IVF laboratory management through workflow-based RFID tag witnessing and real-time information entry.

BACKGROUND: Dual-person inspection in IVF laboratories cannot fully avoid mix-ups or embryo transfer errors, and data transcription or entry is time-consuming and redundant, often leading to delays in completing medical records. METHODS: This study introduced a workflow-based RFID tag witnessing and real-time information entry platform for addressing these challenges. To assess its potential in reducing mix-ups, we conducted a simulation experiment in semen preparation to analyze its error correction rate. Additionally, we evaluated its impact on work efficiency, specifically in operation and data entry. Furthermore, we compared the cycle costs between paper labels and RFID tags. Finally, we retrospectively analyzed clinical outcomes of 20,424 oocyte retrieval cycles and 15,785 frozen embryo transfer cycles, which were divided into paper label and RFID tag groups. RESULTS: The study revealed that comparing to paper labels, RFID tag witnessing corrected 100% of tag errors, didn't affect gamete/embryo operations, and notably shorten the time of entering data, but the cycle cost of RFID tags was significantly higher. However, no significant differences were observed in fertilization, embryo quality, blastocyst rates, clinical pregnancy, and live birth rates between two groups. CONCLUSIONS: RFID tag witnessing doesn't negatively impact gamete/embryo operation, embryo quality and pregnancy outcomes, but it potentially reduces the risk of mix-ups or errors. Despite highly increased cost, integrating RFID tag witnessing with real-time information entry can remarkably decrease the data entry time, substantially improving the work efficiency. This workflow-based management platform also enhances operational safety, ensures medical informational integrity, and boosts embryologist's confidence.

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.

Passive UHF RFID-based real-time intravenous fluid level sensor.

Ultra high frequency (UHF) passive radio frequency identification (RFID) tag-based sensors are proposed for intravenous (IV) fluid level monitoring in medical Internet of Things (IoT) applications. Two versions of the sensor are proposed: a binary sensor (i.e., full vs. empty state sensing) and a real-time (i.e., continuous level) sensor. The operating principle is demonstrated using full-wave electromagnetic simulation at 910 MHz and validated with experimental results. Generalized Additive Model (GAM) and random forest algorithms are employed for each interrogation dataset. Real-time sensing is accomplished with small deviations across the models. A minimum of 72% and a maximum of 97% of cases are within a 20% error for the GAM model and 62% to 98% for the random forest model. The proposed sensor is battery-free, lightweight, low-cost, and highly reliable. The read range of the proposed sensor is 4.6 m.

Design and research of multi-information fusion RFID sensor for fruit and vegetable quality detection.

With the increasing demand for fruits and vegetables in the market, the development of cold chain logistics has put forward higher requirements for the quality of fruits and vegetables in storage. To ensure the freshness of fruits and vegetables during storage and transportation and avoid unnecessary loss, it is necessary to conduct real-time detection of their odor to ensure their quality. Therefore, based on nano-composite materials combined with Radio Frequency Identification (RFID) technology, this paper designs an integrated RFID sensor that can simultaneously detect temperature, carbon dioxide, and ethanol concentrations. The test results show that the sensor has a high sensitivity of 0.25 dB/°C, 0.011 dB/ppm, and 0.65 MHz/ppm for detecting temperature, carbon dioxide, and ethanol concentration, respectively. The sensor also uses Printed Circuit Board (PCB) technology to make the sensor base, which has the advantages of low cost, easy portability, and mass production capability. The results obtained evidence that the system meets the requirements of environmental monitoring for fruit and vegetable storage, runs stably, and has a high use value.

Radiofrequency as a method of localizing impalpable breast lesions.

BACKGROUND: The incidence of early stage breast cancer has risen as a result of increased detection of non-palpable tumors through the implementation of screening programs and greater public awareness. Performing breast-conserving surgery can be challenging due to the need for accurate localization of non-palpable breast lesions, particularly given the logistical difficulties associated with wire localization. After implementing a new technique for localizing non-palpable breast lesions (LOCalizerTM Radiofrequency identification TAG-Hologic®), a radiofrequency identification tag localization device manufactured by Hologic, Inc. in Marlborough, MA, was launched in 2017, our objective was to investigate its impact on surgical outcomes, whether there was an increase in re-excision rates for positive margins and whether the attainment of clear margins was dependent on the exact positioning of the RFID device. METHOD: A single-center single-arm interventional study, data were gathered both in a forward-looking manner for 1 year (prospectively) and by looking back at past records for 1 year (retrospectively) for a total period of two years. Individuals who were diagnosed with non-palpable breast lesions, as confirmed by histological analysis, or invasive breast cancer and who were scheduled to undergo breast-conserving surgery were eligible for inclusion in the study. The RFID (Radiofrequency Identification) method was used to localize the lesions prior to surgery. Either with a mammogram or ultrasound scan position of the Tag was recorded, including the distance of the lesion from the center of the lesion and the lesion depth from the skin in millimeters. The rate of re-excision was documented and examined in relation to the parameters mentioned above. RESULTS: Two hundred and twenty RFID Tags were inserted in two hundred and seventeen (three patient had bilateral tags insertion), patients aged between 30 and 85 had a localizer Tag inserted between Oct 2020 and Oct 2022. Three patients had non-palpable breast lesions in both breasts. Fourteen were inserted under stereotactic guidance and two hundred and six under ultrasound guidance. Ten patients subsequently had wire insertion also due to Tag position. Of 210 procedures, RFIF Tags within the lesion was seen in hundred and sixty patients (76.19 %). An additional 50 procedures were performed using the RFID Tag system, which were not directly related to the lesion but were deemed appropriate to proceed with. Out of a total of 220 procedures, positive margins were observed in 38 cases (17.27 %). Among these cases, eleven (28.94 %) involved the use of the RFID Tag system, not within the lesion but adjacent to it (within 15 mm surrounding the lesion). CONCLUSION: RFID is a good alternative to wire localization of non-palpable breast lesions. Re-excision rates are higher in patients with Tag outside the lesion compared to those with Tag within the lesion.

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.

Design and Implementation of Digital Calibration Certificate for RFID Tag Storage.

The digital transformation of metrology is one of the most active activities in the field of metrology at present, where the digital calibration certificate (DCC) being developed is the topic receiving the most concern in the current digital transformation. In practical industrial applications, the issue of storage carrier for the DCC plays a crucial role in its promotion and implementation. To address this issue, a DCC meta-model called DCC-Lite schema has been designed along with a corresponding processing method. This solution involves compressing and segmenting the DCC to make it suitable for storage using RFID tags. These RFID tags are affixed to the instruments and accompany them throughout their usage. Additionally, the DCC-RFID processing system has been developed to validate the effectiveness of the DCC meta-model and its corresponding processing method within a wireless temperature acquisition system. Experimental results demonstrate that the system successfully reads and writes the DCC stored within the RFID tag group. Furthermore, it enables automated parsing of the DCC calibration data by the machine and real-time compensation of measurement data to reduce measurement errors.

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 Wireless Network for Monitoring Pesticides in Groundwater: An Inclusive Approach for a Vulnerable Kenyan Population.

Safe drinking water is essential to a healthy lifestyle and has been recognised as a human right by numerous countries. However, the realisation of this right remains largely aspirational, particularly in impoverished nations that lack adequate resources for water quality testing. Kenya, a Sub-Saharan country, bears the brunt of this challenge. Pesticide imports in Kenya increased by 144% from 2015 to 2018, with sales data indicating that 76% of these pesticides are classified as highly hazardous. This trend continues to rise. Over 70% of Kenya's population resides in rural areas, with 75% of the rural population engaged in agriculture and using pesticides. Agriculture is the country's main economic activity, contributing over 30% of its gross domestic product (GDP). The situation is further exacerbated by the lack of monitoring for pesticide residues in surface water and groundwater, coupled with the absence of piped water infrastructure in rural areas. Consequently, contamination levels are high, as agricultural runoff is a major contaminant of surface water and groundwater. The increased use of pesticides to enhance agricultural productivity exacerbates environmental degradation and harms water ecosystems, adversely affecting public health. This study proposes the development of a wireless sensor system that utilizes radio-frequency identification (RFID), Long-range (LoRa) protocol and a global system for mobile communications (GSM) for monitoring pesticide prevalence in groundwater sources. From the system design, individuals with limited literacy skills, advanced age, or non-expert users can utilize it with ease. The reliability of the LoRa protocol in transmitting data packets is thoroughly investigated to ensure effective communication. The system features a user-friendly interface for straightforward data input and facilitates broader access to information by employing various remote wireless sensing methods.

Enhanced Indoor Positioning Using RSSI and Time-Distributed Auto Encoder-Gated Recurrent Unit Model.

This study presents a novel approach to indoor positioning leveraging radio frequency identification (RFID) technology based on received signal strength indication (RSSI). The proposed methodology integrates Gaussian Kalman filtering for effective signal preprocessing and a time-distributed auto encoder-gated recurrent unit (TAE-GRU) model for precise location prediction. Addressing the prevalent challenges of low accuracy and extended localization times in current systems, the proposed method significantly enhances the preprocessing of RSSI data and effectively captures the temporal relationships inherent in the data. Experimental validation demonstrates that the proposed approach achieves a 75.9% improvement in localization accuracy over simple neural network methods and markedly enhances the speed of localization, thereby proving its practical applicability in real-world indoor localization scenarios.

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.

Tag-Array-Based UHF Passive RFID Tag Attitude Identification of Tracking Methods.

Attitude information is as important as position information in describing and localizing objects. Based on this, this paper proposes a method for object attitude sensing utilizing ultra-high frequency passive RFID technology. This method adopts a double tag array strategy, which effectively enhances the spatial freedom and eliminates phase ambiguity by leveraging the phase difference information between the two tags. Additionally, we delve into the issue of the phase shift caused by coupling interference between the two tags. To effectively compensate for this coupling effect, a series of experiments were conducted to thoroughly examine the specific impact of coupling effects between tags, and based on these findings, a coupling model between tags was established. This model was then integrated into the original phase model to correct for the effects of phase shift, significantly improving the sensing accuracy. Furthermore, we considered the influence of the object rotation angle on phase changes to construct an accurate object attitude recognition and tracking model. To reduce random errors during phase measurement, we employed a polynomial regression method to fit the measured tag phase information, further enhancing the precision of the sensing model. Compared to traditional positioning modes, the dual-tag array strategy essentially increases the number of virtual antennas available for positioning, providing the system with more refined directional discrimination capabilities. The experimental results demonstrated that incorporating the effects of inter-tag coupling interference and rotation angle into the phase model significantly improved the recognition accuracy for both object localization and attitude angle determination. Specifically, the average error of object positioning was reduced to 12.3 cm, while the average error of attitude angle recognition was reduced to 8.28°, making the method suitable for various practical application scenarios requiring attitude recognition.

Efficiency Improvement for Chipless RFID Tag Design Using Frequency Placement and Taguchi-Based Initialized PSO.

Frequency encoding chipless Radio Frequency Identification (RFID) tags have been frequently using the radar cross section (RCS) parameter to determine the resonant frequencies corresponding to the encoded information. Recent advancements in chipless RFID design have focused on the generation of multiple frequencies without considering the frequency position and signal amplitude. This article proposes a novel method for chipless RFID tag design, in which the RCS response can be located at an exact position, corresponding to the desired encoding signal spectrum. To achieve this, the empirical Taguchi method (TM), in combination with particle swarm optimization (PSO), is used to automatically search for optimal design parameters for chipless RFID tags with a fast response time, to comply with the frequency encoding requirements in the presence of the mutual coupling effect. The proposed design method is validated using I-slotted chipless tag structures that are fabricated and measured with different sets of resonant frequencies.

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.

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.

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.