2(dua) komponen tag dan reader untuk mengidentifikasi suatu objek secara unik. reader adalahperangkat yang memiliki satu atau lebih antena yang mengirimkan gelombang radio danmenerima sinyal kembali dari tag. RFID. Antena yang digunakan dan chip mengkomunikasikaninformasi untuk identifikasi yang dikenal sebagai reader, kemudian reader mengubah gelombang radio yang dipantulkan dari tag RFID menjadi informasi digital. Penerapan Radio Frequency Identification (RFID) dimaksudkan untuk membantu proses pengujian kualitas sepeda motor Honda atau PDI (pre-delivery inspection) dimana hal ini merupakan bagian dari SOP (standard operating procedure) sebelum sepeda motor didistribusikan ke konsumen untuk memastikan kualitas sepeda motor tetap terjaga. Pemeriksaan yang dilakukan meliputi bagian luar motor kemudian bagian dalam, bawah, kemudian pengujian saat motor berjalan, ketersediaan peralatan atau perkakas, dan dokumen peralatan seperti buku servis dan petunjuk perawatan. Padahal proses sebelumnya masih menggunakan kartu kertas yang akan dibuang saat konsumen menerima motor. Aplikasi yang dibuat dengan menggunakan aplikasi Radio Frequency Identification (RFID) berupa kartu akan menggantikan penggunaan kertas saat melakukan pemeriksaan kualitas motor.&nbsp

In this paper, a novel Radio Frequency Identification chipless tag for permittivity sensing characterized by a reduced size, an original shape and a low manufacturing cost is presented. The tag consists of a linear shape taken with multiple linear slots etched on the metal patch, ensuring a multi-frequency response. It enables the development of a robust tag with 8 bits as data capacity within a reduced surface is of 17.5×23 mm². Hence, using the frequency Domain Approach, the chipless tag is able to obtain more than 64 different binary states, by the utilization of the frequency shifting technique and the bandwidth distribution. Also, the operating frequency band ranges from 3.5 to 6.5 GHz. The new design is simulated, realized and experimentally validated by a bi-static measurement in the anechoic chamber. Then, preliminary tests are used for defining the Radio Frequency sensing chipless tag for permittivity monitoring, and proving its feasibility to control the evolution of a material over time or after use.

The fashion industry is one of the main businesses in the global economy in terms of employment, investment, trade and revenue and Italian companies are worldwide recognized as representative of cultural heritage, expertise and high-quality standards. The adoption of traceability technologies, such as Radio Frequency Identification (RFId), from the very early stage of the production chain, may help to obtain a more effective process and may also assure the origin of the garments, a key aspect in the fashion industry. The chapter aims at presenting an Italian family business, Oscalito, which has adopted the RFId technology, joining tradition and innovation in its production. A qualitative case study methodology has been adopted, to explore this experience within its context. Oscalito has applied RFId tags to each label, to ensure complete traceability throughout the production chain for each single item (and not merely by lots), fine-tuned control over the production process, and timely and accurate shipment. Thanks to their application, the production chain has been monitored and the Italian origin of the garments has been guaranteed. This research has undoubtedly some limitation due to the applied method. Deeper studies are requested in order to check a general fashion industry trend with reference to the application of RFId technology.

Due to the ongoing COVID-19 pandemic, the use of filtering facepiece respirators (FFRs) is increasingly widespread. Since the masks’ wetness can reduce its filtering capabilities, the World Health Organization advises to replace the FFRs if they become too damp, but currently, there is no practical way to monitor the masks’ wetness. A low-cost moisture sensor placed inside the FFRs could discriminate a slightly damp mask from a wet one, which must be replaced. In this letter, a radio frequency identification (RFID) tag exploiting an auto-tuning microchip for humidity sensing is designed and tested during an ordinary working day and a physical exercise. The tag returns about 1 unit of the digital metric every 3 mg of water generated by breathing and sweating, and it can identify excessively wet masks from commonly used ones.

The combination of Electrical Engineering (EE) and Information Technology (IT) has played a significant role in developing several aspects in academic and professional sectors such as student or employee monitoring. It is a critical subject to track and to manage employee attendance in work places urging employees to attend on time to increase efficiency of work, so is at schools or colleges for students. Hence, an attendance system can be useful to reduce administrative complexity and cost. The conventional pen-paper based attendance system is not absolutely flawless. In this paper we have designed an attendance system using RFID and Wi-Fi Module. Radio Frequency Identification (RFID) is an extensive application to yield maximum advantage of this technology with minimal effort for management and attendance monitoring. But it is hard to keep track of every individual only through monitoring. At such times we need an online solution. We have used Node MCU for this purpose. It is a complete and self-contained Wi-Fi network solution that can carry software applications as a stand-alone device or connected with a microcontroller.

A meander microstrip antenna was designed to operate in the UHF and microwave bands. Laser direct structuring (LDS) and the flexible printed circuit board (FPCB) method were used to fabricate the antenna, and their results were compared. A dual-band low-power-consumption active radio frequency identification (RFID) tag based on the present antenna was developed and fabricated for an automated subway vehicle maintenance system. The recognition distance of the active tag is more than 20 m at 900 MHz and more than 170 m at 2.4 GHz, while the recognition rate is >95% at 900 MHz and 100% at 2.4 GHz. The 100% recognition rate was obtained when the RFID readers were placed in a line parallel to the subway track. Therefore, we have shown that our active RFID tag can be used in a subway vehicle management system.

We propose an ultra high frequency (UHF) radio frequency identification (RFID, 902–928 MHz in the US) channel emulation testbed that is capable of simultaneously emulating unique wireless channels. The proposed system can potentially be an invaluable tool in the design and validation of RFID-based Internet of Things (IoT) sensors and systems. Emulation of ray-tracing-based wireless channels enables the evaluation of inherently difficult and complex radio frequency (RF) scenarios, particularly in situations when in-person experimentation is not feasible or desirable (e.g., during a pandemic or in a critical care facility). Furthermore, the emulation testbed is able to generate a large amount of sensor data in a limited time period. Machine learning techniques used in wireless IoT can be greatly enhanced by a large amount of data extracted from the emulation of dynamic and challenging environments. The proposed multi-channel emulation testbed is therefore a valuable solution for experimentation on real hardware and a convenient tool for pre-clinical-trial system validation.

Passive radio frequency identification (RFID) tags have been widely used in logistics, supply chain, warehousing, and other fields. However, for RFID-based automatic inventory management in warehouses, the deployment of current methods is more complex, and the localization range still has some limitations. This paper proposes DNCL, which is a hybrid passive RFID localization scheme based on direction-of-arrival (DOA) estimation and nonmetric multidimensional scaling (NMDS) to achieve spatial coordinate localization of tagged objects on shelves or racks using a single antenna for simple 1D scanning. DNCL uses antenna dynamic scanning to generate a virtual antenna array for the dynamic information capture of tags in the scene, which helps eliminate the phase shift produced by ambient noise. We apply the angle profile linear model to identify the characteristics of each tag and introduce the NMDS algorithm to improve the robustness of the scheme through the fixed layout of the reference tags, which can reliably estimate the coordinates of the tagged objects in the space. This paper realizes a prototype system and validated its practical performance in real complex situationse by COTS RFID devices. The results indicate that DNCL can achieve high accuracy for the localization of passive tags in free space.

The integration and installation of innovative Radio Frequency Identification (RFID) technologies in combination with wireless Internet of Things (IoT) technologies in Building Information Modelling (BIM), assigned building elements, can create connectivity between the physical- and the virtual world. Beyond the identification of physical objects, further information can be connected, which can be made available to different user groups during the entire life cycle of the building structure. This provides a high level of transparency, in that by scanning the tagged building elements, complete associated information can be accessed and presented to users via applications, in visual and audio form. One use of an RFID and BIM-supported electronic guidance system, namely for the visually impaired, has already been investigated in my bachelor thesis at the University of Applied Sciences (Technische Hochschule Mittelhessen, THM). This Master’s Thesis focuses on the implementation of passive RFID technology into BIM models in combining them with open-source software applications. BIM represents the digital twin of building models in the digital world and can be linked to physical structures (buildings, roads, sewer systems and such others) and building materials (e.g. textiles, mineral and plastic floor coverings, concrete components) by integrating RFID tags. Connecting the parametric BIM models with the physical building elements by using RFID and wireless IoT technologies in a multi-platform application enables the BIM building models to be actively used throughout the life cycle of a building, not only by the facility management, but also by the public for various use cases. During the literature review, suitable software and hardware components were selected, and a prototype multi-platform application for a navigation and positioning system was developed as proof of concept for the Industry Foundation Classes (IFC) file. (See Demo Version at https://opennavibim.herokuapp.com/ ). The challenge was to read the RFID tags in different installation scenarios. Depending on the installation situations (under, over or in the material), various requirements were specified for RFID tags and readers (RFID, handhold personal digital assistant “PDA”). In this field, further hardware developments are necessary. RESUMEN: Mediante la integración e instalación de la innovadora tecnología de identificación por radiofrecuencia (RFID, Radio Frequency Identification) en el modelado digital de información de construcción (BIM, Building Information Modelling), con la interconexión inalámbrica del internet de las cosas (IoT, Internet of Things), es posible crear una conectividad entre el mundo físico y el virtual. Más allá de la mera identificación de objetos existentes, esta conectividad permite incorporar información adicional, que puede ponerse en disposición de los diferentes grupos de usuarios que intervienen durante el ciclo completo de vida de la estructura de la edificación. Se consigue un alto de nivel de transparencia en ese traspaso de información, accesible por medio del escaneado de los elementos etiquetados en la edificación, al tener una completa información asociada que es presentada a los usuarios vía aplicaciones en formato visual o de audio. Una investigación en la aplicación de tecnología RFID basada en BIM para un sistema de navegación electrónica, destinada a personas con discapacidad visual, ha sido desarrollada en mi trabajo fin de grado en la Universidad de Ciencias Aplicadas de Mittelhessen (THM). El presente Trabajo Fin de Master se centra en la implementación de tecnología RFID pasiva en modelos BIM combinados con aplicaciones de software libre. El modelo BIM representa el gemelo digital de los elementos de construcción en el mundo virtual, permitiendo establecer una relación del modelo con estructuras físicas (edificios, carreteras o sistemas de alcantarillado, entre otros) y materiales de construcción (por ejemplo, textiles, cubiertas de suelo minerales o plásticas, componentes de hormigón, …) por medio de la integración de etiquetas RFID. La conexión de los modelos paramétricos BIM con los elementos físicos del edificio, mediante el uso de tecnologías RFID e IoT inalámbricas en una aplicación multiplataforma, permite que los modelos de construcción BIM se utilicen activamente a lo largo del ciclo de vida de un edificio, no solo por la gestión de las instalaciones, sino también por el público para diversos casos de uso. Durante la revisión bibliográfica, se seleccionaron los componentes de software y hardware adecuados, y se desarrolló un prototipo de aplicación multiplataforma para un sistema de navegación y posicionamiento como prueba de viabilidad del concepto del modelo Industry Foundation Classes (IFC). (Véase la versión de demostración en https://opennavibim.herokuapp.com/ ). La lectura de las etiquetas RFID en diferentes en diferentes situaciones de instalación presenta un desafío, dependiendo de la instalación (debajo, encima o en el material) los requisitos impuestos a las etiquetas y lectores RFID son diferentes. Por lo tanto, es necesario seguir desarrollando el hardware en este ámbito. Máster en Ingeniería de Caminos, Canales y Puertos (Plan 2020)

The challenges faced by managers of transportation systems in developing nations such as Nigeria are numerous. These include driver scheduling, which, in many cases, is still being done manually; diversion of vehicles to unauthorized routes by drivers for selfish reasons results in illegal use of fuel meant for official duties, causing the organization lose considerable revenue. In its drive to reduce its carbon footprint, Elizade University, Nigeria, is embarking on the development and use of electric vehicles (EV) as a means of transportation within the university campus. This research is geared towards supporting this initiative by developing an EV tracking system that combines tracking of EV drivers with vehicle position and battery power (energy) tracking in order to mitigate the challenges outlined above. Personnel tracking was achieved using an RFID-enabled staff identity card that authenticates authorized drivers before activating the vehicle ignition system, position tracking was achieved using a geographical positioning system (GPS), and current and voltage sensors were used for tracking of electric vehicle power. Tests revealed that the EV system administrator operated through a personal computer was able to track the EV driver, position and power through a web interface/Google Maps and e-mail in real time. Whereas previous studies either considered tracking of vehicle position or power without personnel, others tracked personnel with less emphasis on the vehicle position or energy. In this study, we combined different technologies such as RFID, GPS and power sensors to consider EV administration in a holistic manner, thereby providing intervention in an infrastructurally deficient setting.

A novel Radio Frequency Identification (RFID) based sensor supporting touch detection and localization features is proposed in this work. The formulated sensor leverages chipless variant of RFID technology for the design of a passive fully-printable frequency domain-based sensor-incorporated tag. The sensor is composed of square resonators arranged in a peculiar fashion laid down across a $3\times2$ grid. The proposed sensor incorporated-tag readily keeps track of human-digit position, allowing for tracking of finger-swipes which, in turn, can potentially be used for recognition of unlock patterns and security codes. Performance of the sensor is analyzed using its Radar Cross Section (RCS) response observable in the spectral domain. Each constituent resonant-element making up the sensor resonates at a single frequency represented by a distinct dip in the RCS response. The spectral dip drifts well outside of its allocated band upon occurrence of a touch event. A functional prototype of the sensor tag is fabricated on a 0.508 mm thick Rogers RT/Duroid® 5880 laminate is scrutinized of its electromagnetic performance. The sensor possesses a compact physical footprint equal to 45 mm $\times55$ mm. The obtained results solidify the suitability of the proposed sensor for deployment in secure access control settings prevalent in smart cities and connected home applications.

The growing research interest in passive RFID (Radio Frequency Identification)-based devices and sensors in a diverse group of applications calls for flexibility in reader antenna performance. We propose a low-cost, easy-to-fabricate, and pattern reconfigurable UHF (Ultra High Frequency) RFID reader antenna in the RFID ISM band (902–928 MHz in the US). The antenna offers a 54 MHz bandwidth (890 – 944 MHz) and 8.9 dBi maximum gain. The proposed reconfigurable antenna can radiate four electronically switchable radiation beams in the azimuth plane. The antenna is LHCP (Left Hand Circularly Polarized) with axial ratio (AR) in the ranging from 0.45 dB to 7 dB in the RFID ISM band. Simulation and measurements are presented, and they are in good agreement. The proposed reader array performance is compared against a commercially available reader antenna. The pattern reconfigurable UHF RFID reader antenna not only increases the coverage area for conventional RFID applications but also opens the door to on-body RFID sensor implementation and indoor localization applications.

In this article, we describe a customized 2.45-GHz radio frequency identification (RFID) reader designed to simultaneously perform 3-D tracking of multiple tagged entities (objects or people), static or dynamic, in harsh electromagnetic indoor environments. This is obtained by a bi-dimensional electronic beam-steering, implementing the monopulse radar concept simultaneously in the elevation and azimuth directions, with tags-reader distance estimation based on received signal strength indicator (RSSI) measurements. Experimental results show that the system is able to perform a tri-dimensional scanning of a monitored room with decimeter-accuracy over the three reference axes. The RF front end is designed to be lightweight, thin, and compact in such a way that it is portable and embeddable in domestic objects. For this purpose, a multi-layer solution is adopted with a 2-D patch antenna array aperture coupled with the RF front end. 3-D localization data are computed onboard by means of a seamless connection of the RF front end with a low-power microcontroller, which is able to store tags 3-D localization data over a multi-hour time frame. A useful method to remotely control the whole system is presented, using a Raspberry Pi 3B, directly connecting the reader with a flexible and extensive digital platform for Smart Homes. The presented architecture is experimentally demonstrated to perform a reliable fall detection of tagged people in indoor environments.

Moisture content (MC) detection plays a vital role in the monitoring and management of living trees. Its measurement accuracy is of great significance to the progress of the forestry informatization industry. Targeting the drawbacks of high energy consumption, low practicability, and poor sustainability in the current field of living tree MC detection, this work designs and implements an ultra-high-frequency radio frequency identification (UHF RFID) sensor system based on a deep learning model, with the main goals of non-destructive testing and high-efficiency recognition. The proposed MC diagnostic system includes two passive tags which should be mounted on the trunk and one remote data processing terminal. First, the UHF reader collects information from the living trees in the forest; then, an improved online sequential parallel extreme learning machine algorithm (OS-PELM) is proposed and trained to establish a specific MC prediction model. This mechanism could self-adjust its neuron network structure according to the features of the data input. The experimental results show that, for the entire living tree dataset, the MC prediction model based on the OS-PELM algorithm can identify the MC level with a root-mean-square error (RMSE) of no more than 0.055 within a measurement range of 1.2 m. Compared with the results predicted by other algorithms, the mean absolute error (MAE) and RMSE are 0.0225 and 0.0254, respectively, which are better than the ELM and OS-ELM algorithms. Comparisons also prove that the prediction model has the advantages of high precision, strong robustness, and broad applicability. Therefore, the designed MC detection system fully meets the demand of forestry Artificial Intelligence of Things.

With the trend of textile antennas development, ultra high frequency (UHF, 865–868 MHz) radio frequency identification (RFID) devices using textile materials are expected to be developed in many areas for replacing or simplifying some complex RFID devices on a PCB. In this paper, we present a textile UHF-RFID tag with two sensing positions ('radiation parts' and 'loop part') for exploring the feasibility of sucrose solutions measurements and the relationship between variables of the proposed design and the sucrose solutions. The simulated and measured resonance curves of the designs both match well (-20 dB in the simulation and -15.8 dB in the measurement at 868 MHz) and the read range measured by the RFID reader (M6e kit) is 1.71 m in air. Before the tests by the solutions on the proposed designs, a test board is developed as a preparation work for confirming the relative dielectric constants of the sensing substrate area in the real measurements. Compare the results of the simulation and the real tests, the proposed design shows good feasibility by comparing the simulated and measured results in confirmed relative dielectric constants. Moreover, its two sensing positions have different sensing features. The sensing 'radiation parts' position shows a stable frequency operation performance but sensing range is from 1.71 m (dry) to 2.3 m, while the sensing 'loop part' position has a wide sensing range from 0.4 m to 1.71 m (dry) but a lower frequency operation performance. This work was supported by Spanish Government-MINECO under Project TEC2016- 79465-R and China Scholarship Council No.201908440233.

At present, some existing tag anti-collision algorithms are used mostly in scenarios of fixed number of tags and they perform poorly in tag moving scenarios. Therefore, this paper proposes a double reader tag movement RFID anti-collision method based on suffix, and through the cloud platform based on cloud computing, the supply chain data sharing is realized. Tag moving scenarios usually use a single reader. The proposed employs double reader to expand the recognition range and also to prolong the recognition time, but there is the problem of repeated recognition. This article proposes a suffix-based bit-slot ALOHA (SBSA) algorithm, where this problem is solved and the time-slot is reduced. In view of the problem that a large number of tags entering into the recognition area of readers lead to the reduction of the recognition efficiency. This article proposes a suffix-based tag group bit-slot ALOHA (STGBSA) algorithm, tag grouping and tag estimation methods are proposed. Complexity analysis is deployed in this article, from the perspective of the tag loss ratio and identification efficiency, the performances of various anti-collision algorithms are evaluated and compared with those of the existing methods. The simulation results show that the method proposed in this paper is better than the existing methods.

This NEMA standard describes a protocol for authenticating EV charging service requests using contactless proximity Radio Frequency Identification (RFID)–type credentials. Authentication provides assurance to the Electric Vehicle (EV) charging network that the EV driver is the correct authorized party incurring a financial or other obligation for the services to be rendered. Similarly, the EV driver can have confidence that transactions have not been authenticated using forged or fraudulent credentials.

Internet of Things (IoT) devices are basic units in edge computing. Denial of service (DoS) attack is a great threat to low-cost IoT devices, even worse in privacy-preserving authentication protocols for radio frequency identification (RFID) tags. During DoS attacks, the attacker consumes the legal states in a target tag by continuous scanning and further observes its behavior in authentication to break privacy. Due to lack of adequate energy and computing power, it is hard for passive backscattering RFID tags to defend against DoS attacks. In this work, we cast a new insight on the DoS attacks to RFID tags and leverage the malicious scanning behavior as a new energy source. In this way, a passive tag gains more and more energy and can afford more and more complex cryptography computation under a DoS attack. Finally, the victim tag with adequate energy achieves to complete the complicated public key cryptographic computations and defend against the DoS attack. We further propose a protocol, namely the RUND protocol. We define the tracking privacy model and introduce in the notion of tracking interval to define the tracking privacy other than indistinguishable privacy. To guarantee the security and tracking privacy properties of our protocol, we propose 3 rules as designing guidelines. The analysis shows that our approach can achieve $O$ (1) efficiency while providing DoS-defending privacy-preserving authentication. Furthermore, with proper parameters our approach can save about 40% boosting time at least, compared to the directly charging for public key cryptographic computation method.

Radio Frequency Identification (RFID) is recognized as an essential technology for the development of the Internet of Things (IoT) concept. This is due to the possibility of object identification using passive tags which do not require batteries for their operation. Instead, tags are powered by the electromagnetic waves emitted from the reader and then the same electromagnetic wave is used as a carrier to reflect the modulated information about their unique serial number back to the reader. According to the EPCglobal Class-1 Generation-2 RFID standard, Dynamic frame slotted ALOHA procedure is used to solve the anticollision problem. Basically, a reader adjusts the frame length for the next reading round based on the estimated number of unread tags. To achieve high reading efficiency, an algorithm with accurate estimation of the remaining number of tags is required. The article shows that for the adjustment of the next frame length, only the number of collisions is relevant. A simple estimator for the frames with 64 slots is designed, and generalized for the frames of any length provided within the EPCglobal Class-1 Generation-2 standard. Contrary to existing solutions, which use more tables for storage of the estimated values depending on the frame length, proposed approach requires just one table. Also, the problem of estimation is reduced to dependence on the number of collisions only, while conventional approaches use the number of collisions and successful slots.

This paper presents a compact microstrip ultra-high frequency (UHF) reader patch antenna with complementary split ring resonator (CSRR) for radio frequency identification (RFID). The total size of the antenna is 208 × 208 × 1.6 mm3. The proposed antenna is designed, fabricated and measured in order to verify the proposed concept. The characterization for radiation parameters, like return loss, radiation pattern and antenna gain have been done experimentally. The proposed antenna is operated at 921 MHz for and achieved a gain of 8.285 dBi. All simulations in this work have been carried out by means of the commercial computer simulation technology (CST) software. In compare to the simulated results, the measured outcomes are promised.

In this study, a novel compact auto-tracking antenna system was developed to ensure the high reliability of practical applications. The system consisted of three antennas (two anchor antennas and a tag antenna), three ultra-wide band (UWB) chips, and one compact turntable. On the anchor side, two highly linearly polarized antennas with a short baseline were installed on an auto-control turntable. Two UWB chips were integrated with the two anchor antennas to extract the phase and amplitude information of the receiving signal. On the tag side, a wide-beam circularly polarized antenna with a UWB chip was installed to mitigate the effect of the tag’s pose on the phase measurement. Using a correlation matching algorithm based on the phase difference of arrival, high tracking reliability with a 90% success rate was achieved for all practical direction-of-arrivals and various axial rotating angles of the tag over the maximum radiation deflection angles between –90° and 135°. The operation distance of a demo self-balanced two-wheeled vehicle was 20 m.

Security in our country and abroad requires the search for new information technologies to protect and secure facilities from unauthorized access. The protection of objects of national importance is especially urgent. The protection of the perimeter of the territory is impossible without the use of computerized control systems and measurement of motion parameters of objects. With the development of information technology, the equipment of attackers is getting more and more advanced, who are finding new ways to overcome obstacles in their path. Therefore, an urgent task is to improve computerized access systems to closed objects in order to increase their resistance to attacks and reliability of operation. The article analyzes the modern methods, means and technologies of identification and determination of the parameters of the movement of vehicles. The advantages and disadvantages of these methods are revealed, new methods are developed for information technologies for the identification of objects in access control systems for a closed object. Modern models and methods for constructing a computerized vehicle identification system are based on a comprehensive solution. A method for constructing a block of decision making about the identification of objects is proposed. The production model of the knowledge base was designed with weights taken into account to reduce the error rates of the first and second kind.

Purpose The purpose of this paper is to identify the impact of enterprise systems (ESs), in particular radio frequency identification (RFID) and enterprise resource planning (ERP) systems, on supply chain management (SCM). The results of this conceptual paper demonstrate that ERP and RFID systems contribute to SCM by improving supply chain integration. Supply chain integration occurs to facilitate the flow of financing, products, and information throughout the chain. In this regard, ERP and RFID contribute to integration by enhancing the information flow across the supply chain. Design/methodology/approach This paper proposes a conceptual model developed from the findings of literature review within the research domains of SCM, ESs, and supply chain integration. Findings This conceptual study contributes to the existing theory by linking the concept of information technology, ESs to SCM. The conceptual model in this paper may provide insights for executives who wish to implement ERP or RFID systems in their businesses in order to achieve higher integration, both within internal sectors and also with supply chain partners. Originality/value The findings in this study contribute to the theory base by linking the concept of information technologies, ESs to SCM. The conceptual model presented in this paper can provide insights for executives who wish to implement ERP or RFID systems in their businesses in order to achieve higher integration within internal sectors and with supply chain partners. This study offers new understandings by investigating the impact of ERP and RFID together on SCM.

This paper presents an approach based on radio frequency identification (RFID) and machine learning for contamination sensing of food items and drinks such as soft drinks, alcohol, baby formula milk, etc. We employ sticker-type inkjet printed ultra-high-frequency (UHF) RFID tags for contamination sensing experimentation. The RFID tag antenna was mounted on pure as well as contaminated food products with known contaminant quantity. The received signal strength indicator (RSSI), as well as the phase of the backscattered signal from the RFID tag mounted on the food item, are measured using the Tagformance Pro setup. We used a machine-learning algorithm XGBoost for further training of the model and improving the accuracy of sensing, which is about 90%. Therefore, this research study paves a way for ubiquitous contamination/content sensing using RFID and machine learning technologies that can enlighten their users about the health concerns and safety of their food.

This paper presents a new type of radio frequency identification positioning method. This method uses a hybrid positioning method combining signal angle of arrival and RSSI (signal strength value positioning). First, the phased array antenna is used to measure the azimuth angle of the target tag, and then, the reader is read to read the signal strength of the target tag. After using the neural network model to fit the curve of signal strength and distance, when the signal strength is converted into a distance by the curve relationship, the positioning function of the target tag is realized. Experimental results show that compared with traditional positioning algorithms, not only the positioning accuracy is improved but also the working range is increased and the system anti-jamming capability is improved.

Intelligent packaging is an emerging technology, aiming to improve the standard communication function of packaging. Radio frequency identification (RFID) assisted smart packaging is of high interest, but the uptake is limited as the market needs cost-efficient and sustainable applications. The integration of screen printed antennas and RFID chips as smart labels in reusable cardboard packaging could offer a solution. Although paper is an interesting and recyclable material, printing on this substrate is challenging as the ink conductivity is highly influenced by the paper properties. In this study, the best paper/functional silver ink combinations were first selected out of 76 paper substrates based on the paper surface roughness, air permeance, sheet resistance and SEM characterization. Next, a flexible high frequency RFID chip (13.56 MHz) was connected on top of screen printed antennas with a conductive adhesive. Functional RFID labels were integrated in cardboard packaging and its potential application as reusable smart box for third party logistics was tested. In parallel, a web-based software application mimicking its functional abilities in the logistic cycle was developed. This multidisciplinary approach to developing an easy-scalable screen printed antenna and RFID-assisted smart packaging application is a good example for future implementation of hybrid electronics in sustainable smart packaging. ispartof: MATERIALS vol:14 issue:19 ispartof: location:Switzerland status: published

Customized/personalized products are gaining more shares in today’s product market. Such products need collective efforts from consumers, manufacturers and third parties. This requirement has not been well addressed due to both market and technology factors. On the other hand, the Internet of Things (IoT) provides real-time sensing/actuating ability and fast transmission capability of data/information, so that remote operation of manufacturing activities and efficient collaboration among stakeholders are greatly facilitated. This provides great opportunities to address the requirement mentioned above. Thus we propose a full-connection model of product design and manufacturing in the IoT-enabled cloud manufacturing environment. The proposed model uses social networks to connect multiple parties and facilitate open innovations, and use IoT to glue physical space to cyber space and cloud manufacturing to provide various elastic services, so that the on-demand workspace, interaction, information sharing or collective problem solving are enabled. We also propose a supporting infrastructure for this model using the latest information and communication technologies. Finally, we present a case study of an RFID enabled production system for customized and personalized product with the ability to enable a new paradigm of “dynamic processes and close collaborations among different roles” and ensure robust production.

Skin-mounted electronics is the new frontier for unobtrusive body-centric monitoring systems. In designing the wireless devices to be placed in direct contact with the human skin, the presence of the lossy body cannot be ignored because of strong electromagnetic interactions. In this paper, the performance of epidermal antennas, for application to radio frequency identification (RFID) links in the UHF band, was investigated by means of numerical simulations and laboratory tests on fabricated prototypes. The analysis demonstrates the existence of an optimal size of the antennas (from 3 to 6 cm for loops and from 6 to 15 cm for dipoles) and of upper bounds in the achievable radiation gain (less than −10 dB in the case of 0.5 mm thick application substrates) as a consequence of the balance between the two opposing mechanisms of radiation and loss. This behavior, which is controlled by the hosting medium, does not depend on the antenna shape, even if the loop layout permits considerably minimizing the device size. Even the conductivity of the antenna trace plays only a second-order role; low-cost inkjet printable paints with conductivity higher than 104 S/m are suitable to provide radiation performance comparable with the performance of copper-made antennas. Starting from the investigation of the above cited physical phenomena, including the effect of common classes of suitable substrate membranes, guidelines are finally derived for the optimal design of real RFID epidermal antennas.

FDM (Fused Deposition Modelling) 3D printing emerged in the last few years as one of the most promising additive manufacturing techniques for fast prototyping. In this work, this technique is used to fabricate UHF (Ultra High Frequency) RFID (Radiofrequency Identification) flexible tag antennas, using a plastic-based conductive filament with copper inclusions, called Electrifi. A comparison with other prototypes with similar shape but fabricated through different and already investigated techniques [1] has been performed in terms of ease of use, processing time, cost, tag sensitivity, radiation pattern, and impedance. More specifically, 3D-printing technology for RFID tag fabrication is compared with inkjet printing, screen printing, wax-based deposition, and cutting plotter. The conductive properties of the antennas realized with the Electrifi filament, as expected, are lower than those of the antennas realized with the other techniques. Nevertheless, a slight degradation in terms of tag performances, is balanced by the extremely high versatility of the fabrication technique. Moreover, the capability to easily fabricate a fully 3D printable antenna, together with the possibility to print complex and not only planar geometries, pave the way to interesting and meaningful future developments. © 2019 IEEE.

In this paper, a UHF RFID sensor tag suitable for cold-chain applications is presented. The purpose of this RFID tag, developed in the framework of a TETRAMAX technology transfer project, is to provide both tracking and temperature monitoring of fresh and frozen fish. The device is a semi-passive tag that includes an antenna matched with the EM4325 RFID chip impedance, a MCU, LEDs, and GPIO ports. A continuous temperature monitoring is performed through the RFID chip with embedded temperature sensor, and alerts are generated when specific pre-set thresholds are overcome. In order to operate also with the presence of ice, a platform-Tolerant PIFA tag antenna has been specifically designed and simulated through CST Microwave Studio software. Obtained results demonstrate the tag robustness to the background material even in case of ice and metal. © 2019 University of Split, FESB.

International audience; This article presents an innovative contribution, which is the design of a novel radio frequency identification chipless tag characterized by a reduced size and a multifrequency response. It consists of a microstrip grounded structure based on a circular patch coupled with meandered metal strip. The adopted approach is an encoding frequency approach that ensures a capacity of 20 data bits in the ultra wideband. The main aim of this contribution is to introduce a novel configuration resulting from the study of the classic principles of the chipless tag design. It focuses on the design of an encoding surface associated with the same shape having the role of the transmitter/receiver antenna in order to mainly gain time to work on another tag component. The tag is analyzed, optimized, and measured to validate its feasibility and to prove the possibility of its commercial application.

We present a survey on battery-less Radio Frequency Identification (RFID-based wireless sensors that have emerged in the past several years. We discuss the evolution of RFID turning into wireless sensors. Moreover, we talk about different components of these battery-less RFID-based wireless sensors, five main topologies that transform a simple RFID chip into a battery-less wireless sensor, and state-of-the-art implementations of these topologies. In battery-less wireless sensors, the read range is of key importance. Hence, we discuss how each component of the sensor plays its role in determining the read range and how each topology exploits these components to optimize read range, complexity, and/or cost. Additionally, we discuss potential future directions that can help provide improvements in RFID-based wireless sensor technology.

This paper presents a novel inkjet-printed near-field ultra-high-frequency (UHF) radio frequency identification (RFID) tag/sensor design with uniform magnetic field characteristics. The proposed tag is designed using the theory of characteristics mode (TCM). Moreover, the uniformity of current and magnetic field performance is achieved by further optimizing the design using particle swarm optimization (PSO). Compared to traditional electrically small near-field tags, this tag uses the logarithmic spiral as the radiating structure. The benefit of the logarithmic spiral structure lies in its magnetic field receiving area that can be extended to reach a higher reading distance. The combination of TCM and PSO is used to get the uniform magnetic field and desired resonant frequency. Moreover, the PSO was exploited to get a uniform magnetic field in the horizontal plane of the normal phase of the UHF RFID near-field reader antenna. As compared with the frequently-used commercial near field tag (Impinj J41), our design can be readable up to a three times greater read distance. Furthermore, the proposed near-field tag design shows great potential for commercial item-level tagging of expensive jewelry products and sensing applications, such as temperature monitoring of the human body.

State-of-the-art radio frequency identification (RFID)-based indoor autonomous vehicles localization methods are mostly based on received signal strength indicator (RSSI) measurements. However, the accuracy of these methods is not high enough for real-world scenarios. To overcome this problem, a novel dual-frequency phase difference of arrival (PDOA) ranging-based indoor autonomous vehicle localization and tracking scheme was developed. Firstly, the method gets the distance between the RFID reader and the tag by dual-frequency PDOA ranging. Then, a maximum likelihood estimation and semi-definite programming (SDP)-based localization algorithm is utilized to calculate the position of the autonomous vehicles, which can mitigate the multipath ranging error and obtain a more accurate positioning result. Finally, vehicle traveling information and the position achieved by RFID localization are fused with a Kalman filter (KF). The proposed method can work in a low-density tag deployment environment. Simulation experiment results showed that the proposed vehicle localization and tracking method achieves centimeter-level mean tracking accuracy.

As the Internet of Things (IoT) and the Web of Things (WoT) are becoming a reality, their interconnection with mobile phone computing is increasing. Mobile phone integrated sensors offer advanced services, which when combined with Web-enabled real-world devices located near the mobile user (e.g., body area networks, radio-frequency identification tags, energy monitors, environmental sensors, etc.), have the potential of enhancing the overall user knowledge, perception and experience, encouraging more informed choices and better decisions. This paper serves as a survey of the most significant work performed in the area of mobile phone computing combined with the IoT/WoT. A selection of over 100 papers is presented, which constitute the most significant work in the field up to date, categorizing these papers into ten different domains, according to the area of application (i.e., health, sports, gaming, transportation, and agriculture), the nature of interaction (i.e., participatory sensing, eco-feedback, actuation, and control), or the communicating actors involved (i.e., things and people). Open issues and research challenges are identified, analyzed and discussed. © 2014 IEEE. 3 6 885 898 Cited By :3

The generation and propagation of cracks are critical factors that affect the performance and life of large structures. Therefore, in order to minimize maintenance costs and ensure personal safety, it is necessary to monitor key structures. The sensor based on ultra-high frequency radio frequency identification (UHF RFID) antenna has the advantages of passive wireless, low cost, and great potential in the field of metallic structure health monitoring. In this paper, aimed at the key parts of a metallic structure, a dual-tag system is used for crack monitoring. In conjunction with mode analysis, the principles of the sensing tag and the coupling principles of the dual-tag are analyzed. Considering that the dual-tag is placed in different methods, the effect of mutual coupling on the sensing performance of the tag is studied. The results show that the frequency of the sensing tag can be tuned by adding the interference tag, and the dual-tag sensor system has reasonable sensitivity. The results also provide potential guidance for the optimal placement of multiple tags in the near-field region.

Textile radio-frequency identification operating in ultra-high frequency (UHF-RFID) sensors based on different scenarios are becoming attractive with the forthcoming internet of things (IoT) era and aging society. Compared with conventional UHF-RFID sensors, textile UHF-RFID sensors offer the common textile features, light weight, washability and comfort. Due to the short time and low level of development, researches on the integration of textile UHF-RFID techniques and textile sensing techniques are not flourishing. This paper is motivated by this situation to identify the current research status. In this paper, we provide a systematic review of the fundamentals of textile UHF-RFID sensors techniques, materials, the brief history and the state-of-the-art of the scenario-based development through detailed summary and analysis on the achievements from the starting year of 2004 to the present time. Moreover, according to the analysis, we give a proposal of the future prospects in several aspects, including the new materials and manufacturing processes, machine learning technology, scenario-based applications and unavoidable reliability. This work was supported by Spanish Government-MINECO under Project TEC2016-79465-R and ChinaScholarship Council No. 201908440233.

In a natural disaster such as an earthquake, it is vital to know the number of people trapped under the ruins. To address this problem, we propose RESCUE - wiREless backScattering CommUnication based disastEr recovery system. RESCUE is composed of special Radio-frequency identification (RFID) readers and sensors that are used to determine the total number of people under the ruins. Passive wireless sensor nodes are placed inside the building during construction and are equipped with a camera that is activated during an earthquake. After the earthquake, communication to the passive tags of sensors is achieved by wireless power transfer from a reader located outside the ruins. Tags harvest this energy and send the image data stored by the camera. We also design an antenna structure to maximize simultaneous wireless information and power transfer (SWIPT) for devices under ruins. We analyze the communication channel between reader and sensors and derive a channel model over ruins. Furthermore, we obtain the results of experimental study where we validate the derived channel model. Results show that RESCUE can collect the desired data in a relatively short time, and hence, is a promising disaster recovery system architecture., Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences Distinguished Young Scientist Award Program (Turkish Academy of Sciences (TÜBA)-GEBIP)

usc Refereed/Peer-reviewed One of the issues faced by manufacturing industry is a lack of automatic localization techniques. In this research, a Radio Frequency Identification (RFID) based localization system is proposed for resource tracking. In this study, we incorporated a RFID tag at each item to be tracked, and a RFID reference tag at each location zone. The encoded IDs are read to identify the names of items and location zones. At the same time, radio signals (received signal strength and phase) are measured as RFID fingerprints. Similarity measures are studied to compare fingerprints between RFID item tags and location reference tags to track the location of the items. The kernel-based learning method was implemented as similarity measure. Different cluster labelling methods were compared and it was found that the proximity method is more efficient. The clustering method is used to overcome the issues faced by traditional RFID based localization methods.

usc Refereed/Peer-reviewed Tracking the location of mobile manufacturing objects is essential for manufacturing execution system. This paper presents a review of recent RFID-based localization and tracking technologies. Based on the literature review, we studied the feasibility of indoor localization that locates items on the manufacturing shop-floor automatically using wireless signals and RF-based localization technologies. Although the real-time locating systems (RTLS) exist to provide real-time localization, these technologies are costly to implement on a large scale. In this feasibility study, we measured received signal strength and phase shift signals from commercial off-the-shelf (COTS) wireless devices for tracking the location of manufacturing objects.

Radio Frequency Identification (RFID) technologies were considered as the main enabler for the Internet of Things (IoT) vision due to its almost zero energy consumption and efficient price/performance ratio. Small and cost effective devices called tags can report their memory content from NLOS distances and therefore represent true replacement for old-fashioned barcodes. RFIDs are still advancing, and as already shown in the literature, there is some work to be done in order to improve overall system performances. To deal with this, research efforts made so far are concentrating on particular details of the protocol stack, while neglecting the influences that appear from the other layers. When looked integrally, to be optimal, these should be properly compensated. In this paper an overview of these influences is given while discussing open research questions and opportunities that remain to be investigated both in PHY and MAC layer.

International audience; Radio Frequency Identification (RFID) is a technology for automatic object identification that has been implemented in several real-life applications. In this work, we expand a novel relevant application of RFID tags for grocery stores, which aims to check the adequacy of food items with respect to the shoppers' personal preferences. Unlike similar works, we focus on shoppers' privacy and running time efficiency. For this aim, we propose a novel private set intersection (PSI) protocol to be used in matching the shoppers' personal preferences with the set of each item's adequate profiles that are held by the back-end server of the store. We provide a standard security proof against curious stores and malicious customers. For efficiency concern, we build our protocol without cryptographic operations, and we achieve a linear asymptotic complexity of O(v + c) for communications and store-side computations, where v and c are the numbers of profiles in the store's back-end server and the shopper's list of preferences respectively. Moreover, experimental results and comparisons with state-of-the art solutions reveal the scalability of our novel PSI protocol for big market stores.

This paper presents the development of GUI to monitor health condition of university students of Universiti Teknologi MARA (UiTM) Shah Alam. The objectives of this work are to design and develop the GUI, to create the database according to the students’ identification (ID) card, and to update and verify the students’ medical information supported by the Radio Frequency Identification (RFID) system. Based on the issue of high frequency of class absence and cases of fake medical certificates submission, this work is highly motivated to improvise the situation for the university students in order to validate the medical leave certificate provided by the students if missing from a class. Microsoft Visual Basic Express 2010 and Microsoft Office Access 2007 are utilized for the software part, which is then integrated with the RFID system. This work is tested to the students of Faculty of Electrical Engineering, UiTM. When a student ID card is scanned by the RFID reader, a GUI displaying student’s information can be viewed on a host computer by the medical practitioner and can be updated with the current state of health information. The medical information given at the health center can be verified and accessed by the faculty. At the end of this work, the GUI displays are successfully developed for the medical practitioner at the health center and the lecturer at the faculty. This system facilitates lecturer to easily verify and validate on medical leave or the student’s absence, since medical information can be viewed directly by the lecturer.

The paper discusses the use of RFID technologies in healthcare setting examining the status of applications and prospective views. The authors have identified two classes of applications of RFID technologies in healthcare setting: people monitoring/management and items/assets management applications. While for the perspective views it is provided their classification in: future scenarios, emerging applications and needs. Moreover, a discussion on components, development, key strengths and critical issues affecting the RFID usage in healthcare setting is given in the paper.

A planar wideband patch antenna for ultra-high frequency (UHF) radio frequ ency identification (RFID) tag for metallic applications is presented in this research work. Three different shape patches ar e inductively coupled to a triangle loop to form wi de impedance bandwidth for uni- versal application UHF (860 – 960 MHz) RFID. The struc- ture of the proposed antenna exhibits planar profile to provide ease of fabrication for cost reduction well suited for mass production. The simulation of the antenna was carried out using Finite Elemen t Method (FEM) based software, Ansoft HFSS v13. The simulated and measured impedance bandwidth of 113 MHz and 117 MHz (Return Loss ≥ 6 dB) were achieved to cover the entire UHF RFID operating frequency band worldwide. The simulated and measured radiation patterns at the operating frequency of 915 MHz are in good agreement. Moreover the simulated maximum antenna gain at th e bore sight direction in free space and when mounted on 200 × 200 mm 2 metal plate are -5.5 dBi and -9 dBi res pectively which is enough to provide reasonable read range over the entire UHF RFID system operating band.

A solution for the automation of inventory taking and location of prod-ucts in a store or warehouse is presented. Radio Frequency Identifica-tion (RFID), an automatic identification technology, and mobile robotics are combined in the design of an inventory robot. The navigation of the robot is commanded by an algorithm that takes as input the progress of new identifications. Such algorithm is essential for the robot to deliver an accuracy higher than 99% and for an optimal inventory duration. An interface for the interaction with the robot and a set of procedures for its operation are implemented. The location of items is implemented using two different approaches. The first approach applies clustering to streams of identifications and assigns the known location of a reference item to all the members of a cluster. The second approach applies Bayesian Re-cursive Estimation after the computation of an identification model. A methodology for the assessment is proposed and the data set generated for the analysis shared openly. Inventory accuracy and location are as-sessed in real scenarios. The proposed solution is demonstrated valuable and ready for the market. Es presenta una solució per a l'automatizació de l'inventari i la localització dels productes de tendes i magatzems. Radio Frequecy Identification (RFID), una tecnologia d'identificació automàtica, i la robòtica mòbil es combinen per dissenyar un robot per a inventaris. La navegació del robot està comandada per un algoritme que escolta el progrés de les noves identificacions. L'algoritme és essencial per tal que el robot obtingui una exactitud superior al 99% i per tal que la duració de l'inventari sigui òptima. S'implementen una interfície d'interacció i el conjunt de procediments necessaris per a operar amb el robot. La localització dels productes s'aborda de dues maneres. La primera consisteix en aplicar clústering a les cadenes d'identificacions dels productes i després assignar la localitzacio coneguda d'un producte de referència a tots els membres del clúster. El segon mètode de localització consisteix en aplicar Bayesian Recursive Estimation després d'haver computat un model d'identificació. Es proposa una metodolgia per a l'avaluació dels inventaris i el dataset generat per a l'anàlisi és compartit obertament. L'exactitud dels inventaris i la localització s'avaluen en escenaris reals. Es demostra que la solució proposada és de valor i està llesta per entrar al mercat.

Passive Gen2 RFID systems based on the wireless communication between readers and tags have become the enabling technology for Internet of Things (IoT) application. Such passive RFID tags are powered up by incident RF power and they respond back to the reader by modulating the backscattering power in terms of changing the tag IC impedance. In various environments this incident power can oscillate and have a certain influence on the power of tag signal. This may have a significant influence on the data available at the reader, especially when analyzing the multiple tag responses, which may happen at the same time (usually referred to as a collision of multiple tags). This paper associates the electromagnetic problem of chip's impedance matching with the variation of tag SNR at the reader. The simulation results depict the difference of tag's backscattering for some chip impedance states. By using fully configurable Software Defined Radio (SDR), the performances of the actual system and characterize the variation of SNR at the reader was retrieved.