Radiofrequency identification tracking system (RFID) significantly improves blood bank inventory management and decreases staff work effort.

BACKGROUND: Before implementation of the radio frequency identification (RFID) system, there was a high loss rate of 4.0%-4.3% of red blood cell (RBC) units every year expiring on the shelf in our transfusion service laboratory. We introduced RFID technology to improve inventory management and the burden of work on the staff. The goal of this study was to evaluate the impact of RFID technology on the inventory management of RBC units and the staff workload in a transfusion service laboratory. STUDY DESIGN AND METHODS: Using an RFID system involves encoding RBC units with an RFID tag capturing information such as donor identification number, product code, blood type, expiration date, product volume, and negative antigen(s). Tag information is collected through retrofitted storage shelves linked to the RFID server. The study analyzed RBC usage by unit and by volume (mL) and staff work effort to carry out inventory management tasks before and after the implementation of the RFID system. RESULTS: Implementation of the RFID technology reduced the loss, or discard, of RBC units to less than 1% annually (a statistically significant change, p < .001). The RFID computer dashboard provides a constant visual update of the inventory, allowing technologists to have accurate product counts and reducing their work burden. DISCUSSION: Implementation of RFID technology substantially reduced RBC product loss, improved inventory management, and lessened staff work burden.

Male starling floaters preferentially visit nests of males with reduced resource holding potential.

Floaters are sexually mature individuals that are not able to reproduce by defending breeding resources. Floaters often visit active nests, probably to gather public information or to compete for a nesting site. We tested the hypothesis that floaters preferentially prospect nests in which they have a better chance of taking over, and that they do so by assessing the owners' resource holding potential (RHP). We manipulated the flight capacity of male and female breeders in a population of spotless starlings (Sturnus unicolor) by clipping two flight feathers per wing before egg laying, thus increasing their wing-load and likely impairing their condition. We subsequently monitored breeder and floater activity by means of transponder readers during the nestling period. We found that nests owned by wing-clipped males were visited by a greater number of male floaters than control nests. This effect was absent in the case of wing-clipped females. The number of male floaters also increased with increasing nestling age and number of parental visits. The experiment shows that male floaters preferentially prospect nests in which the owner shows a reduced RHP, a strategy that likely allows them to evict weak owners and take over their nests for future reproductive attempts.

Propagation Analysis of an RFID System in the UHF Band in the Honeycomb Frame of a Beehive.

In recent years, communication systems, including RFID, have been used in intelligent beehives for beekeeping. RFID systems in the UHF frequency band offer reading distances of tens of centimetres, allowing the localisation and identification of the queen bee inside the hive. With this purpose, this work proposes an analysis of an environment of propagation that consists of a honeycomb frame, where the reader is placed within the frame, and the tag is placed in different positions over it. A honeycomb frame consists of a wooden box containing a honey wax panel, supported by metallic wires. The environment is modelled theoretically using its S-parameters and simulated in CST Studio. An analysis of these results and empirical measurements is performed. The results show that a periodicity in the received power of the tag is found with respect to the distance to the reader when the tag is located in a direction parallel to the wire, where local maximum and minimum values are found. Additionally, when the tag is placed over a wire of the frame, a higher received power is obtained compared to the case where the tag is placed between two wires. Furthermore, it has been observed that the reading range has increased with respect to free space, covering the full frame.

Artificial Intelligence-Assisted RFID Tag-Integrated Multi-Sensor for Quality Assessment and Sensing.

Radio frequency identification (RFID) is well known as an identification, track, and trace approach and is considered to be the key physical layer technology for the industrial internet of things (IIoT). However, IIoT systems have to introduce additional complex sensor networks for pervasive monitoring, and there are still challenges related to item-level sensing and data recording. To overcome the shortage, this work proposes an artificial intelligence (AI)-assisted RFID-based multi-sensing technology. Both passive and semi-passive RFID tag-integrated multi-sensors are developed. The main contributions and the novelty of this investigation are as follows. A UHF RFID tag-integrated multi-sensor with a boosted charge pump is proposed; it enables high RF signal sensitivity and a long operational range. The whole hardware design, including the antenna and energy harvester, are studied. Moreover, a demonstration with real-world ham product sensing data is conducted. This work also proposes and successfully demonstrates the integration of machine learning algorithms, specifically the NARX neural network, with RFID sensing data for food product quality assessment and sensing (QAS). This application of machine learning to RFID-generated data for quality assessment is also a novel aspect of the research. The deployment of an autoregressive model with an exogenous input (NARX) neural network model, tailored for nonlinear processes, emerges as the most effective, achieving a root mean square error (RMSE) of 0.007 and an R-squared value of 0.99 for ham product QAS. By deploying the technology, low-cost, timely, and flexible product QAS can be achieved in manufacturing industries, which helps product quality improvement and the optimization of the manufacturing line and supply chain.

Empowering the Blind: Contactless Activity Recognition with Commodity Software-Defined Radio and Ultra-High-Frequency Radio Frequency Identification.

This study presents a novel computational radio frequency identification (RFID) system designed specifically for assisting blind individuals, utilising software-defined radio (SDR) with coherent detection. The system employs battery-less ultra-high-frequency (UHF) tag arrays in Gen2 RFID systems, enhancing the transmission of sensed information beyond standard identification bits. Our method uses an SDR reader to efficiently manage multiple tags with Gen2 preambles implemented on a single transceiver card. The results highlight the system's real-time capability to detect movements and direction of walking within a four-meter range, indicating significant advances in contactless activity monitoring. This system not only handles the complexities of multiple tag scenarios but also delineates the influence of system parameters on RFID operational efficiency. This study contributes to assistive technology, provides a platform for future advancements aimed at addressing contemporary limitations in pseudo-localisation, and offers a practical, affordable assistance system for blind individuals.

A Compact and Robust RFID Tag Based on an AMC Structure.

A platform-tolerant RFID (Radio-Frequency Identification) tag is presented, designed to operate across the entire RFID band. This tag utilizes a small Artificial Magnetic Conductor (AMC) structure as a shielding element for an ungrounded RFID tag antenna. It can be easily mounted on various surfaces, including low permittivity dielectric materials, metal objects, or even attached to the human body for wearable applications. The key features of this RFID tag include its ability to be tuned within the worldwide RFID band, achieving a maximum theoretical read range of over 11 m. Despite its advanced capabilities, the design emphasizes simplicity and cost-effective manufacturing. The design and simulations were conducted using CST Studio Suite.

Textronic Capacitive Sensor with an RFID Interface.

This article presents an innovative combination of textile electrical circuits with advanced capabilities of electronic RFID sensors, indicating the revolutionary nature of the development of textronics, which is used in various areas of life, from fashion to medicine. A review of the literature relating to the construction of textronic RFID identifiers and capacitive textronic sensors is performed. Various approaches to measuring capacity using RFID tags are discussed. This article focuses on presenting the concept of a capacitive sensor with an RFID interface, consisting of a microelectronic part and a textile part. The textile part is based on the WL4007 material, where antennas and capacitive sensors are embroidered using SPARKFUN DEV 11791 conductive thread. The antenna is a half-wave dipole designed to operate at a frequency of 860 MHZ. The microelectronic part is sewn to the textile part and consists of a microcontroller, an RFID-integrated circuit and a coupling loop, placed on the PCB. The embroidered antenna is coupled with a loop on the microelectronic module. This article focuses on presenting various designs of textronic electrodes, enabling various types of measurements. Article presents capacitance measurements of individual sensor electrodes, made using a measuring bridge and a built RFID tag. The sensors' capacity measurement results are shown.

Displacement Estimation via 3D-Printed RFID Sensors for Structural Health Monitoring: Leveraging Machine Learning and Photoluminescence to Overcome Data Gaps.

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace.

Planar Thermoelectric Microgenerators in Application to Power RFID Tags.

This paper presents an innovative approach to the integration of thermoelectric microgenerators (µTEGs) based on thick-film thermopiles of planar constantan-silver (CuNi-Ag) and calcium cobaltite oxide-silver (Ca3Co4O9-Ag) thick-film thermopiles with radio frequency identification (RFID) technology. The goal was to consider using the TEG for an active or semi-passive RFID tag. The proposed implementation would allow the communication distance to be increased or even operated without changing batteries. This article discusses the principles of planar thermoelectric microgenerators (µTEGs), focusing on their ability to convert the temperature difference into electrical energy. The concept of integration with active or semi-passive tags is presented, as well as the results of energy efficiency tests, considering various environmental conditions. On the basis of the measurements, the parameters of thermopiles consisting of more thermocouples were simulated to provide the required voltage and power for cooperation with RFID tags. The conclusions of the research indicate promising prospects for the integration of planar thermoelectric microgenerators with RFID technology, opening the way to more sustainable and efficient monitoring and identification systems. Our work provides the theoretical basis and practical experimental data for the further development and implementation of this innovative technology.

Applications of Chipless RFID Humidity Sensors to Smart Packaging Solutions.

Packaging solutions have recently evolved to become smart and intelligent thanks to technologies such as RFID tracking and communication systems, but the integration of sensing functionality in these systems is still under active development. In this paper, chipless RFID humidity sensors suitable for smart packaging are proposed together with a novel strategy to tune their performances and their operating range. The sensors are flexible, fast, low-cost and easy to fabricate and can be read wirelessly. The sensitivity and the humidity range where they can be used are adjustable by changing one of the sensor's structural parameters. Moreover, these sensors are proposed as double parameter sensors, using both the frequency shift and the intensity variation of the resonance peak for the measure of the relative humidity. The results show that the sensitivity can vary remarkably among the sensors proposed, together with the operative range. The sensor suitability in two specific smart packaging applications is discussed. In the first case, a threshold sensor in the low-humidity range for package integrity verification is analyzed, and in the second case, a more complex measurement of humidity in non-hermetic packages is investigated. The discussion shows that the sensor configuration can easily be adapted to the different application needs.

Compact Wideband Tapered Slot Antenna Using Fan-Shaped and Stepped Structures for Chipless Radio-Frequency-Identification Sensor Tag Applications.

In this paper, two kinds of miniaturization methods for designing a compact wideband tapered slot antenna (TSA) using either fan-shaped structures only or fan-shaped and stepped structures were proposed. First, a miniaturization method appending the fan-shaped structures, such as quarter circular slots (QCSs), half circular slots (HCSs), and half circular patches (HCPs), to the sides of the ground conductor for the TSA was investigated. The effects of appending the QCSs, HCSs, and HCPs sequentially on the input reflection coefficient and gain characteristics of the TSA were compared. The compact wideband TSA using the first miniaturization method showed the simulated frequency band for a voltage standing wave ratio (VSWR) less than 2 of 2.530-13.379 GHz (136.4%) with gain in the band ranging 3.1-6.9 dBi. Impedance bandwidth was increased by 29.7% and antenna size was reduced by 39.1%, compared to the conventional TSA. Second, the fan-shaped structures combined with the stepped structures (SSs) were added to the sides of the ground conductor to further miniaturize the TSA. The fan-shaped structures based on the HCSs and HCPs were appended to the ground conductor with the QCSs and SSs. The compact wideband TSA using the second miniaturization method had the simulated frequency band for a VSWR less than 2 of 2.313-13.805 GHz (142.6%) with gain in the band ranging 3.0-8.1 dBi. Impedance bandwidth was increased by 37.8% and antenna size was reduced by 45.9%, compared to the conventional TSA. Therefore, the increase in impedance bandwidth and the size reduction effect of the compact wideband TSA using the second miniaturization method were better compared to those using the first method. In addition, sidelobe levels at high frequencies decreased while gain at high frequencies increased. A prototype of the compact wideband TSA using the second miniaturization method was fabricated on an RF-35 substrate to validate the simulation results. The measured frequency band for a VSWR less than 2 was 2.320-13.745 GHz (142.2%) with measured gain ranging 3.1-7.9 dBi.

Novel Technologies towards the Implementation and Exploitation of "Green" Wireless Agriculture Sensors.

This manuscript presents the use of three novel technologies for the implementation of wireless green battery-less sensors that can be used in agriculture. The three technologies, namely, additive manufacturing, energy harvesting, and wireless power transfer from airborne transmitters carried from UAVs, are considered for smart agriculture applications, and their combined use is demonstrated in a case study experiment. Additive manufacturing is exploited for the implementation of both RFID-based sensors and passive sensors based on humidity-sensitive materials. A number of energy-harvesting systems at UHF and ISM frequencies are presented, which are in the position to power platforms of wireless sensors, including humidity and temperature IC sensors used as agriculture sensors. Finally, in order to provide wireless energy to the soil-based sensors with energy harvesting features, wireless power transfer (WPT) from UAV carried transmitters is utilized. The use of these technologies can facilitate the extensive use and exploitation of battery-less wireless sensors, which are environmentally friendly and, thus, "green". Additionally, it can potentially drive precision agriculture in the next era through the implementation of a vast network of wireless green sensors which can collect and communicate data to airborne readers so as to support, the Artificial Intelligence and Machine Learning-based decision-making with data.

The Rise of Passive RFID RTLS Solutions in Industry 5.0.

In today's competitive landscape, manufacturing companies must embrace digital transformation. This study asserts that integrating Internet of Things (IoT) technologies for the deployment of real-time location systems (RTLS) is crucial for better monitoring of critical assets. Despite the challenge of selecting the right technology for specific needs from a wide range of indoor RTLS options, this study provides a solution to assist manufacturing companies in exploring and implementing IoT technologies for their RTLS needs. The current academic literature has not adequately addressed this industrial reality. This paper assesses the potential of Passive UHF RFID-RTLS in Industry 5.0, addressing the confusion caused by the emergence of new 'passive' RFID solutions that compete with established 'active' solutions. Our research aims to clarify the real-world performance of passive RTLS solutions and propose an updated classification of RTLS systems in the academic literature. We have thoroughly reviewed both the academic and industry literature to remain up to date with the latest market advancements. Passive UHF RFID has been proven to be a valuable addition to the RTLS domain, capable of addressing certain challenges. This has been demonstrated through the successful implementation in two industrial sites, each with different types of tagged objects.

Radiofrequency localization of nonpalpable breast cancer in a multicentre prospective cohort study: feasibility, clinical acceptability, and safety.

PURPOSE: In breast conserving surgery, accurate lesion localization is essential for obtaining adequate surgical margins. Preoperative wire localization (WL) and radioactive seed localization (RSL) are widely accepted methods to guide surgical excision of nonpalpable breast lesions but are limited by logistical challenges, migration issues, and legislative complexities. Radiofrequency identification (RFID) technology may offer a viable alternative. The purpose of this study was to evaluate the feasibility, clinical acceptability, and safety of RFID surgical guidance for localization of nonpalpable breast cancer. METHODS: In a prospective multicentre cohort study, the first 100 RFID localization procedures were included. The primary outcome was the percentage of clear resection margins and re-excision rate. Secondary outcomes included procedure details, user experience, learningcurve, and adverse events. RESULTS: Between April 2019 and May 2021, 100 women underwent RFID guided breast conserving surgery. Clear resection margins were obtained in 89 out of 96 included patients (92.7%), re-excision was indicated in three patients (3.1%). Radiologists reported difficulties with the placement of the RFID tag, partially related to the relatively large needle-applicator (12-gauge). This led to the premature termination of the study in the hospital using RSL as regular care. The radiologist experience was improved after a manufacturer modification of the needle-applicator. Surgical localization involved a low learning curve. Adverse events (n = 33) included dislocation of the marker during insertion (8%) and hematomas (9%). The majority of adverse events (85%) occurred using the first-generation needle-applicator. CONCLUSION: RFID technology is a potential alternative for non-radioactive and non-wire localization of nonpalpable breast lesions.

Measuring body temperature in birds - the effects of sensor type and placement on estimated temperature and metabolic rate.

Several methods are routinely used to measure avian body temperature, but different methods vary in invasiveness. This may cause stress-induced increases in temperature and/or metabolic rate and, hence, overestimation of both parameters. Choosing an adequate temperature measurement method is therefore key to accurately characterizing an animal's thermal and metabolic phenotype. Using great tits (Parus major) and four common methods with different levels of invasiveness (intraperitoneal, cloacal, subcutaneous, cutaneous), we evaluated the preciseness of body temperature measurements and effects on resting metabolic rate (RMR) over a 40°C range of ambient temperatures. None of the methods caused overestimation or underestimation of RMR compared with un-instrumented birds, and body or skin temperature estimates did not differ between methods in thermoneutrality. However, skin temperature was lower compared with all other methods below thermoneutrality. These results provide empirical guidance for future research that aims to measure body temperature and metabolic rate in small bird models.

Manipulating actions: A selective two-option device for cognitive experiments in wild animals.

Advances in biologging technologies have significantly improved our ability to track individual animals' behaviour in their natural environment. Beyond observations, automation of data collection has revolutionized cognitive experiments in the wild. For example, radio-frequency identification (RFID) antennae embedded in 'puzzle box' devices have allowed for large-scale cognitive experiments where individuals tagged with passive integrated transponder (PIT) tags interact with puzzle boxes to gain a food reward, with devices logging both the identity and solving action of visitors. Here, we extended the scope of wild cognitive experiments by developing a fully automated selective two-option foraging device to specifically control which actions lead to a food reward and which remain unrewarded. Selective devices were based on a sliding-door foraging puzzle, and built using commercially available low-cost electronics. We tested it on two free-ranging PIT-tagged subpopulations of great tits Parus major as a proof of concept. We conducted a diffusion experiment where birds learned from trained demonstrators to get a food reward by sliding the door either to the left or right. We then restricted access of knowledgeable birds to their less preferred side and calculated the latency until birds produced solutions as a measure of behavioural flexibility. A total of 22 of 23 knowledgeable birds produced at least one solution on their less preferred side after being restricted, with higher-frequency solvers being faster at doing so. In addition, 18 of the 23 birds reached their solving rate from prior to the restriction on their less preferred side, with birds with stronger prior side preference taking longer to do so. We therefore introduce and successfully test a new selective two-option puzzle box, providing detailed instructions and freely available software that allows reproducibility. It extends the functionality of existing systems by allowing fine-scale manipulations of individuals' actions and opens a large range of possibilities to study cognitive processes in wild animal populations.

An ecologist's introduction to continuous-time multi-state models for capture-recapture data.

Recent technological advances have led to a rapid increase in the collection of capture-recapture data in continuous time. Unlike traditional capture-recapture data, the detection times from these technologies are themselves random variables and analysis of these data, therefore, requires models that properly account for stochasticity in both state transitions and detection times. Despite the ubiquity of continuously collected capture-recapture data, the mathematical concepts needed to fit continuous-time models remain unfamiliar to many ecologists. In this paper, I provide an introduction to continuous-time models, with a focus on multi-state capture-recapture data. After reviewing the basic structure of these models, I describe several variations, including constant parameters, temporal variation in state transition rates and autocorrelation in detections. To aid comprehension, each model is accompanied by code to simulate data and fit the model in Stan. Although the models presented in this guide are only a small subset of the variations that are possible to suit the needs of specific datasets or questions, the concepts and code will hopefully serve as a foundation for future analyses, allowing ecologists to develop new and creative approaches to continuous-time modelling.

Mesocosm experiment reveals scale dependence of movement tendencies in sticklebacks.

Habitat fragmentation can have negative impacts on migratory organisms that rely on the functional connectivity between growing and breeding grounds. Quantifying the population-level phenotypic consequences of such fragmentation requires fine-scaled tracking of individual behaviour and movements across relevant scales. Here we make use of a natural experiment where some populations of 'migrant' three-spined sticklebacks (Gasterosteus aculeatus) became 'residents', following habitat fragmentation five decades ago. To test whether residents have a lower movement tendency than migrants, we developed a novel experimental platform that allows the automated tracking of individual movements via RFID technology in a semi-natural mesocosm where spatio-temporal scales and environmental conditions can be manipulated. We found that residents moved significantly less than migrants at large but not at small spatial scale. This pattern was consistent across time and contexts (water flow and group size). Our study substantiates prior literature on rapid phenotypic divergence in sticklebacks in response to human-induced isolation and highlights the importance of observing behaviour in ecologically relevant set-ups that bridge the gap between laboratory and field studies.

Evaluation of the radiofrequency identification lung marking system: a multicenter study in Japan.

BACKGROUND: The radiofrequency identification (RFID) lung marking system is a novel technique using near-field radio-communication technology. The purpose of this study was to investigate the utility and feasibility of this system in the resection of small pulmonary nodules. METHODS: We retrospectively reviewed clinical records of 182 patients who underwent sublobar resection with the RFID marking system between March 2020 and November 2021 in six tertial hospitals in Japan. Target markings were bronchoscopically made within 3 days before surgery. The contribution of the procedure to the surgery and safety was evaluated. RESULTS: Target nodule average diameter and depth from the lung surface were 10.9 ± 5.4 mm and 14.6 ± 9.9 mm, respectively. Radiologically, one third of nodules appeared as pure ground-glass nodules (GGNs) on CT. The average distance from target nodule to RFID tag was 8.9 ± 7.1 mm. All surgical procedures were completed by video-assisted thoracoscopic surgery. Planned resection was achieved in all cases without any complications. The surgeons evaluated this system as helpful in 93% (necessary: 67%, useful; 26%) of cases. Nodule radiological features (p < 0.001) and type of surgery (p = 0.0013) were associated with the degree of contribution. In most cases, identification of the RFID tag was required within 1 min despite adhesion (p = 0.27). CONCLUSION: The RFID lung marking system was found to be safe and effective during successful sublobar resection. Patients with pure GGNs are the best candidates for the system.

RF-Alphabet: Cross Domain Alphabet Recognition System Based on RFID Differential Threshold Similarity Calculation Model.

Gesture recognition can help people with a speech impairment to communicate and promote the development of Human-Computer Interaction (HCI) technology. With the development of wireless technology, passive gesture recognition based on RFID has become a research hotspot. In this paper, we propose a low-cost, non-invasive and scalable gesture recognition technology, and successfully implement the RF-alphabet, a gesture recognition system for complex, fine-grained, domain-independent 26 English letters; the RF-alphabet has three major advantages: first, this paper achieves complete capture of complex, fine-grained gesture data by designing a dual-tag, dual-antenna layout. Secondly, to overcome the disadvantages of the large training sets and long training times of traditional deep learning. We design and combine the Difference threshold similarity calculation prediction model to extract digital signal features to achieve real-time feature analysis of gesture signals. Finally, the RF alphabet solves the problem of confusing the signal characteristics of letters. Confused letters are distinguished by comparing the phase values of feature points. The RF-alphabet ends up with an average accuracy of 90.28% and 89.7% in different domains for new users and new environments, respectively, by performing feature analysis on similar signals. The real-time, robustness, and scalability of the RF-alphabet are proven.