RFID Research Articles

Digitalization of the national economy as a driver of virtualization of communications among dairy market stakeholders

Theoretical and methodological approaches to the study of key trends in the digitalisation of the national economy, which act as a driver of virtualisation of communications of dairy market stakeholders, have been studied and substantiated. It is established the different speed and slow implementation of digital accounting technologies in the conditions of differentiation of requests of interested organisations and customers, providing time saving, and communication costs are calculated. On the one hand, the involvement of local computer networks in the internal activities of national organisations, the internet – in the environment of virtual external interaction, rather with suppliers than with consumers, and e-mail, websites – in all spheres of their virtual activity is predominantly developed. On the other hand, there is a big lag in the implementation of such key elements of digital technologies as “big data”, “internet of things”, artificial intelligence models, radio-frequency identification, “digital twins”. The feasibility of creating a web showcase site for virtual interactions between innovatively active dairy enterprises and customers is substantiated.

DNA TRIKKY Based Security Mechanism for Radio Frequency Identification Protocol

Radio frequency identification (RFID) technology has seen rapid expansion in recent years, used in a variety of applications like tracking, monitoring, ticketing, supply-chain management, contactless payments, etc. Several researchers have recommended elliptical curve cryptography (ECC) as a great cryptosystem to pair with RFID technology to increase security and privacy. However, RFID systems have major problems with insecure communication routes, which pose security concerns. In this research, a DNA TRIKKY based security mechanism has been proposed for RFID protocol to mutually authenticate the RFID tag and reader through insecure channels. The proposed solution uses a sponge structure and DNA-XOR to enhance the hash function generation process, preventing sensitive data from being leaked from the backend server. Informal security evaluations provide proof that the proposed method can withstand many attacks. According to performance evaluation, the proposed method performs better than the current protocols, making it ideal for use with RFID systems since it necessitates less processing time, communication costs, and storage costs particularly for the tag. According to the results, the proposed authentication paradigm works well with RFID tags that have limited resources. A comparison of the proposed protocol to other protocols shows that it performs more securely. Studies have found that this method outperforms other existing strategies.

O-211 Exploring risk factors of mismatch in the ART laboratory: An analysis based on 73719 electronic witnessing points

Abstract Study question What are the risk factors associated with mismatch (MM) and genuine mismatch (GMM) in the ART laboratory? Summary answer MM is associated with individual operators, oocyte denudation (OD) and embryo transfer (ET) processes, while GMM related to OD and extended work hours (>4pm). What is known already Mix-up of gametes or embryos in the ART laboratory causes dramatic consequences to both the patients and clinics. Recent studies using electronic witnessing system (EWS) equipped with radio frequency ID (RFID) tags, have revealed that most MM events only involved empty cell culture vessels, while the true mix-up risk arose from a subgroup of GMM involving culture vessels carrying gametes or embryos belonging to different patients. Exploration of risk factors associated with MM and GMM occurrence, separately, is still currently lacking in the literature. Study design, size, duration A total of 73719 witnessing points were retrospectively extracted from an EWS database, representing 11210 consecutive treatment cycles performed at Fertility North between January 2016 and July 2023. The 11210 treatment cycles comprised 5472 fresh IVF, 3732 frozen embryo transfer, 93 oocyte freeze, and 1913 intrauterine insemination cycles. Participants/materials, setting, methods All laboratory work areas were equipped with RFID readers. A MM was triggered by detection of RFID tagged cell culture vessels (either carrying biological material or not) and/or ID cards that belong to different patients in the same work area. A GMM was defined when a MM had involved biological materials and/or patients during procedure, with a potential mix-up. Risk factors evaluated included time of the day, weekdays, weekend, public holiday, operators, and laboratory processes. Main results and the role of chance A total of 138 (0.19%) MMs and 16 (0.02%) GMMs were identified during the study period, without actual mix-up. MM rate was the highest during 12-2pm (0.28%, p < 0.001) compared to other periods of the day, whilst GMM was the highest after 4pm (0.13%, p = 0.004). Neither MM nor GMM was associated with any specific weekday, weekend or public holiday (p > 0.05, respectively). Amongst 8 laboratory processes investigated, ET (0.36%, p < 0.001) led to the highest MM rate, followed by OD (0.35%, p = 0.021), but no increase was observed in oocyte collection, sperm preparation, insemination, embryo culture, cryopreservation and Assign ID. OD was the only process associated with higher GMM (0.13%, p < 0.001). Furthermore, Two of the 20 assessed operators were identified to produce more MMs (0.59%, p < 0.001, and 0.40%, p = 0.004; respectively) while GMM rates were similar among all operators (p > 0.05). Multivariate logistic regression indicated that the OD (adjusted odds ratio or aOR=2.147, p = 0.011) and ET (aOR=2.118, p < 0.001) processes as well as 2 individual operators (aOR=3.511, p < 0.001; aOR=2.538, p = 0.002; respectively) were independent risk factors to MM, but not the 12-2pm period of the day (aOR=1.341, p > 0.05). Finally, both extended work hours beyond 4pm (aOR=8.651, p = 0.005) and OD (aOR=9.538, p < 0.001) were independent risk factors to GMM. Limitations, reasons for caution Each individual ART laboratory has a unique team of scientists and workflow arrangement so findings in our study may not be universally applicable. GMM occurs at an extremely low frequency and is often calculated based on large numbers, therefore caution ought to be taken at statistical interpretation of data. Wider implications of the findings GMMs should be separated from MMs for analysis considering the very different clinical implications. Sufficient staffing with regular break and streamlined workflow are highlighted in preventing mix-up in the ART laboratory. Using electronically logged data, EWS enables identification of site-specific risk factors, which facilitates the development of corresponding preventative protocols. Trial registration number not applicable

Power Consumption Efficiency of Encryption Schemes for RFID

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

Results of shared learning of a new radiofrequency identification localization device—a UK iBRA-NET breast cancer localisation study

Localisation methods for surgical excision of impalpable breast lesions have advanced in recent years, with increasing utilization of new wire-free technologies. The Hologic LOCalizer™ radiofrequency identification (RFID) tag is one such device; however, as is the case when new technologies are first introduced, little is known about clinical experiences, potential complications, and learning used to overcome perioperative challenges when changing from guidewires to RFID tags. This study reports shared learning experiences of clinicians using the LOCalizer™ as part of the national iBRA-NET localisation study. This mixed-methods study captured shared-learning themes relating to LOCalizer™ usage as part of a multicentre prospective registry study, which collected data on each LOCalizer™ placement. Prospective, anonymized clinical and demographic data were collected and managed using a Research Electronic Data Capture (REDCap) database. Shared learning was captured prospectively as part of the registry study between January 2021 and July 2022, combined with a virtual qualitative webinar-style focus group. Learning events were then coded, grouped by theme, and suggestions for practice were produced. Twenty-four UK breast units submitted data on 1188 patient records pertaining to RFID-guided localisation between January 2021 and July 2022, of which 59 (5.0%) included a shared-learning event. The virtual webinar was attended by 108 healthcare professionals, including oncoplastic breast surgeons and breast radiologists. Shared-learning themes were categorized into preoperative, intraoperative, and postoperative events. By sharing learning outcomes associated with localisation techniques in this paper, the aim is to shorten the learning curve and potential for adverse events for users new to the LOCalizer™ technique.

Comparing standard‐ and reduced‐size passive integrated transponder (PIT) tags for monitoring juvenile wild spring Chinook Salmon

AbstractObjectivesAnnual migration monitoring can help to discern patterns and environmental factors that impact growth, survival, and movement timing in small fish. Mark–recapture methods form the basis for such monitoring, and the standard 12‐mm passive integrated transponder (PIT) tag has emerged as an essential tool for studies of juvenile salmonids. A smaller, 9‐mm PIT tag now provides the potential to conduct mark–recapture studies on smaller fish. We evaluated relative performance of the 9‐mm tag, which is similar in design to its 12‐mm predecessor.MethodsFor this comparison, we tagged and released approximately 8400 wild spring Chinook Salmon Oncorhynchus tshawytscha parr in Valley Creek, Idaho, from 2011 to 2013. Tag‐size cohorts were of similar average body size and were tagged in equal numbers. We estimated survival and detection probability for each cohort over two river segments.ResultsIn both segments, survival varied among years, but we observed no significant differences between tag‐size groups. At Valley Creek, average detection rates of fish with 9‐mm tags were a little less than one‐half the rates of fish with 12‐mm tags and were significantly lower in all 3 years. At Lower Granite Dam, detection rates were again lower for 9‐mm tags, but the differences were much smaller (3%–12%) and were not statistically significant.ConclusionWe found that 9‐mm tags can be as effective as 12‐mm tags and may allow for better inference to smaller (<55‐mm) non‐tagged fish. However, the lower detection rates of the 9‐mm tags could lead to less precise estimates, and site‐specific detection rates should be considered for studies that rely on these tags.

Design of a Wind Tunnel Nozzle Section Trolley Control System Based on Backstepping Method

Abstract To accommodate different types of supersonic wind tunnel tests, frequent replacements of nozzle sections and test sections are required, involving multiple complex technical processes. To optimize operational procedures and improve efficiency, a control system for the wind tunnel nozzle section trolley based on the backstepping method was designed. The system uses radio frequency identification (RFID) signals for station positioning and intelligently adjusts the speed and direction of the control motor, thus driving the trolley to move back and forth automatically. Through the simulation of the motor motion control model, the system effectively reduces random disturbances in the motion system caused by load changes, achieves precise positioning of wind tunnel plugins and nozzle assemblies, enhances system operating accuracy, reduces production cycle times, and realizes a one-button positioning function for all components, playing a significant role in improving wind tunnel test efficiency and operational quality.

Power cable monitoring method based on UHF‐RFID and deep learning in edge computing environment

AbstractThis research addresses the challenge faced by most existing prediction methods in handling nonlinear data of cables. Furthermore, it proposes a novel power cable monitoring method utilizing UHF‐RFID and deep learning within an edge computing environment, specifically targeting the currently suboptimal wireless monitoring of cables. First, based on edge computing, a power cable monitoring system is designed to migrate the analysis of massive data to the edge of the network to improve the monitoring efficiency. Then, the temperature sensing chip and RFID chip were integrated to design a UHF‐RFID temperature tag, which was fixed at the cable temperature measurement point to achieve passive wireless monitoring of the cable. Finally, the parameters of the GRNN model are optimized using the beetle antennae search algorithm, and the EEMD decomposed data is input into the BAS‐GRNN model for learning to output temperature prediction results. Based on the establishment of an experimental platform, the method was demonstrated, and results showed that the maximum error between the UHF‐RFID temperature tag temperature measurement results and the thermocouple was within 0.3°C, and the average relative error of the proposed method was only 0.01, which can meet the accuracy requirements of actual monitoring of power cables.

Analysis of Reader Orientation on Detection Performance of Hilbert Curve-based Fractal Chipless RFID Tags

The role of the orientation of the radio frequency identification (RFID) reader is vital in the RFID-based communication system. This study presents the design and analysis of the impact of the orientation of the RFID reader (angle of incidence of the plane wave) on the detection and sensitivity characteristics of fractal chipless RFID tags. Four fractal (irregular) shaped tags are developed using four iterations of the Hilbert curve filling algorithm. The full-wave EM analysis of the designed tags in Matlab is performed by exporting them in Computer Simulation Technologies Micro-Wave Studio (CST MWS) in the frequency range of 2 to 20 GHz. Firstly, the performance of the tags is analyzed by observing the radar cross-section (RCS) of the tag for the fixed orientation of the incident plane wave in three different polarizations (horizontal, vertical, and oblique). Later, the variations in the EM spectrum (RCS results) are analyzed for oblique polarization by varying the incidence plane wave in both elevations (for two cases of 0∘ and 90∘) and azimuth planes (sweeping from 0∘ to 180∘ with a step size of 10∘). The analysis of the proposed aggregated RCS response for all cases in oblique polarization produces higher coding capacity (169 bits), coding spatial capacity (16.504 bits/cm2), coding spectral capacity (9.826 bits/GHz), and coding density (0.960 bits/GHz/cm2) for the realized highly irregular tag using fourth-iteration (4T) of Hilbert curve filling algorithm. The proposed procedure of detection based on aggregated response makes the developed RFID communication system more secure and reliable.

Digital Twin Modeling for Hydropower System Based on Radio Frequency Identification Data Collection

The safe and steady operation of hydropower generation systems is crucial for electricity output in the grid. However, hydropower stations have complicated interior structures, making defect detection difficult without disassembly inspections. The application of digital modeling to hydropower stations will effectively promote the intelligent transformation of hydropower stations as well as reduce the maintenance costs of the system. This study provides a model of the power generating and transmission system for hydropower plants, with an emphasis on primary equipment and measured data. The model utilizes PSCAD to digitalize state response in hydropower plants with various short-circuit faults. The fault information is identified and learned using the Adaptive Time–Frequency Memory (AD-TFM) deep learning model. It is demonstrated that our proposed method can effectively obtain the fault information through radio frequency identification (RFID). The accuracy of the traditional method is 0.90, while the results for AD-TFM show a fault classification accuracy of 0.92, which is more than enough to identify multiple fault types compared to the existing methods.

Rancang Bangun Purwarupa Simulasi Sistem Keamanan Rumah Berbasis Internet of Things

The use of information technology has spread to all fields, for example in the field of security using the Internet of Things technology. One of the places that need to be given security is the home, so that in this study prototypes of home security systems using the Internet of Things have been made with the aim of providing information to homeowners in the event of infiltration through windows or doors, gas leaks and fires. The tools used are Arduino Mega 2560 as a microcontroller, gas sensor, fire sensor, magnetic switch sensor, RFID, keypad, and selenoid. The home security system is made so that homeowners can control the condition of the home. The results of this study are that the home security systems that are made can run well and can be integrated with home security information systems. Sensors can detect gas leaks, fires, and doors or windows open when the security system is active. Homeowners can only turn off the home security system and unlock the door by using RFID tags that have registered IDs and correct passwords. Home security systems can also turn on alarms and send notifications to homeowners, fire stations and police stations in the event of a fire, gas leak or window or door that is opened when the security system is active.

RFID-GSM Automatic Gate Control for Highly Secure Organizations

Abstract: In the current dynamic global landscape, security is paramount for organizations, particularly those entrusted with safeguarding sensitive data and valuable assets. Automatic gate control systems are pivotal in fortifying security and optimizing the operational efficiency of access points for highly secure organizations. By integrating Radio-Frequency Identification (RFID) and Global System for Mobile Communications (GSM) technologies, these systems provide sophisticated features that bolster security measures while enabling seamless access for authorized personnel. These automatic gate control systems provide a multi-layered approach to security, addressing various vulnerabilities and potential threats highly secure organizations face. By leveraging RFID technology, these systems enable efficient and reliable authentication of authorized personnel, minimizing the risk of unauthorized access or breaches. Additionally, the integration of GSM technology enhances the system's responsiveness and remote management capabilities, allowing administrators to monitor gate activities in real time and respond promptly to any security incidents or anomalies.

Student Face Recognition and Alert Rule

Abstract: Attendance marking in a classroom during a lecture is not only an onerous task but also a time-consuming one at. Due to an unusually high number of students present during the lecture, there will always be a probability of proxy attendance(s). Attendance marking with conventional methods has been an area of challenge. The growing need for efficient and automatic techniques for marking attendance is a growing challenge in the area of face recognition. In recent years, the problem of automatic attendance marking has been widely addressed through the use of standard biometrics like fingerprint and Radiofrequency Identification tags, etc., However, these techniques lack the element of reliability. In this proposed project an automated attendance marking and management system is proposed by making use of face detection and recognition algorithms. Instead of using conventional methods, this proposed system aims to develop an automated system that records the student’s attendance by using facial recognition technology. The main objective of this work is to make the attendance marking and management system efficient, time-saving, simple, and easy. Here faces will be recognized using face recognition algorithms. The processed image will then be compared against the existing stored record and then attendance is marked in the database accordingly. Compared to the existing system traditional attendance marking system, this system reduces the workload of people. This proposed system will be implemented with 4 phases Image Capturing, Segmentation of group image and Face Detection, Face comparison and Recognition, and Updating of Attendance in the database. Index Term – Mongo DB, React JS, Node JS, Express JS, Attendance, Facial recognition, and detection, Haar cascade, Alert, Student Face.

Battery-free flexible wireless temperature sensing for food storage

The method of monitoring food temperature during food storage needs to be improved to continuously and accurately perceive the temperature of the food in the package to ensure the quality and safety of the food during storage. This paper proposes and develops a battery-free flexible wireless temperature sensing system (BFTS) for food storage. The BFTS consists of a battery-free flexible wireless temperature sensing tag (BFTT), a wireless reader, and a personal computer (PC). The BFTT developed in this paper has good flexibility and can be placed inside the food package to realize the continuous monitoring of temperature changes. The flexible circuits of the BFTT were fabricated by laser engraving laser-induced graphene (LIG) −copper (Cu) plating film made with Cu plating on LIG. The LIG-Cu plating film has good thickness uniformity, electrical conductivity, and laser engraving processability. The antenna of BFTT has good performance. The wireless reader is connected to the PC using a data line, and the BFTT communicates wirelessly with the wireless reader using ultra-high frequency (UHF) radio frequency identification (RFID). The BFTT was realized by the wireless radio frequency (RF) as the supply power from the wireless reader. The BFTS could realize the temperature monitoring of food stored at 0℃ and −18℃, and it has the advantages of low cost, simple manufacturing process, and low energy consumption, which could be used to continuously and accurately monitor the inside temperature of the food packages. Overall, the LIG-Cu plating film developed in this paper could be used in the fabrication of flexible circuits, and the temperature monitoring inside food packages realized by the BFTS has potential applications in actual food storage.

Collaborative Pricing of Green Supply Chain of Prefabricated Construction

In the process of carbon peak and carbon neutrality, prefabricated buildings have developed rapidly, and the concept of green and low carbon has been introduced into the field of prefabricated buildings. This paper establishes an information sharing platform based on BIM (Building Information Modeling), RFID (Radio Frequency IDentification), and GIS (Geographic Information System) technologies from the green supply chain of prefabricated buildings. On the basis of information sharing, the Stackelberg two-stage game is used to analyze and compare the overall profit of the supply chain under the centralized pricing decision and the decentralized pricing decision. Through numerical simulation, this paper analyzes the relationship between pricing and the overall profit of the supply chain, compares the difference of the overall profit of supply chain under two different pricing strategies, centralized pricing and decentralized pricing, and analyzes the influence of information sharing degree on the overall profit of the supply chain. The results show that the overall profit of the supply chain under centralized pricing decisions is significantly higher than that under decentralized pricing decisions. The higher the degree of information sharing, the greater the overall profit of the supply chain.

Digital Transformation in IT Asset Management Process

Information Technology Asset Management (ITAM) is a key process in the Information Technology (IT) sector. Since the late 20th century, maintaining a growing number of IT assets has become a challenging task. It requires technological advancements to streamline ITAM processes efficiently and cost- effectively. The digital transformation of ITAM processes can help organizations overcome many challenges. Digitalizing asset management processes requires a centralized repository for efficiently managing IT assets, such as workstations, laptops, and even software assets. This enhances security and ensures that assets adhere to security compliance. Technologies for digital transformation, alongside techniques such as process automation and the adoption of advanced Radio Frequency Identification (RFID) technology, can be utilized to improve ITAM. These technologies and techniques enable organizations to improve their asset management processes, meeting the organization's needs. This paper addresses the impact of digital transformation on IT Asset Management and explores areas for process improvement. Digital transformation impacts Asset Management by enabling faster asset- related decision-making, optimizing asset utilization, reducing maintenance costs, and providing greater transparency and asset traceability.

Circuits for Printed Electronics for Flexible Displays & Sensors

Printed circuits are crucial components in the field of printed electronics, enabling the creation of flexible, lightweight, and cost-effective electronic devices. This proposal explores the fabrication techniques, materials, and applications of printed circuits in printed electronics. Various printing methods such as inkjet, screen, and flexography are discussed, along with the integration of conductive inks and substrates. The versatility of printed circuits allows for the development of diverse electronic products including wearable sensors, RFID tags, and flexible displays. Moreover, advancements in additive manufacturing technologies continue to drive innovation in printed circuit design and production, promising a future of increasingly sophisticated printed electronic devices.

Mobilefacenet-Based Facial Recognition System for Contactless Access Control

Conventional access control systems require physical contact, such as pressing buttons, using fingerprints, or employing radio-frequency identification (RFID). These interactions increase the risk of transmitting diseases like COVID-19 through surface contact. To mitigate this risk, a contactless identification method becomes imperative. Hence, this study proposes an adaptive and seamless dual-mode mobile facial recognition-based access control system. Specifically, the proposed system uses a convolutional neural network (CNN) algorithm (MobileFaceNet) to develop high-precision facial verification on mobile devices with a dual-mode (real-time and offline) facial recognition system. The system is implemented on Raspberry Pi, running an Android Operating System equipped with camera functionality. The system instantaneously operates by detecting human faces, compares the faces with a pre-existing database, and grants access to successful matches. The system underwent preliminary testing on an Android 9 device with an 8-megapixel camera. Faces were detected and recognised in a record time (within seconds), showcasing commendable accuracy. The system achieved a recognition accuracy of 95% under varied lighting conditions and distances. The proposed system can be seamlessly integrated with electronic doors, ensuring optimal access control for smart homes and restricted facilities.Keywords: Access control, convolutional neural network, face recognition, firebase, mobilefacenet

Timber Traceability and Sustainable Transportation Management: A Review of Technologies and Procedures

There has been considerable research on sustainable forest management due to its importance in ensuring the long-term health of the forests and its industries. Traceability is an important tool to ensure that the wood and wood-based products are produced in a legal, sustainable, and ethical manner. Therefore, various technologies were implemented within the supply chain to monitor and trace the wood with the aim of fulfilling the traceability objectives. Using a systematic literature review, this paper provides a comprehensive state-of-the-art on the technologies and procedures used in timber traceability and transportation management. It debates traceability tradition and advanced methods such as smart marking, QR (Quick Response) codes, DNA fingerprinting, smartphone apps, RFID (Radio Frequency Identification), machine learning, and computer vision since these technologies enable the integrity of the supply chain by documenting the source of wood and following up on the wood in all the stages, beginning from the standing tree until the final customer. The paper also reviews the advancements in wood transportation management systems, including spatial databases, GPS (Global Positioning System), and fleet management systems, which ultimately lead to real-time monitoring and optimisation of transportation routes, leading to improved efficiency and minimal environmental impact. The review results acknowledge that financial constraints, infrastructure limitations, data management uncertainties, acceptance and compliance issues, and stakeholder commitment are still challenges to implementing traceability technology in the forestry sector. Moreover, this review not only highlights how traceability systems promote responsible forestry practices, ensure sustainable timber sourcing, and develop supply chain management, but also the advantages of utilising these technological advances at economic, social, and environmental levels.

Automated monitoring of brush use in dairy cattle.

Access to brushes allows for natural scratching behaviors in cattle, especially in confined indoor settings. Cattle are motivated to use brushes, but brush use varies with multiple factors including social hierarchy and health. Brush use might serve an indicator of cow health or welfare, but practical application of these measures requires accurate and automated monitoring tools. This study describes a machine learning approach to monitor brush use by dairy cattle. We aimed to capture the daily brush use by integrating data on the rotation of a mechanical brush with data on cow identify derived from either 1) low-frequency radio frequency identification or 2) a computer vision system using fiducial markers. We found that the computer vision system outperformed the RFID system in accuracy, and that the machine learning algorithms enhanced the precision of the brush use estimates. This study presents the first description of a fiducial marker-based computer vision system for monitoring individual cattle behavior in a group setting; this approach could be applied to develop automated measures of other behaviors with the potential to better assess welfare and improve the care for farm animals.