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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. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) is a contemporary technology that enables the identification of objects and facilitates the transmission of additional information, making it possible to achieve real-time object tracking in a mobile object network and to report information on the object's current state at each step. RFID devices continuously generate large amounts of data, and collecting, filtering, and consolidating these data are therefore crucial tasks, which characterize RFID data management by a set of challenges. However, one of the greatest challenges in this field is managing large volumes of data in complex applications, where real-time operation is vital, given that the volume and speed of RFID data often exceed the capacity of the existing technological infrastructure. The aim of this study is to propose an RFID middleware that manages both the RFID hardware network and the large amounts of data that are captured, in order to process and transmit the collected data under the right conditions for ultimate use by an information system. This new RFID middleware architecture, named BTMiddleware combines complex event processing (CEP) with a MongoDB database to offer large-volume data streaming, processing, and storage in real time, as well as better interoperability thanks to the use of the JavaScript object notation (JSON) format for data presentation. [ABSTRACT FROM AUTHOR]

Abstract In present times, Radio‐Frequency Identification (RFID) systems have seen a significant rise in their usage. There has been an increasing interest in developing even lighter RFID protocols suitable for resource‐constrained environments. Ensuring security and privacy remain critical challenges in RFID‐based systems. Recently proposed lightweight authentication schemes, namely LRSAS+ and LRARP+, are ideally suited for constrained devices. However, this article investigates these schemes and reveals certain vulnerabilities: LRSAS+ is susceptible to tag impersonation, desynchronization, and traceability attacks, while LRARP+ can fall prey to traceability and secret disclosure attacks. An enhanced version of these authentication systems is proposed that tackles their inherent weaknesses by leveraging the χper function. To verify the security of the proposed scheme, a formal analysis is conducted using Gong–Needham–Yahalom logic (GNY logic) and an automated security protocol verification tool, ProVerif. The improved scheme's effectiveness is also compared with multiple contemporary lightweight systems. The results indicate that the enhanced scheme not only meets the security requirements for lightweight authentication schemes but also achieves this with minimal computational overhead.

In present times, Radio‐Frequency Identification (RFID) systems have seen a significant rise in their usage. There has been an increasing interest in developing even lighter RFID protocols suitable for resource‐constrained environments. Ensuring security and privacy remain critical challenges in RFID‐based systems. Recently proposed lightweight authentication schemes, namely LRSAS+ and LRARP+, are ideally suited for constrained devices. However, this article investigates these schemes and reveals certain vulnerabilities: LRSAS+ is susceptible to tag impersonation, desynchronization, and traceability attacks, while LRARP+ can fall prey to traceability and secret disclosure attacks. An enhanced version of these authentication systems is proposed that tackles their inherent weaknesses by leveraging the χper$\chi per$ function. To verify the security of the proposed scheme, a formal analysis is conducted using Gong–Needham–Yahalom logic (GNY logic) and an automated security protocol verification tool, ProVerif. The improved scheme's effectiveness is also compared with multiple contemporary lightweight systems. The results indicate that the enhanced scheme not only meets the security requirements for lightweight authentication schemes but also achieves this with minimal computational overhead. [ABSTRACT FROM AUTHOR]

RFID technology, as an important intelligent perception technology, provides a more efficient, convenient, and intelligent way for library management and services. However, the security issues of RFID (Radio Frequency Identification) systems have gradually emerged, such as tampering with RFID tags and system cracking. In order to address the security issues of RFID technology in smart libraries, a RFID security algorithm based on intelligent perception systems was studied. This algorithm utilized the location information, physical properties, and communication features of RFID tags to achieve location privacy protection, and improved the security of the algorithm by combining dynamic and static keys. The simulation results showed that the algorithm had a high recognition rate (Max: 94%) and security (Max: 97.9%), which can effectively achieve RFID system identification of tag identity, effectively prevent tag attacks and cracking, and improve system reliability. [ABSTRACT FROM AUTHOR]

Several decades ago, the medicine supply chain (MSC) transferred the medicines from the manufacturer to the end‐consumer and kept all records in a manual register. The manual intermediary management of MSC and medicine data often leads to issues like unauthorized third parties participating in the process and illegally tempering medicine data. As a result of this medicine temperament, end users get counterfeit medicine that poses severe consequences for patients' health. Over time, manual data management and intermediaries transform into digital platforms that track, manage, and exchange data in real‐time. Real‐time data exchange opens attackers up to target MSCs, access medicine data illegally, and modify medicine conditions, locations, and specifications. With the objective of this, the proposed survey identifies security and privacy issues and discusses security solutions. This security solution involves various data security and privacy frameworks such as micro‐segmentation, zero trust model, and many other software‐based security solutions. Moreover, The proposed survey explores radio frequency identification for medicine tracking in which each intermediary transforms the medicine location over the internet. In contrast, the Internet of Things is used to exchange medicine temperature conditions in real‐time. Furthermore, cybersecurity‐based solutions help protect against malicious threats, and blockchain keeps data private and temper‐proof. Artificial intelligence provides machine learning and deep learning models for analyzing large amounts of data to generate insights from the MSC data. Therefore, this survey addresses the various security and privacy issues and provides solutions that help researchers carry out work in this domain. [ABSTRACT FROM AUTHOR]

When the radio frequency identification (RFID) system inventories multiple tags, the recognition rate will be seriously affected due to collisions. Based on the existing dynamic frame slotted Aloha (DFSA) algorithm, a sub-frame observation and cyclic redundancy check (CRC) grouping combined dynamic framed slotted Aloha (SUBF-CGDFSA) algorithm is proposed. The algorithm combines the precise estimation method of the quantity of large-scale tags, the large-scale tags grouping mechanism based on CRC pseudo-random characteristics, and the Aloha anti-collision optimization mechanism based on sub-frame observation. By grouping tags and sequentially identifying them within subframes, it accurately estimates the number of remaining tags and optimizes frame length accordingly to improve efficiency in large-scale RFID systems. Simulation outcomes demonstrate that this proposed algorithm can effectively break through the system throughput bottleneck of 36.8%, which is up to 30% higher than the existing DFSA standard scheme, and has more significant advantages, which is suitable for application in large-scale RFID tags scenarios. [ABSTRACT FROM AUTHOR]

Accurate positioning is crucial in fields such as indoor positioning, autonomous driving, and robot navigation. However, traditional base station positioning algorithms are often affected by factors such as sensor errors, environmental noise, and uncertainty, resulting in certain errors in the positioning results. The article constructed a probability graph model using Radio Frequency Identification (RFID) by using position estimation results as variables. In this model, each position estimation result was represented as a node, and the dependency relationship between positions was represented as an edge. This article observed sensor data and uses Bayesian inference methods to update the probability distribution of each node. The experimental results showed that compared to traditional base station positioning algorithms, the probability graph optimization model based on radio frequency identification can significantly improve the accuracy and reliability of positioning. The highest values for both reached 0.989 and 0.95, respectively. This model has significant advantages in positioning tasks and provides an effective solution for practical applications. [ABSTRACT FROM AUTHOR]

In this paper, a proposal is made for a cryptographic algorithm designed for passive ultra-high-frequency (UHF) radio frequency identification systems. The algorithm relies on the advanced encryption standard (AES) as its fundamental encryption technique, augmented by two supplementary steps: the initial step involves generating a random key and the second is the randomization of data, this introduces an extra level of security to encryption process against attacks. The developed architecture has been optimized to minimize hardware resource consumption with faster execution speed. The algorithm has been simulated, synthesized and implemented in an xtreme digital signal processing (DSP) starter kit equipped with xilinx’s spartan-3A DSP 1800A edition and it serves the purpose of encrypting and decrypting user data on a radio frequency identification (RFID) passive tag. The main objective is to make it difficult to break the algorithm because of its multiple steps. The experimental results showed that the speed, functionality and cost of encryption and decryption make this a perfectly practical solution, providing a satisfactory level of security for today’s communications systems, or other electronic data transfer processes where security is required. [ABSTRACT FROM AUTHOR]

Kidnapping has the power to generate insecurity, social tension, psychological trauma, premature death, and many other problems in society. Therefore, any solution to the challenges caused by kidnapping in Nigeria is worth implementing. This study was conducted to determine the perspectives of the citizens in the states with a high incidence of kidnapping and their willingness to adopt implant radio frequency identification (iRFID) as a security measure against the ravaging menace. Purposive sampling technique, Taro Yamane's method at 92% confidence level and error margin ±8% were employed. A Google Form questionnaire was distributed to the residents in the concerned states, and the first 150 responses were countenanced and analyzed. Findings show that the middle-aged range (18-50 years) is the main target of the kidnappers, representing 94.7% of the respondents. Only 54.7% of the respondents know iRFID chips, and 56.7% are willing to be iRFID-chipped when deployed. Findings further revealed that the unwilling respondents hold an erroneous perspective of iRFID based on privacy, health, culture, and religion, and it is hoped that orientation programs would remedy such a perspective. The study concludes that the citizens are willing to be iRFIDchipped against the kidnapping menace despite privacy, health, cultural, and religious concerns. It is recommended that government should facilitate the deployment of iRFID. [ABSTRACT FROM AUTHOR]

Printed conductive polymer composites allow for the bespoke manufacture of products with complicated geometries, which is critical for rapid prototyping and adaptability of flexible electrical devices. However, it is still challenging to prepare environmentally friendly and sustainable conductive polymer composites with aqueous solvent systems which accomplish excellent printing and electromechanical properties at the same time. In this work, the effect of composite components on performance was explored, and orthogonal tests were utilized to discover the precise formulation of new green aqueous conductive polymer composites with superior performance. The printing accuracy of the conductive polymer composites was enhanced (printed circuit burrs less than 20 μm) and the dependability of the printed circuits as well as the failure mechanism during electrochemical migration (ECM) were thoroughly investigated. As a proof of concept, ultrahigh frequency (UHF) flexible linearly polarized antennae with read range forward surpassing 10 m was designed and printed. [ABSTRACT FROM AUTHOR]

Abnormal crowd detection and estimation are critical in video surveillance for ensuring public safety and preventing stampedes. Owing to occlusions and blind spots, traditional video surveillance methods cannot detect, estimate, or locate people in dense moving crowds with acceptable accuracy, posing a major challenge. Therefore, this study aims to provide an in-depth analysis of the most recent advancements in recognizing abnormal behaviors in large crowds. We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. Furthermore, this study presents the most recent findings on mobile crowdsensing based on edge computing, urban dynamics, optical flow, and machine learning techniques. Finally, we critically analyze the major challenges, shedding light on opportunities and directions for future work.

A miniaturized ultra-high frequency (UHF) radio frequency identification (RFID) tag antenna was designed.The antenna was composed of two square spiral resonators shorted inside and outside.By adjusting the edge length of the outer ring spiral resonator and the spacing between the inner and outer ring spiral resonators, the resonant frequency of the proposed tag antenna could be effectively tuned.The simulation results show that the proposed tag antenna has good impedance matching and the frequency band range covers the whole UHF band (840～960 MHz).It has a dimension of 7.60 mm×7.60 mm×0.05 mm, which is 96% smaller than the traditional spiral resonator (SR) antenna.The measure result shows that the proposed tag antenna achieves the maximum reading distance at 910 MHz in 4 W effective isotropic radiated power.The proposed UHF RFID tag antenna has some advantages of small size, wide frequency band, low cost and easy batch fabrication, and is suitable for applications with small size requirements.

The wireless use of radio frequency waves for data acquisition and transfer is known as Radio Frequency Identification (RFID). RFID-based systems have been applied in various fields, including building construction and maintenance. This study aims to evaluate the RFID tools for realizing the sustainability of construction projects. The literature was reviewed to obtain secondary data, complemented by a quantitative method involving the administration of a questionnaire to 107 experts in Nigeria using a random sampling method. It was followed by data analysis using the Exploratory Factor Analysis (EFA) approach. Finally, the structural equation modeling-artificial neural network model was applied to prioritize the major constructs. The EFA results demonstrated that RFID deployment areas may be divided into two main categories: hardware and system. The results affirmed the effectiveness of the system tools for RFID implementation in the building industry. Additionally, the hybrid model revealed that system and hardware predictors rank first and second in the RFID implementation areas. The outcomes of this study are important to understanding tools and methodologies related to the fuzziness of RFID for prospective workforces. Furthermore, it is envisaged that the identified RFID tools would enhance the sustainability of building projects. This study lays the foundation for the enhancement of decision-making in building projects. Although these studies have been confined to Nigeria, the findings apply to other developing countries, especially those with similar construction processes and operations.

Objective: Restoration of many populations of anadromous American Shad Alosa sapidissima and river herring (Alewife A. pseudoharengus and Blueback Herring A. aestivalis) has been hampered by the presence of barriers to their spawning migrations and insufficient monitoring of run size. Here, we describe results of a 10‐year (2012–2021) study of American Shad and river herring passage at the Island Farm Weir (IFW), the downstream‐most migration barrier on the Raritan River, New Jersey, United States. Methods: We used passive integrated transponder tags applied to fish that were captured and released downstream of the IFW to estimate passage rates and migration delays associated with upstream movements through an antenna array on a vertical slot fishway within the weir. By combining estimated passage rates with video monitoring of the total numbers of American Shad and river herring transiting the fishway, we estimated the annual run size below the weir. Result: Results suggest that the fishway on the IFW is moderately effective for American Shad (passage rate = 41%; 95% credible interval [CI] = 21–61%) but ineffective for the smaller‐bodied river herring (passage rate = 0.5%, 95% CI = 0–2%; fallback‐adjusted passage rate = 1.1%, 95% CI = 0.0–4.5%). The IFW may have also delayed the spawning migrations of those fish that did pass, with total passage times ranging from 0.4 to 20.9 days (mean ± standard deviation = 8.2 ± 5.3 days) for American Shad and 15.0 days for the one river herring that passed within the same year that it was tagged. Run size estimates during the study period ranged from 103 to 2624 individuals for American Shad and from 1486 to 53,334 for river herring. Conclusion: Restoration of these species in the Raritan River will likely require removal of the IFW or replacement of its current fish passage device with one that increases the passage rates of alosines. Impact statementUsing a combination of electronic tags and video monitoring, we found that a fish passage structure on the Raritan River, New Jersey, works moderately well for the large‐bodied American Shad but passes only a small fraction of the smaller‐bodied river herring. [ABSTRACT FROM AUTHOR]

Investigator disturbance while monitoring seabirds can result in lower survival rates and breeding success, leaving lasting negative impacts on the population and biasing observations. For example, monitoring rhinoceros auklets (Cerorhinca monocerata) and other burrowing alcids can reduce breeding success or even survival through handling stress and damage to nesting habitat. For this reason, researchers must seek to decrease colony disturbance. Automated radio-frequency identification (RFID) via passive integrated transponder (PIT) tags is an inexpensive and reliable way to identify individual presence and record attendance behaviour, avoiding the need to recapture seabirds or visit the colony frequently. PIT tags either can be implanted subcutaneously or attached externally to leg bands, but it is unclear which method causes lower disturbance. To examine the impact of PIT tagging on rhinoceros auklets nesting in artificial burrows on Middleton Island, Alaska, we monitored burrow entrances with automated recording RFID readers to collect presence and nest attendance data. PIT-tagged (either band attachment or subcutaneous implant) and control birds had similar breeding success and chick growth rates. Breeding success was similar between nests with one or two parents marked. Birds tagged externally were detected less often than birds marked with a subcutaneous implant. We conclude that PIT tagging of rhinoceros auklets is a relatively non-invasive method for seabird monitoring, and that subcutaneous implants do not cause more disturbance than external attachment. [ABSTRACT FROM AUTHOR]

Copyright of Information Library Magazine 'INFOLIB' is the property of National Library of Uzbekistan named after Alisher Navoi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the emergence of the fourth industrial revolution, the use of intelligent technologies in supply chains is becoming increasingly common. The aim of this research is to propose an optimal design for an intelligent supply chain of multiple perishable products under a vendor-managed inventory management policy aided by IoT-related technologies to address the challenges associated with traditional supply chains. Various levels of the intelligent supply chain employ technologies such as Wireless Sensor Networks (WSNs), Radio Frequency Identification (RFID), and Blockchain. In this paper, we develop a bi-objective nonlinear integer mathematical programming model for designing a four-level supply chain consisting of suppliers, manufacturers, retailers, and customers. The model determines the optimal network nodes, production level, product distribution and sales, and optimal choice of technology for each level. The objective functions are total cost and delivery times. The GAMS 24.2.1 optimization software is employed to solve the mathematical model in small dimensions. Considering the NP-Hard nature of the problem, the Grey Wolf Optimizer (GWO) algorithm is employed, and its performance is compared with the Multi-Objective Whale Optimization Algorithm (MOWOA) and NSGA-III. The results indicate that the adoption of these technologies in the supply chain can reduce delivery times and total supply chain costs. [ABSTRACT FROM AUTHOR]

ABSTRACT: This study aimed to estimate genetic parameters for feeding behavior (FB) traits and to assess their genetic relationship with performance traits in group-housed broilers. In total, 99,472,151 visits were recorded for 95,711 birds between 2017 and 2022 using electronic feeders. The visits were first clustered into 2,667,617 daily observations for ten FB traits: daily feed intake (DFI), daily number of visits (NVIS), time spent at the feeders (TSF), number of visited feeders (NVF), visiting activity interval (VAI), feeding rate (FR), daily number of meals (NMEAL), average intake per meal (INTMEAL), number of visits per meal (VISMEAL) and interval between meals (MEALIVL). All FB traits were then considered as the average per bird across the feeding test period. Three growth traits (body weight at the start – SBW and at the end of the feeding test – FBW, and weight gain over the test period – BWG), and 2 feed efficiency (FE) traits (Feed Conversion Rate - FCR and Residual Feed Intake - RFI) were also recorded. The (co)variance components were estimated using multitrait animal mixed models. For growth and FE, the heritability (h2) estimates were moderate, ranging from 0.20 ± 0.01 (BWG) to 0.32 ± 0.02 (RFI). Overall, the h2 estimates for FB traits were higher than for productive traits, ranging from 0.31 ± 0.01 (DFI) to 0.56 ± 0.02 (TSF). DFI presented high genetic correlations (0.53–0.86) with all performance traits. Conversely, the remaining FB traits presented null to moderate genetic correlations with these traits, ranging from –0.38 to 0.42 for growth traits and between –0.14 and 0.25 for FE traits. Genetic selection for favorable feeding behavior is expected to exhibit a fast genetic response. The results suggest that it is possible to consider different feeding strategies without compromising the genetic progress of FE. Conversely, breeding strategies prioritizing a higher bird activity might result in lighter broiler lines in the long term, given the negative genetic correlations between visit-related traits (NV, NVF, and NMEAL) and growth traits (SBW and FBW).

Abstract With the rapid development of the Internet of Things and intelligent technology, the application of Radio Frequency Identification (RFID) technology in training room management is becoming increasingly widespread. An efficient and accurate RFID system can significantly improve the management efficiency and resource utilization of the training room, thereby improving teaching quality and reducing management costs. Although RFID technology has many advantages, there are still some problems in practical applications, such as label collision and recognition of unknown labels. These issues not only affect the performance of the system but may also cause interference with actual teaching and management. This study proposes a grouping-based bit arbitration query tree algorithm and anti-collision technology to solve label collisions and reduce label recognition time in the technology. A new unknown label recognition algorithm is also proposed to improve the recognition efficiency and accuracy of identifying new unknown labels. Related experiments have shown that the recognition accuracy of the algorithm designed this time is 95.86%. Compared with other algorithms, the number of idle time slots is the smallest. When the number of queries is 1000, the algorithm has 1842 queries, and the communication complexity is the best. When the number of unknown tags is 10,000, the actual accuracy rate is 95.642%. Compared with traditional recognition algorithms, the new unknown label recognition algorithm has a smaller frame length in the same label proportion and good recognition performance. On a theoretical level, the research content on RFID technology helps to improve and develop the basic theories of the Internet of Things and intelligent recognition technology and provides solutions and application technologies for equipment management and IoT applications in training rooms. On a practical level, the research results can provide specific guidance for the management of training rooms, help solve equipment management and safety maintenance problems in practical applications, and improve the management efficiency of training rooms.

Owing to the rapid development of the ambient Internet of Things (IoT) industry, Backscatter Communication Systems (BCS) require higher receiver sensitivity for large-scale IoT scenarios than traditional Radio Frequency Identification (RFID) systems. This paper proposes a method of using Multiple-Input Multiple-Output (MIMO) technology to compensate for reflected signals in the 920 MHz backscatter communication systems. The researcher first created a MATLAB model to verify the theoretical feasibility and then built a One-Transmitter Two-Receiver (1T2R) BCS transceiver system compatible with the EPC global protocol for practical verification on LabVIEW. The ITIR and 1T2R tests were conducted using the National Instrument (NI) USRP-2952R device, the directional antennas, and the standard RF electronic tags. Through the process of superimposing and utilizing the phase shift between the two reflected carriers, it has been confirmed that the overall signal strength can be enhanced from 2.2 mV to 4.13 mV and 4.37 mV (nearly reaching 4.70 mV by using two Rx antennas in ideal conditions). After calculation, this advancement increases signal strength from −40.14 dBm (when using a single Rx antenna) to −34.18 dBm (when using two Rx antennas). The improvement in signal strength can provide a gain of 5.96 dB to the backscatter communication systems. Experimental results demonstrate that utilizing MIMO technology to the backscatter communication systems can effectively enhance the sensitivity of the receiver at 920 MHz.