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关键词： Sustainable   Weaving   Spinning   Dyeing   Blockchain   Automation   RFID   Digitization  

摘要： Purpose The purpose of this review paper is to thoroughly assess and analyze the progression of technology and research in textile material and machine manufacturing over the past ten years. The primary focus is on understanding how advancements in technology, including mechatronics, smart technology, digitization, and artificial intelligence, contribute to enhancing stakeholders' experiences. Design/methodology/approach This review paper is designed to comprehensively explore the technological advancements within the textile industry. The information is gathered from diverse sources such as academic research, industrial research, machine manufacturers, and textile manufacturers. The methodology involves an in-depth examination of both the transformative impact of digitization and the integration of commercially viable technologies, emphasizing their adoption and adaptation to enhance manufacturing processes and competitiveness. Findings Significant progress has been achieved through technical advancements, research, digitization, and the integration of artificial intelligence (AI) in the fields of fiber manufacturing, spinning, weaving, knitting, textile machinery, dyeing, and monitoring in the past decade. Advanced technologies such as blockchain, soft computing, and AI technologies have brought a new era of textile manufacturing through enhanced efficiency, optimized processes, improved product quality, and reduced resource consumption throughout the textile production life-cycle. The labor-intensive industry is shifting towards the digital automatic industry which is providing a lot of opportunities and challenges. Originality/value The review explores recent textile technological advancements, emphasizing digitization and AI's transformative role in processes and product quality enhancement. It uniquely integrates academic and industrial research, highlighting the industry's shift towards digital automation and its impact on efficiency and sustainability.

关键词： Radio frequency identification (RFID)  

摘要： This paper presents ArmTenna, a novel articulated RFID-based exploration robot designed to address challenges in dynamic warehouse inventory management. The robot integrates a custom-built base, two 4-degree-of-freedom (DOF) robotic arms with Radio Frequency Identification (RFID) antennas, and a 2DOF neck supporting a depth camera. This unique configuration enables targeted RFID sensing and visual object detection during exploration. ArmTenna employs an advanced frontier-based exploration strategy. This approach integrates RFID sensing data, visual object detection, and traditional mapping techniques to make informed decisions about navigation priorities. The robot’s decision-making process prioritizes frontiers based on three key parameters: the number of unique RFID tags detected, their average Received Signal Strength Indicator (RSSI), and the count of potential product objects identified by an onboard neural network. To assess the potential advantages of this approach, we conducted comparative experiments between ArmTenna and Robin50, a robot employing a simpler RFID-guided exploration strategy with fixed antennas. The experiments results shows that ArmTenna efficiently explored approximatly 97% of all the RFID-environment while the counter only 72%, demonstrating superior speed, completeness, and efficiency in its exploration pattern. This study highlights the advantages of ArmTenna’s advanced multi-modal sensing approach and articulated design in complex warehouse environments. This work contributes to the ongoing development of more adaptive and comprehensive automated inventory systems, addressing critical challenges in modern supply chain management. © 2025, The Authors. All rights reserved.

关键词： radio frequency identification (RFID)   Cole-Cole model   adaptive extended Kalman filter (AEKF)   concentration monitoring  

摘要： Salt concentration monitoring is crucial for industrial process control and wastewater management, yet existing methods often lack real-time capability or require invasive sampling. This paper presents a novel RFID wireless sensing system for noninvasive solution concentration monitoring, combining physical modeling with advanced estimation algorithms. By combining the Cole-Cole model and the slit cylindrical capacitor (SCC) model, the system establishes physics-based state-space models to characterize concentration-dependent RFID signal variations. The concentration dynamics are modeled as a hidden Markov process and tracked using an adaptive extended Kalman filter (AEKF). The AEKF algorithm avoids computationally expensive inversion of complex observation equations while automatically adjusting noise covariance matrices via innovation sequence. Experimental results demonstrate a mean relative error (MRE) of 2.8% for CaCl2 solution across 2-10 g/L concentrations. Within the experimentally validated optimal range (2-8 g/L CaCl2), the system maintains MRE below 3% under artificially introduced measurement noise, confirming its strong robustness. Compared with baseline approaches, the proposed AEKF algorithm shows improved performance in both accuracy and computational efficiency.

关键词： RFID   respiratory monitoring   motion disturbances   respiratory rate estimation  

摘要： Traditional respiratory monitoring methods typically use wearable sensors. In recent years, Radio Frequency Identification (RFID) tags have emerged as potential respiratory monitoring devices. However, existing research only detects respiration under static or simple body movements such as forward and backward motions, which limits the availability of RFID. In this article, an RFID-based respiratory monitoring system under body motion disturbances is proposed. In order to eliminate the effect of body movement on the signal, reference tags are placed on the user's shoulders. The phase between different tags is calibrated and aligned to remove the discreteness. Then, a sliding window peak-seeking algorithm is designed to calculate respiratory rate over time. The system measures respiratory rate during daily exercise and maintains an accuracy of no less than 86.12%, even when influenced by lying down and turning. Additionally, the system can analyze estimated respiratory rates and intervals to provide alert information.

关键词： Inventory   SMEs   carbon emission   preservation technology   RFID   AI and ML  

摘要： Effective inventory management is crucial for small and medium-sized enterprises (SMEs) to enhance efficiency, reduce costs, and adopt sustainable practices. This study introduces an inventory model that integrates demand dynamics, preservation technology, and sustainability measures, addressing price, time, and advertisement frequency to optimize strategies. Carbon emission regulations are incorporated to promote eco-friendly operations. AI-driven demand forecasting enables precise predictions by analyzing historical sales data, seasonal trends, and external market factors, while ML-based optimization dynamically adjusts inventory policies to minimize costs and improve supply chain performance. Automated inventory tracking using barcode and RFID technologies ensures real-time visibility and accuracy, reducing errors and streamlining warehouse operations. RFID, in particular, provides non-line-of-sight tracking, enhancing inventory monitoring capabilities. These technologies not only improve operational efficiency but also generate actionable insights for strategic decision-making. The theoretical properties of the model are validated through numerical examples and sensitivity analyses. The findings underscore the importance of integrating modern technologies and sustainability measures in inventory management, demonstrating that SMEs can reduce operational costs, enhance efficiency, and build resilient, eco-friendly supply chains. This research showcases how leveraging advanced inventory models enables SMEs to remain competitive, financially viable, and environmentally responsible.

关键词： Metallic formworks   Tracking   BIM   IoT   RFID   Management  

摘要： PurposeTracking physical resources at the construction site can generate information to support effective decision-making and building production control. However, the methods for conventional tracking usually offer low reliability. This study aims to propose the integrated Smart Twins 4.0 to track and manage metallic formworks used in cast-in-place concrete wall systems using internet of things (IoT) (operationalized by radio frequency identification [RFID]) and building information modeling (BIM), focusing on increasing quality and ***/methodology/approachDesign science research is the research approach, including an exploratory study to map the constructive system, the integrated system development, an on-site pilot implementation in a residential project and a performance evaluation based on acquired data and the perception of the project's production *** all rounds of requests, Smart Twins 4.0 registered and presented the status from the formworks and the work progress of buildings in complete correspondence with the physical progress providing information to support decision-making during operation. Moreover, analyses of the system infrastructure and implementation details can drive researchers regarding future IoT and BIM implementation in real construction ***/valueThe primary contribution is the system proposal, centralized into a mobile app that contains a Web-based virtual model to receive data in real time during construction phases and solve a real problem. The paper describes Smart Twins 4.0 development and its requirements for tracking physical resources considering theoretical and practical previous research regarding RFID, IoT and BIM.

关键词： 电网电表   EFQ算法   自动化巡检   RFID   数据采集  

摘要： 在智慧电网的整体发展趋势下，为解决大规模设备管理中效率低下的问题，本文设计并提出了电网大规模设备盘点智慧系统。该系统通过整合机器人巡检技术、物联网数据采集手段及智能化数据处理技术，为大规模电网设备的自动化巡检与高效管理提供了一种系统化的解决方案。然而，RFID标签冲突问题成为该系统在密集标签场景下高效运行的关键瓶颈。为此，本文在智慧系统的设计基础上，面向该系统提出了一种智能增强型动态帧队列算法（EFQ）。EFQ算法通过动态帧调整与优先级优化策略，提升了高密度场景下的识别效率与系统稳定性。本文对EFQ算法与IABS算法、ICT算法的性能表现进行了对比。实验结果表明，EFQ算法在吞吐量和冲突率方面表现出显著优势，冲突率降低超过30%，系统效率提升约15%。尽管在识别时间上与其他算法相比无显著差异，但EFQ算法的整体性能更加稳定，尤其适用于密集标签场景的设备管理需求。

关键词： RFID定位   边缘计算   相控阵天线   A3C算法   复杂环境   多路径效应  

摘要： 为了提升RFID定位技术在复杂环境中的精度、鲁棒性和实时性，本文提出了一种基于多节点边缘计算协同的RFID相控阵智能定位方法。该方法利用相控阵天线实现波束动态控制，结合多节点边缘计算处理大规模标签数据，从而降低多路径效应和信号衰减的影响。同时，系统集成A3C强化学习算法，根据环境变化动态优化定位参数，提高系统适应性和稳定性。实验分别在标准环境和复杂环境下进行测试，复杂环境中模拟了大量金属货架、多路径效应和动态干扰源，并对比RSSI、TDOA及本文方法的定位误差和准确率。实验结果表明，在标准环境中，本文方法的定位误差降低至0.8-0.9米，准确率达到92%；在复杂环境中，误差控制在1米以内，准确率保持在90%以上，显著优于传统方法。此外，在智能仓储资产管理系统中的实际应用验证进一步证明了该方法的高精度和鲁棒性，盘点准确率从85%提升至96%，误判率降至1.5%。本文研究为RFID定位技术在智慧城市、电网资产管理和物流仓储等领域的应用提供了可靠的技术支撑，展现出优异的环境适应性和高效的定位能力。

关键词： Sensors   Chipless RFID   Capacitors   Dielectric measurement   Semiconductor device measurement   Transmission line measurements   Sensor phenomena and characterization   Chipless radio frequency identification (RFID)   chipless RFID sensors   dielectric constant   minerals   relative permittivity   rocks   sensory tag   relative permittivity   rocks   sensory tag  

摘要： This article introduces an innovative approach to measure the dielectric constants of solid geological samples using a cross-polarized chipless radio frequency identification (RFID) sensor. Co-polarized RFID sensors often face interference from the material under test (MUT), resulting in significant deviations in resonance frequency. To address this issue, we developed a cross-polarized chipless RFID sensor that transmits and receives signals in different polarization directions, enhancing measurement accuracy. Our sensor features resonator-integrated ground plane cylindrical capacitors designed to detect variations in the dielectric properties of minerals and rocks. Both simulation and experimental validation indicate that the sensor can identify dielectric constant variations ranging from 1 to 10, with a frequency shift sensitivity of 63.5 MHz per dielectric unit. The sensor was tested on various mineral and rock samples, demonstrating alignment with established dielectric values. Operating effectively across a wide frequency range of 3.1-10.6 GHz, the system is well-suited for ultrawideband (UWB) applications. This proposed method is cost-effective, compact, and compatible with remote sensing platforms, presenting a promising alternative for mineralogical and geophysical testing applications.

关键词： Internet of Things   Security   Authentication   Protocols   Systematic literature review   Object recognition   Privacy   Keyword search   Computational modeling   Complexity theory   Attacks   authentication   Internet of Things (IoT)   protocols   RFID   security   technologies  

摘要： The idea of the Internet of Things (IoT) is to connect objects and smart devices with any digital element seamlessly at anytime, anywhere, with anything. These devices or objects are characterized by low power consumption, lower bandwidth usage, limited processing power, and limited memory capacity. This article presents a systematic literature review (SLR) of the state-of-the-art security challenges of IoT systems designed for authentication. It reports the strengths, weaknesses, threats, and attacks associated with the proposed authentication models. In addition, a comprehensive analysis of IoT-compatible protocols, enabling technologies, and countermeasures to mitigate risk in IoT is investigated. This study uses the PRISMA methodology to review peer-reviewed articles published from 2014 to 2023, studying 100+ papers by selecting approximately 10 papers each year. It provides a detailed overview that contrasts and compares the advances in securing IoT devices to date while identifying remaining open research questions for IoT security designs. This article highlights the need for a survey integrating authentication models with compatible protocols and other lightweight technologies. The examination and analysis in this work contribute to the body of knowledge and serve as a roadmap for researchers and practitioners to improve their work while designing IoT security models.