Identification Tags Research Articles

An innovative medical waste management system in a smart city using XAI and vehicle routing optimization

Background The management of medical waste is a complex task that necessitates effective strategies to mitigate health risks, comply with regulations, and minimize environmental impact. In this study, a novel approach based on collaboration and technological advancements is proposed. Methods By utilizing colored bags with identification tags, smart containers with sensors, object recognition sensors, air and soil control sensors, vehicles with Global Positioning System (GPS) and temperature humidity sensors, and outsourced waste treatment, the system optimizes waste sorting, storage, and treatment operations. Additionally, the incorporation of explainable artificial intelligence (XAI) technology, leveraging scikit-learn, xgboost, catboost, lightgbm, and skorch, provides real-time insights and data analytics, facilitating informed decision-making and process optimization. Results The integration of these cutting-edge technologies forms the foundation of an efficient and intelligent medical waste management system. Furthermore, the article highlights the use of genetic algorithms (GA) to solve vehicle routing models, optimizing waste collection routes and minimizing transportation time to treatment centers. Conclusions Overall, the combination of advanced technologies, optimization algorithms, and XAI contributes to improved waste management practices, ultimately benefiting both public health and the environment.

An Efficient Early-breaking-estimation and Tree-splitting Missing RFID Tag Identification Protocol

Retailers grapple with inventory losses primarily due to missing items, prompting the need for efficient missing tag identification methods in large-scale RFID systems. Among them, few works considered the effect of unexpected unknown tags on the missing tag identification process. With the presence of unknown tags, some missing tags may be falsely identified as present. Thus, the system’s reliability is hardly guaranteed. To resolve these challenges, we propose an efficient early-breaking-estimation and tree-splitting-based missing tag identification (ETMTI) protocol for large-scale RFID systems. ETMTI employs innovative early-breaking-estimation and deactivation methods to swiftly handle unknown tags. Subsequently, a tree-splitting-based missing tag identification method is proposed, employing a B-ary splitting tree, to rapidly identify missing tags. Additionally, a bit-tracking response strategy is implemented to reduce processing time. Theoretical analysis is conducted to determine optimal parameters for ETMTI. Simulation results illustrate that our proposed ETMTI protocol significantly outperforms benchmark methods, offering a shorter processing time and a lower false negative rate.

Automated Image Quality and Protocol Adherence Assessment of Examinations in Teledermatology: First Results.

Introduction: Image quality and acquisition protocol adherence assessment is a neglected area in teledermatology. We examine if it is feasible to use deep learning methods to automate the assessment of the adherence of examinations to image acquisition protocols. In this study, we focused on the quality criteria of two image acquisition protocols: (1) approximation image and (2) panoramic image, as these are present in all teledermatology examination protocols currently used by the Santa Catarina State Integrated Telemedicine and Telehealth System (STT/SC). Methods: We use a data set of 36,102 teledermatological examinations performed at the STT/SC during 2021. As our validation process, we adopted standard machine learning metrics and an inter-rater agreement (IRA) study with 11 dermatologists. For the approximation image protocol, we used the Mask-Region based Convolutional Neural Network (RCNN) Object Detection Deep Learning (DL) architecture to identify the presence of a lesion identification tag and a ruler used to provide a frame reference of the lesion. For the panoramic image protocol, we used DensePose, a pose estimation DL, architecture to assess the presence of a whole patient body and its orientation. A combination of the two approaches was additionally validated through an IRA study between specialists. Results: Mask-RCNN achieved a score of 96% mean average precision (mAP), while DensePose presented 75% mAP. IRA achieved a level of agreement of 96.68% with the Krippendorff alpha score. Conclusions: Our results show the feasibility of using deep learning to automate the image quality and protocol adherence assessment in teledermatology, before the specialist's manual analysis of the examination.

265 Manger Space Restriction Does not Negatively Impact Growth Efficiency of Feedlot Heifers Program fed a Concentrate-Based Diet to Gain 1.36 kg Daily

Abstract The objective of this research was to determine the influence manger space restriction had on program fed feedlot heifers during the growing phase. Charolais × Angus heifers [initial body weight (BW) = 329 ± 22.1 kg] were used in a 109-d backgrounding phase study. Heifers were received from a ranch in western South Dakota approximately 60 days before study initiation. Initial processing (53 days before study initiation) included individual BW measurement, application of a unique identification tag, vaccination against viral respiratory pathogens (Bovi-Shield Gold 5, Zoetis, Parsippany, NJ) and clostridial species (Ultrabac/Somubac 7, Zoetis), and administration of doramectin pour-on (Dectomax, Zoetis) for control of internal and external parasites. All heifers were administered 36 mg of zeranol (Ralgro, Merck Animal Health, Madison, NJ) at study initiation. Upon study initiation, heifers were assigned to 1 of 10 pens (n = 5 pens/treatment with 10 heifers/pen) in a randomized complete block design (blocked by location). Each pen was randomly assigned to 1 of 2 treatments: 20.3 cm (8IN) or 40.6 cm (16IN) of linear bunk space/heifer. Heifers were individually weighed on days 1, 14, 35, 63, 84 and 109. Heifers were programmed to gain 1.36 kg daily based on predictive equations for a medium frame steer calf set forth by the California Net Energy System. To calculate predictive values, a final BW of 575 kg was assumed to be the mature BW of the heifers and tabular net energy values of 2.05 NEm and 1.36 NEg from d 1 to 22, 2.00 NEm and 1.35 NEg from d 23 to 82, and 1.97 NEm and 1.32 NEg from d 83 to 109 were used, because of ingredient inventory changes. Data were analyzed using the GLIMMIX procedure of SAS 9.4 with manger space allocation as the fixed effect and block as the random effect. No differences (P > 0.35) were observed between 8IN or 16IN heifers for initial BW, final BW, average daily gain, dry matter intake, feed efficiency, variation in daily BW gain (within pen standard deviation) or applied energetic measures. No differences (P > 0.50) were observed between treatments for morbidity. Although not statistically analyzed, 8IN heifers appeared to have looser stools during the first two weeks compared with the 16IN heifers. These data suggest restricting manger space allocation from 40.6 cm to 20.3 cm did not negatively influence gain efficiency or the efficiency of dietary net energy utilization in heifers programmed fed a concentrate-based diet to gain 1.36 kg daily. The use of tabular net energy values and required net energy of maintenance and retained energy equations are an effective means to program cattle to a desired daily rate of gain during the growing phase.

Dual-Mode Nanoprobes Based on Lanthanide Doped Fluoride Nanoparticles Functionalized by Aryl Diazonium Salts for Fluorescence and SERS Bioimaging.

The design of dual-mode fluorescence and Raman tags stimulates a growing interest in biomedical imaging and sensing applications as they offer the possibility to synergistically combine the versatility and velocity of fluorescence imaging with the specificity of Raman spectroscopy. Although lanthanide-doped fluoride nanoparticles (NPs) are among the most studied fluorescent nanoprobes, their use for the development of bimodal fluorescent-Raman probes has never been reported yet, to the best of the authors knowledge, probably due to the difficulty to functionalize them with Raman reporter groups. This gap is filled herein by proposing a fast and straightforward approach based on aryl diazonium salt chemistry to functionalize Eu3+ or Tb3+ doped CaF2 and LaF3 NPs by Raman scatters. The resulting surface-enhanced Raman spectroscopy (SERS)-encoded lanthanide-doped fluoride NPs retain their fluorescence labeling capacity and display efficient SERS activity for cell bioimaging. The potential of this new generation of bimodal nanoprobes is assessed through cell viability assays and intracellular fluorescence and Raman imaging, opening up unprecedented opportunities for biomedical applications.

Overcoming Downscaling Limitations in Organic Semiconductors: Strategies and Progress.

Organic semiconductors have great potential to revolutionize electronics by enabling flexible and eco-friendly manufacturing of electronic devices on plastic film substrates. Recent research and development led to the creation of printed displays, radio-frequency identification tags, smart labels, and sensors based on organic electronics. Over the last 3 decades, significant progress has been made in realizing electronic devices with unprecedented features, such as wearable sensors, disposable electronics, and foldable displays, through the exploitation of desirable characteristics in organic electronics. Neverthless, the down-scalability of organic electronic devices remains a crucial consideration. To address this, efforts are extensively explored. It is of utmost importance to further develop these alternative patterning methods to overcome the downscaling challenge. This review comprehensively discusses the efforts and strategies aimed at overcoming the limitations of downscaling in organic semiconductors, with a particular focus on four main areas: 1) lithography-compatible organic semiconductors, 2) fine patterning of printing methods, 3) organic material deposition on pre-fabricated devices, and 4) vertical-channeled organic electronics. By discussing these areas, the full potential of organic semiconductors can be unlocked, and the field of flexible and sustainable electronics can be advanced.

Giving the Green Light to Photochemical Uncaging of Large Biomolecules in High Vacuum.

The isolation of biomolecules in a high vacuum enables experiments on fragile species in the absence of a perturbing environment. Since many molecular properties are influenced by local electric fields, here we seek to gain control over the number of charges on a biopolymer by photochemical uncaging. We present the design, modeling, and synthesis of photoactive molecular tags, their labeling to peptides and proteins as well as their photochemical validation in solution and in the gas phase. The tailored tags can be selectively cleaved off at a well-defined time and without the need for any external charge-transferring agents. The energy of a single or two green photons can already trigger the process, and it is soft enough to ensure the integrity of the released biomolecular cargo. We exploit differences in the cleavage pathways in solution and in vacuum and observe a surprising robustness in upscaling the approach from a model system to genuine proteins. The interaction wavelength of 532 nm is compatible with various biomolecular entities, such as oligonucleotides or oligosaccharides.

Ultrasensitive fluorescence sensor for Hg2+ in food based on three-dimensional upconversion nanoclusters and aptamer-modulated thymine-Hg2+-thymine strategy.

Mercury (Hg2+) is a potentially toxic heavy metal ion found to be drastically deleterious to humans. Herein, an ultrasensitive fluorescence sensor was developed using three-dimensional upconversion nanoclusters (EBSUCNPs) and aptamer-modulated thymine-Hg2+-thymine strategy. The EBSUCNPs were used as the energy donors, the PDANPs served as the acceptors, and the aptamer was applied as an identification tag for Hg2+. Due to the energy transfer effect, the fluorescence of EBSUCNPs can be effectively quenched by Polydopamine nanoparticles (PDANPs). In the existence of Hg2+, T (thymine)-rich aptamers between EBSUCNPs and PDANPs were hybridized with Hg2+ to yield thymine-Hg2+-thymine and folded back to hairpin structure, causing PDANPs to detach from the EBSUCNPS and the recovery of fluorescence. Under optimum conditions, the linear sensing range of Hg2+ was 0.5-20µg/L, and the detection limit was 0.28µg/L. Furthermore, it exhibited excellent selectivity and anti-interference, which made it an ideal method for identifying Hg2+ in spiked samples.

Multiple Resolution Bit Tracking for Continuous Reliable RFID Tag Identification

Multiple Resolution Bit Tracking for Continuous Reliable RFID Tag Identification

THE IMPACT OF AIRCRAFT CABIN DIGITALIZATION ON IMPROVING PASSENGER EXPERIENCE IN EGYPTAIR

This study aims to investigate the impact of aircraft cabin digitalization (smart electronically dimmable windows, intelligent seats, smart overhead bins, radio-frequency identification tags for luggage tracking, futuristic intelligent seats, and inflight virtual reality) on improving the inflight passenger experience in EgyptAir, as well as measuring passengers' interest in using digital cabins. Furthermore, exploring passengers’ intention to pay to use digital services, including futuristic intelligent seats, inflight virtual reality, and radio frequency identification tags for tracking luggage. To meet the research goals, a structured survey was designed and distributed among Egyptian frequent travelers in EgyptAir. A total of 311 complete surveys were collected and analyzed. Results indicated the high interest of Egyptian passengers in using the digital aircraft cabins in EgyptAir due to its significant impact on improving their inflight experience. Furthermore, analyses revealed the high intention of Egyptian passengers to pay to use inflight virtual reality and futuristic intelligent seats. However, they showed a moderate intention to pay to use radio frequency identification tags for tracking luggage.

Enabling people with intellectual and other disabilities to make verbal requests using cardboard chips with mini objects or pictures and a smartphone.

This study aimed to help six participants with intellectual disability combined with sensory and motor impairments to make verbal requests through the use of a technology system involving cardboard chips and a smartphone. The participants were divided into two groups of three based on whether they did or did not have visual skills. Each group was exposed to the intervention with the technology system according to a non-concurrent multiple baseline across participants design. During the 20 min intervention sessions, the participants were provided with a smartphone and nine cardboard chips each of which had a picture or object (i.e., a mini object replica or raised object contour) and several radio frequency identification tags attached to it. To make a request, the participants were to bring a cardboard chip in contact with the smartphone. This read the tags attached to the cardboard and verbalized the request related to that cardboard. During the baseline (without cardboard chips and smartphone), the participants' mean frequency of independent requests (all non-verbal requests) varied between zero and near 1.5 per session. During the intervention (with cardboard chips and smartphone), the participants' mean frequency of independent requests (all verbal requests) varied between over 4.5 and about 10 per session. The results suggest that the system might be useful to help participants like the ones included in this study to make verbal requests with simple responses.

A Hybrid Solar-RF Energy Harvesting System Based on an EM4325-Embedded RFID Tag

This paper presents the deployment of a hybrid energy harvesting system that combines a wireless energy harvesting (EH) system and a 6 V, 170 mA monocrystalline solar energy derived from the Sun’s rays. The hybrid energy harvesting (HEH) system comprises the rectifier, the solar cell panel, the charging circuit, and the EM4325 embedded RFID tag. This study aims to design an efficient EH system capable of increasing the read range of an active RFID tag. The proposed approach integrates a meandered line radio frequency identification (RFID) tag with an EM4325 IC chip as the receiver antenna. A halfwave doubler RF rectifier circuit is connected to the antenna using a 50 Ω SMA connector to convert the captured RF waves into usable electrical power. A solar energy charging module equipped with a Maximum Power Point Tracking (MPPT) system, a rechargeable lithium-ion battery, and a DC-DC converter is configured to manage and store the harvested energy efficiently. The UHF tag antenna operates at 919 MHz, achieving a peak gain of 3.54 dB. The proposed rectenna achieves a maximum measured harvested power conversion efficiency (PCE) of 55.14% for an input power (Pin) of 15 dBm at a distance of 5.10 cm, while the solar cell panel realizes 3.92 W of power. Experimental results demonstrate the hybrid harvester system’s effectiveness, achieving a PCE of 86.49% at an output voltage (VDC) of 5.35 V. The main advantage of this approach is the creation of a compact hybrid RF and solar EH system by combining the solar cell panel with the antenna, thus enabling multi-functionality.

The evolving story of catadromy in the European eel (Anguilla anguilla)

Abstract Anguillid eels were once considered to be the classic example of catadromy. However, alternative life cycles have been reported, including skipping the freshwater phase and habitat shifting between fresh, brackish, and saltwater throughout the growth phase. There is a lack of knowledge regarding these alternate life strategies, for example, the proportion of individuals in the population that adopt them compared to classic catadromy. We provide a description of these alternate life cycle strategies in temperate anguillids, their possible drivers, and the methods available to investigate them. These methods (lethal and non-lethal), include otolith microchemistry, fatty acid and stable isotope analyses, parasite identification, blood transcriptomics, and electronic tags. We argue that since the current management framework for the European eel and other temperate eels is based mainly on the freshwater component of the population, it ignores eels growing in saline waters. Many of the factors that are thought to be responsible for the precipitous decline of the eel population are more prevalent in freshwater systems. Therefore, the contribution of saline eels may be more important than currently estimated. The habitat-shifting ability of eels may be all the more crucial for the persistence and recovery of those species that are endangered.

Design and analysis of flexible embroidered UHF-RFID tag on facemask for IoT applications using characteristics mode analysis

This work presents an ultra-high frequency (UHF) radio frequency identification (RFID) tag embroidered on a face mask for Internet of Things (IoT) devices. The tag is designed and optimized to operate within the entire US RFID band of 902–928 MHz using characteristic mode analysis (CMA). A Mickey Mouse (MM) shaped radiation element is analyzed by testing three resonating modes at frequency of 900 MHz. Additionally, two dipoles are introduced to achieve the optimal conjugate match with a passive RFID chip (Alien Higgs H3), which exhibits an impedance of 27-200j at the desired frequency. A simulation of the voxel head model has also been carried out to verify the specific absorption rate (SAR), which provides SAR <1.43 W/kg. The proposed tag is embroidered on a cotton fabric facemask with a dielectric constant of 1.143 using conductive thread with a resistance of 28 O/ft. This tag features a good impedance match in US RFID band along with gain of 2.06 dB and a 37% reduction in size as compared to the previous version. Furthermore, it provides a read range of 3 m for an off-body scenario and 2.5 m for an on-body scenario. The proposed wearable facemask tag has potential applications for various real-life applications.

FuseBot: mechanical search of rigid and deformable objects via multi-modal perception

Mechanical search is a robotic problem where a robot needs to retrieve a target item that is partially or fully-occluded from its camera. State-of-the-art approaches for mechanical search either require an expensive search process to find the target item, or they require the item to be tagged with a radio frequency identification tag (e.g., RFID), making their approach beneficial only to tagged items in the environment. We present FuseBot, the first robotic system for RF-Visual mechanical search that enables efficient retrieval of both RF-tagged and untagged items in a pile. Rather than requiring all target items in a pile to be RF-tagged, FuseBot leverages the mere existence of an RF-tagged item in the pile to benefit both tagged and untagged items. Our design introduces two key innovations. The first is RF-Visual Mapping, a technique that identifies and locates RF-tagged items in a pile and uses this information to construct an RF-Visual occupancy distribution map. The second is RF-Visual Extraction, a policy formulated as an optimization problem that minimizes the number of actions required to extract the target object by accounting for the probabilistic occupancy distribution, the expected grasp quality, and the expected information gain from future actions. We built a real-time end-to-end prototype of our system on a UR5e robotic arm with in-hand vision and RF perception modules. We conducted over 200 real-world experimental trials to evaluate FuseBot and compare its performance to a state-of-the-art vision-based system named X-Ray (Danielczuk et al., in: 2020 IEEE/RSJ international conference on intelligent robots and systems (IROS), IEEE, 2020). Our experimental results demonstrate that FuseBot outperforms X-Ray’s efficiency by more than 40% in terms of the number of actions required for successful mechanical search. Furthermore, in comparison to X-Ray’s success rate of 84%, FuseBot achieves a success rate of 95% in retrieving untagged items, demonstrating for the first time that the benefits of RF perception extend beyond tagged objects in the mechanical search problem.

A comparison of conductive ink usage optimization techniques used in fabrication of epidermal UHF radio frequency identification tags for medical and sensing applications.

The aim of this work is to assess the performance of various inkjet printing techniques. These techniques are aimed at optimizing the volume of conductive ink used in the fabrication of inkjet printed Radio Frequency Identification tags. It is also possible that they can be used in fabricating other electronic and electromagnetic devices and structures. Three ink optimization approaches were examined viz. gridded (meshed) designs, conductive area trimming and selective ink deposition. The volume of conductive ink utilized in tag fabrication and the measured on-body (forearm) read range of the tag were used to develop a figure of merit which determined the best printing approach. Although the longest read range was obtained from the tag with 48% conductive area trimming (Trim 1), the best figure of merit, that is, the tag with the best balance between measured read range and utilized conductive ink, was obtained from the tag that had its surface area trimmed by 65% (Trim 2). It is however suggested that optimum use of conductive ink would be achieved with a combination of 65% surface area trimming and selective ink deposition technique.

Unknown Tag Identification Protocol Based on Collision Slot Resolution in Large-Scale and Battery-Less RFID System

Radio frequency identification (RFID) technology is widely used in warehouse management and supply chain management. In the actual application, unknown tags such as newly added or incorrectly placed products will be placed into a certain area of the warehouse. Existing identification protocols can identify such unknown tags by collecting tag IDs and comparing them with back-end server. Alternatively, the known tags can be filtered through the filter vector to prevent interference from unknown tags and improve identification efficiency. However, there is a lack of consideration of the collision impact on identification efficiency. In this paper, we introduce the bit tracking technology to accelerate the identification process and propose a Bit-Tracking Based Strategy for Unknown Tag Identification (BTUTI) protocol. We solve the problem by means of known tag deactivation and unknown tag identify. First, by adopting bit tracking technology, the reader can easily locate the positions of the collision bit. By hashing the tags of these collision slots, the collision slots can be turned into resolvable slots, thus improving the utilization rate of slots. Second, in the expected non-empty slot, the reader can send command to deactivate the known tag and skip empty slots and irresolvable collision slots. The experiment proves that BTUTI can increase the time efficiency compared to the state-of-the-art.

Drone Detection and Tracking Using RF Identification Signals.

The market for unmanned aerial systems (UASs) has grown considerably worldwide, but their ability to transmit sensitive information poses a threat to public safety. To counter these threats, authorities, and anti-drone organizations are ensuring that UASs comply with regulations, focusing on strategies to mitigate the risks associated with malicious drones. This study presents a technique for detecting drone models using identification (ID) tags in radio frequency (RF) signals, enabling the extraction of real-time telemetry data through the decoding of Drone ID packets. The system, implemented with a development board, facilitates efficient drone tracking. The results of a measurement campaign performance evaluation include maximum detection distances of 1.3 km for the Mavic Air, 1.5 km for the Mavic 3, and 3.7 km for the Mavic 2 Pro. The system accurately estimates a drone's 2D position, altitude, and speed in real time. Thanks to the decoding of telemetry packets, the system demonstrates promising accuracy, with worst-case distances between estimated and actual drone positions of 35 m for the Mavic 2 Pro, 17 m for the Mavic Air, and 15 m for the Mavic 3. In addition, there is a relative error of 14% for altitude measurements and 7% for speed measurements. The reaction times calculated to secure a vulnerable site within a 200 m radius are 1.83 min (Mavic Air), 1.03 min (Mavic 3), and 2.92 min (Mavic 2 Pro). This system is proving effective in addressing emerging concerns about drone-related threats, helping to improve public safety and security.

Coding of Chipless RFID Tag using Multiresonator

This research presents the design and simulation of chipless RFID tag based on retransmission. Chipless RFID tag design using inverted L-shaped multi-resonator is proposed in this research. The coding capacity of the tag is 10 bits and the design is simulated using FR4 substrate. Total of 2^(10 ) individual data can be encoded through the proposed design. Occupied frequency range of the design is from 2 GHz to 4 GHz. Chipless RFID tags have its wide applications due to its low cost and compact structure. The printed versions of this tags can be effectively employed in supply chain management for industries.

QR-PUF: Design and Implementation of a RFID-Based Secure Inpatient Management System Using XOR-Arbiter-PUF and QR-Code

In recent years, Physical Unclonable Functions (PUFs) have played a major role in providing low-cost physical security for IoT devices such as Radio Frequency Identification (RFID) tags. PUFs take advantage of the physical properties of the device to build unique security primitives that can be used by authentication mechanisms. Meanwhile, the security and convenience of QR codes for device authentication on mobile devices has been widely recognized. The point-to-point communication makes it less vulnerable to interception and analysis by adversaries. In this article, we propose a <i>new</i> RFID-based secure inpatient management system for identifying a legitimate patient. Our proposed system uses an XOR Arbiter PUF to generate a secret key-stream and then uses the key-stream to construct a secure QR code for secure identification. Also, since PUFs are vulnerable to machine learning attacks, we propose a modeling attack resilience obfuscation framework to enhance the security of the proposed protocol. Security analysis of the proposed scheme using ProVerif shows that the scheme is effective against a variety of imperative attacks on RFID devices. To show the applicability of the proposed scheme, we also provide a case study of an inpatient management system in hospitals.