Search

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]

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.

Vehicular Ad-hoc Networks (VANETs) indeed have significant potential to enhance transportation efficiency, accident prevention, and overall comfort. They enable communication between vehicles and road infrastructure, facilitating the exchange of entertainment and traffic information. This capability can lead to safer and more efficient transportation systems while improving the overall experience for drivers and passengers. The challenging and critical security requirements in VANETs, such as access management, authentication, and privacy protection, are essential for achieving the objectives of vehicle-to-infrastructure (V2I) and intervehicle (I2V) communications. These security measures ensure the integrity, confidentiality, and availability of communication channels, thereby enhancing transportation efficiency, accident prevention, and overall comfort within VANETs. In this study, we investigate the concerns of secure access control, authentication, and privacy protection in VANETs. In response to these challenges, we propose automobile authentication methods. This protocol is built on a toll-based certificate management system utilizing RFID tags and readers deployed on automobiles and toll booths. Additionally, we introduce a vehicular mobility management method and a VANET node attachment strategy that considers quality of service (QoS) requirements. This comprehensive approach addresses key security and operational aspects of VANETs.

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. [ABSTRACT FROM AUTHOR]

Information metasurfaces (IMSs) have been considered to be a revolutionary technology for improving the spectral efficiency of sixth‐generation (6G) wireless communications due to their superior ability to manipulate electromagnetic (EM) waves. However, there are still problems to be solved before the widespread application of IMSs. The first is to reduce power consumption, and the second is to achieve a long‐range remote control. In this paper, a long‐range and nearly passive radio frequency identification (RFID)‐controlled IMS is proposed. The proposed IMS comprises four RFID tags and 8 × 8 elements, each of which is integrated with a single‐pole‐double‐throw switch chip to achieve 1‐bit phase reconfigurability. With the remote control of the RFID system, the IMS can be programmed to switch between three functionalities, including beam splitting, beamforming, and EM‐wave absorption. Experiments are performed and the beam‐splitting functionality is demonstrated. The measurement results indicate that the wireless communication between the RFID reader and the IMS is robust within 21.7 m. Additionally, the power consumption of the IMS is as low as 0.576 mW, which can be negligible. The scheme presented in this paper paves the way for the large‐scale applications of IMSs in 6G wireless communications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of China University of Petroleum is the property of China University of Petroleum 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.)

This paper proposes the Lock-Position-Based RFID Adaptive Parallel Collision Tree (LAPCT) algorithm to address the issues of excessive time slots required in the identification process of collision tree algorithms for multiple tags and the high communication complexity between the reader and multiple tags. The LAPCT algorithm adopts a single-query multiple-response mechanism and dynamically divides the response sub-cycle numbers in the identification cycle based on an adaptive strategy. It uses Manchester encoding to lock collision positions and generate a common query prefix, effectively reducing the number of reader queries. This reduction in queries decreases the total number of required time slots and transmitted bits during the reader–tag communication process, thereby improving the efficiency of multiple tag recognition. Theoretical and simulation experiments demonstrate that compared to similar algorithms, the LAPCT algorithm achieves a maximum reduction of 37% in total time slots required, a maximum improvement of 30% in recognition efficiency, and a maximum reduction of 90% in communication complexity. Furthermore, with an increase in the number of tags, the performance advantages of the LAPCT algorithm become more pronounced, making it suitable for large-scale tag scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office 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.)

In order to address the problem of inability to parallelly identify multiple tags in the Improved Collision Tree（ICT） algorithm when there are multiple collision slots and collisions at multiple positions in large-scale tag scenarios,this paper developed a Parallel Identification Collision Tree（PICT） algorithm based on Walsh codes for RFID. The PICT algorithm combined Walsh synchronization orthogonal codes with the collision tree protocol. It used Walsh codes to spread the tags involved in multiple collisions in the ICT algorithm, and tags with unique Walsh codes communicate with the reader through different sub-channels, enabling parallel identification of multiple tags. Theoretical and experimental analyses demonstrated that the PICT algorithm requires fewer total system time slots compared to similar algorithms, and it achieves higher system identification efficiency, making it suitable for fast identification of largescale tags. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control 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.)

On holidays and weekends, we can notice a large rush at shopping centres in metro areas. This is exacerbated when there are substantial discounts and deals. By applying the notion of internet of thing (IoT) for concerning all things in the grocery store, an automated smart shopping system is created. Each product within such scheme had an economical radio frequency identification (RFID) tag positioned with it. Once an item has been added to a smart cart, the information about the merchandise is quickly read by the RFID reader on the cart. The outcome is, direct invoicing is done out from shopping cart, saving clients from having to wait in a long line at the checkout. The product's expiration date is also displayed and broken products can be determined by their weight. As a result, expired and damaged products will not be taken into account when calculating the cost. Furthermore, this system gains the addition of smart shelves incorporating RFID readers which may check stock and possibly update a central server. Inventory control becomes simpler as a result. Finally, cashier stations could verify a customer's purchase. As a result, billing may be done right in the trolley, saving clients a lot of time. [ABSTRACT FROM AUTHOR]

A key characteristic of free-range chicken farming is to enable chickens to spend time outdoors. However, each chicken may use the available areas for roaming in variable ways. To check if, and how, broilers use their outdoor range at an individual level, we need to reliably characterise range use behaviour. Traditional methods relying on visual scans require significant time investment and only provide discontinuous information. Passive RFID (Radio Frequency Identification) systems enable tracking individually tagged chickens’ when they go through pop-holes; hence, they only provide partial information on the movements of individual chickens. Here, we describe a new method to measure chickens’ range use and test its reliability on three ranges each containing a different breed. We used an active RFID system to localise chickens in their barn, or in one of nine zones of their range, every 30 seconds and assessed range-use behaviour in 600 chickens belonging to three breeds of slow- or medium-growing broilers used for outdoor production (all

The positioning method for mine track locomotives is mainly based on ultra wide band (UWB) positioning. But the complex environment of underground transportation roadways and frequent not line of sight（NLOS） propagation seriously impact the precision of UWB positioning. At present, research on positioning errors caused by NLOS has problems such as complex algorithms and poor real-time positioning. Based on the analysis of the positioning characteristics of railway locomotives and the UWB positioning technology based on the time of arrival (TOA), a positioning method of mine track locomotive based on NLOS error suppression is proposed. Two positioning cards are installed at different positions on the track locomotive. Radio frequency identification technology is used to accurately divide the relative position relationship between the positioning card and the positioning base station. The distance measurement value of the UWB positioning signal is greater than the actual value under NLOS propagation conditions. Based on this situation, the empirical range of the difference between the distance measurement value and the actual value between the two positioning cards is used to calculate the discrimination threshold for NLOS propagation conditions under different position nelationship between positioning cards and positioning base station. By using this discrimination threshold, the ranging value of the positioning signal propagated by NLOS path is eliminated. The ranging value of the positioning signal propagated by the line of sight path is used for positioning calculation, so that to suppress NLOS errors and improve the average positioning precision of mine track locomotives. The test results show that using the positioning method of mine track locomotives based on NLOS error suppression, the average positioning error of locomotives is within 1 m when the positioning signal is in line of sight propagation conditions. When the positioning signal is in NLOS propagation conditions, most of the NLOS errors are effectively suppressed. The average positioning precision is about 1 meter. The positioning precision of track locomotives has been greatly improved compared with normal UWB positioning method based on TOA.

In order to cope with the problems and new challenges arising from the application of Internet of Things (IoT) technology in urban management and to put forward corresponding administrative regulations, this paper explains the concept of IoT technology. And put forward the Internet of Things, radio frequency identification, wireless sensor networks, and other key technologies as the main level of the system architecture. Also, the perception layer, network layer, and application layer are the main levels of the system architecture. At the same time, it explains the specific characteristics of IOT technology and its specific applications in urban planning, transportation, medical care, family, and agricultural management. Zhoushan City, Zhejiang Province, China is chosen as the research object to analyze the application of IoT technology in urban management. The overall index score of Zhoushan City’s IoT city management construction is mainly concentrated between 60% and 70%, in which the scoring rate of the secondary indexes under the first-level index of the city’s intelligent governance regulations is relatively low, all below the 62% level, with an average value of less than 4. In the problem of information silos and shortage of talent, the mainstream opinions of Zhoushan City’s residents are “IoT applications are numerous and complex” and “lack of IoT applications”, respectively. In the problem of information silo and talent shortage, the mainstream views of Zhoushan residents are “the variety and complexity of IoT applications” and “the lack of protection mechanism for talents”, accounting for 68.64% and 58.12%, respectively, and 68.87% of the residents have not used IoT applications.

Class attendance is a key consideration when assigning final marks for courses taught, student attendance is a critical issue for higher institutions. Some institutions choose to regulate attendance with paper sheets, while others prefer to verify students' attendance with paper sheets and then manually enter this information into a computer. This mode of taking students attendance delays time and reduces the time needed for the lecture to be delivered. A system that eases the burden of time delay in taking attendance, promotes the universities, and supports parents is presented in this paper. The radio frequency identification and detection (RFID) student monitoring system has been developed to track student’s attendance in the classroom using passive RFID technology. The system uses an RFID reader and a contactless smart card to ensure time management during student’s attendance. A reader at a fixed place delivers a signal to a passive RFID chip for detection and identifies a huge number of chips in a short amount of time. The biometric thumb detection module for security was applied to improve the system. The applied enhanced technology sends a message to the parent of any students that fails to attend lectures. [ABSTRACT FROM AUTHOR]

The internet of things (IoT) is an emerging and robust technology to interconnect billions of objects or devices via the internet to communicate smartly. The radio frequency identification (RFID) system plays a significant role in IoT systems, providing most features like mutual establishment, key establishment, and data confidentiality. This manuscript designed secure authentication of IoT-based RFID systems using the lightweight PRESENT algorithm on the hardware platform. The PRESENT-256 block cipher is considered in this work, and it supports 64-bit data with a 256-key length. The PRESENT-80/128 cipher is also designed along with PRESENT-256 at electronic codebook (ECB) mode for Secured mutual authentication between RFID tag and reader for IoT applications. The secured authentication is established in two stages: Tag recognition from reader, mutual authentication between tag and reader using PRESENT80/128/256 cipher modules. The complete secured authentication of IoTbased RFID system simulation results is verified using the chip-scope tool with field-programmable gate array (FPGA) results. The comparative results for PRESENT block cipher with existing PRESENT ciphers and other lightweight algorithms are analyzed with resource improvements. The proposed secured authentication work is compared with similar RFID-mutual authentication (MA) approaches with better chip area and frequency improvements. [ABSTRACT FROM AUTHOR]

With the advent of the 5G era, radio frequency identification (RFID) has been widely applied in various fields as one of the key technologies for the Internet of Things (IoT) to realize the Internet of Everything (IoE). In recent years, RFID-based motion sensing has emerged as an important research area with great potential for development. In this paper, an RFID backscatter sport motion sensing scheme is proposed, which effectively solves the multi-classification problem by using the received signal strength (RSS) of the backscattered RFID and the error correcting output coding (ECOC)-based support vector machine (SVM). We conduct extensive experiments to validate the effectiveness of the proposed scheme, in which the signal intensities of different types of action poses are collected and the SVM is used as the classification algorithm to achieve high classification accuracies. [ABSTRACT FROM AUTHOR]

Seaports have a very important role in connecting freight by sea. Goods transported through seaports in the world are increasing day by day to meet human needs. This increases the pressure to apply more technologies for better port management. The world's seaports in the 4th generation, the generation in which seaports enhance connectivity to form a large network, have shown high efficiency when applying technology to port management. This optimizes port operations and connects port information into a network that improves productivity and reduces loading and unloading times. Today, the Internet of Things is the foundation for technologies to manage and optimize operations in various fields. It is considered by scientists to be a highly influential technology in the “4.0” era. The Internet of Things (IoT) technology directly affects the activities and processes of loading and unloading goods at seaports. Modern IoT-based port management technologies such as Radio Frequency Identification (RFID) and Dedicated Short Range Communications (DSRC) are contributing to the increased speed and safe movement of goods through seaports. The application of IoT in port management has become an inevitable trend and will be presented in this article. In the next generation, seaports tend to develop into smart ports based on rapidly developing technology platforms such as IoT, blockchain, and cloud computing. Smart port development also poses many issues to be resolved, including environmental issues. In this paper, the authors present some solutions to develop smart ports in an environmentally friendly manner.

With the continuous development of intelligent refrigerators, users are having higher and higher requirements for smart management of refrigerator contents. When using traditional machine learning algorithms to deal with refrigerator ingredients classification, problems such as slow recognition speed and low accuracy would often arise. At the same time, the classification accuracy is easily affected by the location of the content. Therefore, this paper uses continuous asymmetric convolutions and depthwise separable convolutions to improve the original Inception model and builds a classification prediction network based on the improved Inception model. The steps to applying the said model is as follows: First, we put the Radio Frequency Identification (RFID) tag on the food in the refrigerator, and then we collect the antenna data RSSI received by each tag through the reader. Finally, the RSSI is preprocessed and entered into the classification network to determine the location of the label. The proposed classification network has the advantages of possessing a simple structure, easy expansion of network depth, and fewer training parameters. The experimental results show that compared with other machine learning algorithms and pure convolution networks, the lightweight network model based on the improved Inception structure demonstrates great superiority. Compared with the original Inception structure, the enhanced network model is more lightweight. The number of parameters is reduced by 50%, and the amount of float‐point operations is reduced by 34%. Meanwhile, the accuracy of the lightweight model has been improved by 0.6%. Thus the improved model has better prediction performance in the classification of refrigerator content. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The technological diversity applied in practical examples entails the identification and the analysis of different implementation options, thus opening the way to a world of technology. The goal of this paper is to spot novel prospects for incorporating sensors and Big Data techniques for better property administration strategies, through an indoor localization and navigation architecture. The hereby analysis uses an approach that combines Radio Frequency Identification technology, performance efficient algorithms for calculating routes in very large datasets, methodologies for optimizing spatial representations and Internet of Things specific hardware distribution techniques to properly address challenging logistics issues and complex facilities management. The proposed solution is tailored for a large underground parking area in a commercial center, enabling easy car location identification, automatic parking time calculation and dynamically determined occupancy levels, along with descriptive statistics about busy time intervals or visiting patterns. [ABSTRACT FROM AUTHOR]

Body area network has attracted extensive attention for its applications in athletics, medical, diagnosis, and rehabilitation training in the next generation personalized health care solutions. Here, a contact‐separation direct current triboelectric nanogenerators (CSDC‐TENGs) based self‐powered wireless body area network (SWBAN) is reported that enables multi‐joint movements monitoring for human motion. The CSDC‐TENG is designed as a flexible active sensor with an internal contact switch, and the flexible substrate makes the TENG‐sensor stick onto skin easily. Due to the internal switch, the CSDC‐TENG could generate a DC current, a large instantaneous output voltage exceeds 700 V, and an instantaneous power can reach 1.076 W, which is more than 23 000 times higher than that of the traditional contact‐separation mode TENG in same size and materials without the switch. By coupling with flexible coil, the fixed high‐frequency radio signals can be modulated and emitted clearly ranging from 6 to 16 MHz, which can be wirelessly received and demodulated through a reader. Moreover, the SWBAN is demonstrated in a real time monitoring system for joints motion. This work has realized the wearable TENG for self‐powered wireless real‐time monitoring of body movements driven by low‐frequency human daily activities, which may promote a tremendous development of intelligent healthcare, wireless sensing system and body area network. [ABSTRACT FROM AUTHOR]

Copyright of Formosa Journal of Computer & Information Science (FJCIS) is the property of Formosa Publisher 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.)

Anthropogenic global warming has major implications for mobile terrestrial insects, including long‐term effects from constant warming, for example, on species distribution patterns, and short‐term effects from heat extremes that induce immediate physiological responses. To cope with heat extremes, they either have to reduce their activity or move to preferable microhabitats. The availability of favorable microhabitat conditions is strongly promoted by the spatial heterogeneity of habitats, which is often reduced by anthropogenic land transformation. Thus, it is decisive to understand the combined effects of these global change drivers on insect activity. Here, we assessed the movement activity of six insect species (from three orders) in response to heat stress using a unique tracking approach via radio frequency identification. We tracked 465 individuals at the iDiv Ecotron across a temperature gradient up to 38.7°C. In addition, we varied microhabitat conditions by adding leaf litter from four different tree species to the experimental units, either spatially separated or well mixed. Our results show opposing effects of heat extremes on insect activity depending on the microhabitat conditions. The insect community significantly decreased its activity in the mixed litter scenario, while we found a strong positive effect on activity in the separated litter scenario. We hypothesize that the simultaneous availability of thermal refugia as well as resources provided by the mixed litter scenario allows animals to reduce their activity and save energy in response to heat stress. Contrary, the spatial separation of beneficial microclimatic conditions and resources forces animals to increase their activity to fulfill their energetic needs. Thus, our study highlights the importance of habitat heterogeneity on smaller scales, because it may buffer the consequences of extreme temperatures of insect performance and survival under global change. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department 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.)

This paper proposes a new concept of using RFID tag antennas more actively in the identification process. This innovative concept is based on antenna native properties that allow RF harvesting for DC biasing, either from the reader or from other proximity RF sources at the same time. Nevertheless, for now, RFID identification tags without a self-DC power supply have become more popular and are referred to as passive. Eventually, both RF and light harvesting processes could be addressed as a foreseeable solution for identification range extension. Soon this trend will lead to the cheapest (printable) RFID tags at competitive prices closely shifted to those of the already mass-produced barcode tags, mainly in use today. The proposed semi-passive tag antenna is working by replacing the IMPINJ-MONZA chip with the EM4325 chip which can be DC supplied by a PV panel. This tag can work as RF energy harvester and can be DC biased as well, being the most capable for the proposed concept. The antenna is printed on paper using a metal powder ink printer and the tag is interrogated using a UHF-RFID reader. The harvesting for tag DC biasing is extended through a very small solar panel, which acts also as a substrate for the RFID antenna. Thus, the extended concept of the semi-active tag could increase the coverage and the sensing range of the reader significantly. This happens especially in daylight or when other nearby RF sources are available, otherwise, the tag will work as an ordinary one. This approach will allow the antenna to be shrunk even further near the Chu-Harrington limit. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the dimension of characteristic vector of received signal strength obtained by traditional RFID(radio frequency identification)indoor positioning technology is low, which can􀆳t fully describe the environment information and achieve good positioning effect in complex indoor environment, a robust and high precision indoor positioning algorithm based on joint fingerprint is proposed. Firstly, the algorithm extracted received signal strength indication and phase difference data from signals received by RFID readers, and established the fingerprint database. Then the PSO algorithm was improved by the concave function decreasing strategy and optimized the SVR model, trained the sample data, so the mapping relationship between the fingerprint characteristics of reference tags and their distance to the reader was established. Finally, the improved PSO algorithm was used to optimize iteratively to improve indoor positioning accuracy and robustness. In the simulation, the proposed algorithm was compared with GA-SVR and PSO-SVR algorithms, and the effects of different fingerprint data sets and the noise on positioning performance were analyzed. The simulation results show that the positioning accuracy and system stability of the proposed algorithm are better than those of the other two algorithms in the same fingerprint data set and environment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Fuzhou University is the property of Journal of Fuzhou University, Editorial Department 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.)

This paper presents a comprehensive overview and analysis of the state-of-the-art (SoA) in semi-passive or Battery-Assisted (BAP) Ultra-High Frequency (UHF) Radio Frequency Identification (RFID) sensor tags compliant with EPC Global G2/ISO-18000C. These tags operate on the same communication principle as fully passive sensor tags but incorporate a battery or an energy harvesting module. This additional power source extends communication ranges and enables power demanding applications using low-power microcontrollers (MCUs) and higher-end sensors. This article also analyzes various key features, including tag integrated circuit (IC) architecture, types of energy harvesting modules, and communication range. The main conclusions are threefold. Firstly, selecting the appropriate tag IC requires a careful analysis of its features such as sensitivity, sensor interfaces, or data logging capabilities. For instance, among the solutions examined in the SoA, half of them opted for a tag IC capable of MCU communication via SPI or I2C buses. Secondly, it is essential to assess both the forward and backward communication links to leverage the sensitivity of the tag IC in BAP mode. Interestingly, only one-third of the SoA solutions achieved the theoretical communication range anticipated by the sensitivity of the tag IC. Finally, an energy budget analysis is required to ensure that the energy generation suffices to meet the energy requirements of the tag. While most solutions rely on batteries as the energy source and analyze battery lifespan, only a few studies employing energy harvesters conduct an energy budget analysis due to the additional complexity involved.