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关键词： 物流运输   物流行业   智能仓储   物流企业   射频识别技术   智能化发展   有效应用   市场竞争  

摘要： 近年来,随着我国经济的高速发展,物流运输行业也随之蓬勃发展。物流行业面临着较好的发展机遇,有着较大的发展前景,但与此同时市场竞争也日益激烈,物流企业想要寻求更为长远的发展,就必须做到与时俱进,改变传统的物流运输管理模式,充分发挥智能仓储系统的作用,有效应用射频识别技术,以促进物流运输管理与跟踪水平的提升,逐步完善智能仓储功能,为物流行业注入新鲜血液,实现物流行业的智能化发展,更好满足人们的物流运输需求。

关键词： 防伪   RFID   装饰   一体化   瓶盖   环保喷涂  

摘要： 全新模块化设计环保瓶盖喷涂装饰工艺产线,将防伪瓶盖的结构防盗、印刷装饰、标识防伪技术的各自独立应用集成在装饰生产过程中,从源头上解决标识、标的物的应用配合问题,综合提升瓶盖的防伪水平。

关键词： radio frequency identification   collision tree   adaptive strategy   lock-bit   anti-collision  

摘要： 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.

关键词： Sensors   Gesture recognition   Radiofrequency identification   Wireless sensor networks   Wireless communication   Transfer learning   Mobile computing   RFID   few-shot learning   siamese network  

摘要： Performing accurate sensing in diverse environments is a challenging issue in wireless sensing technologies. Existing solutions usually require collecting a large number of samples to train a classifier for every environment, or further assume similar sample distribution between different environments such that a model trained in one environment can be transferred to another. In this paper, we propose RF-Siamese, an RFID-based gesture sensing approach that achieves comparable accuracy to existing solutions but requires only a few samples in each eivironment. RF-Siamese leverages Siamese networks to distinguish different gestures with only a small number of samples and is enhanced by several novel designs to achieve high accuracy in diverse environments. First, the network structure and parameters (e.g., loss function and distance metric) are carefully designed to be suitable for RFID gesture recognition. Second, a permutation-based dataset generation strategy is proposed to make full use of the collected samples to enhance the recognition accuracy. Third, a template matching method is proposed to extend the Siamese network to classify multiple gestures. Extensive experiments on commercial RFID devices demonstrate that RF-Siamese achieves a high accuracy of 0.93 with only one sample of each gesture when recognizing 18 different gestures, while state-of-the-art approaches based on transfer learning and meta learning achieve an accuracy of only 0.59 and 0.70, respectively.

关键词： authentication   industrial network   internet of things (IOT)   proximity   reliability and safety   RFID  

摘要： This research focuses on developing a proximity-based authentication and surveillance system using Internet of Things (IoT) devices in industrial networks. The system aims to improve security measures by ensuring only authorized personnel have access to critical areas of the network. Researching authentication mechanisms and protocols, examining network authentication system features and application environments, and developing an online-based, real-time monitoring authentication system are the goals of this article. The system will utilize sensors and cameras installed in strategic locations to detect and track personnel movement within the network. When a person approaches a secured area, their identity will be verified using proximity-based authentication using RFID technology. The system will also monitor and record any suspicious activity, providing real-time alerts to security personnel. To detect malicious behavior on short-range, low-rate, and low-power networks, such as those found in the Internet of Things (IoT), we advise utilizing SVM models. The proposed system is expected to increase security and reduce the risk of unauthorized access to industrial networks, ultimately enhancing overall network reliability and safety. The results are compared with various parameters.

关键词： VIoT   RFID   ITS   Bit formation   Right-shift rotation   Scyther   Communication   Cloud server   Tag   Reader   Hamming weight  

摘要： Vehicular Internet of Things (VIoT) refers to integrating Internet of Things (IoT) technology into the transportation sector, specifically vehicles. It aims to enhance transportation safety, efficiency, and sustainability by using connected devices and real-time data exchange between vehicles, road infrastructure, and transportation management systems. RFID can provide valuable insights into the functioning and performance of vehicles, enabling the development of intelligent transportation systems and contributing to the growth of the VIoT. To secure essential driving data tag location, data privacy, and road safety are the primary concerns in the VIoT system. An attacker can perform a variety of attacks on the tag and compromise its privacy through the wireless channel between it and the reader. To ensure secure communication for the various application of the VIoT system, An RFID-based protocol is proposed, which is referred to as UPSRVNet (Ultralightweight, Privacy preserved, and Secure RFID-based authentication protocol for VIoT Networks). The proposed protocol guarantees secure authentication in VIoT networks using ultralightweight, privacy-preserving RFID tags by substituting bit formation and right-shift rotation for high-computing operations like hash functions and encryption/decryption algorithms. It also reduces RFID tags' storage and communication overhead and aims to secure the driver's location, personal information, and resistance from known attacks. As per the experiment result, the proposed UPSRVNet protocol showed a significant reduction in communication overhead between tag and reader, that is 50%, and the storage cost on the tag is also reduced by 33.33% compared to existing protocols. Due to this, the certification and authentication processes may be performed quickly. The protocol ensured the security requirements by informal analysis using the Scyther tool. A comprehensive analysis of the proposed protocol reveals its substantial advantages ove

关键词： Energy efficiency  

摘要： The utilization of radio frequency identification (RFID) technology has witnessed a substantial rise in recent years, and this upward trend is expected to continue in the coming years. It is often described as an industry-changing concept, which is why continuous improvements in the technique of object identification are still needed. These enhancements are related to security, speed, and reliability of communications. RFID is frequently used in areas where a large number of things must be identified. Therefore, some problems of tag collision when many tags are transmitting their data are presented by these systems. The research presented here thoroughly analyzes and evaluates existing tag reading approaches that offer low power consumption during identification. The outcome of this work is the proposal of energy-efficient anti-collision protocol, namely HT-EEAC. By assessing the energy consumed for HT-EEAC at checkpoints, we were able to increase throughput and reduce energy consumption in our protocol. The HT-EEAC approach for updating frame size aims to enhance the energy and throughput of the EPC C1 G2 UHF RFID standard. Performance comparisons demonstrate the advantages of the strategy we propose in terms of low energy consumption per identified tag, minimal collisions, and high throughput. As a result, this method can be effectively utilized in the field of RFID systems to significantly enhance their efficiency. © 2024

关键词： Antenna arrays   Antennas   Metals   Radiofrequency identification   Directive antennas   Antenna feeds   Reflector antennas   1-bit reflectarray   metal environment   near-field focused   radio frequency identification (RFID)   standing wave cancelling  

摘要： In this letter, a radio frequency identification (RFID) near-field focused polling antenna array working with insensitive polarization 1-bit reflectarray is proposed for semi-open metal shelf applications. Composed of two 3 x 2 focused antenna arrays and two polling feeding networks, the antenna array is designed to realize multiple focal points, and generate the electric field distribution in accordance with the shape of the shelf, which contributes to avoiding error reading tags outside the interrogation zone. The reflectarray controlled by pin diodes is used to deal with the interference of shelf board in the near-field application. Standing waves will occur due to the reflection of shelf board when the antenna array is working. By switching the work states of the pin diodes, the nodes/antinodes of the standing waves in metal shelf are moved. Then, the miss reading problem of the tags in the nodes of standing waves is solved. Measurement results show that the RFID near-field antenna array working with 1-bit reflectarray can achieve 100% reading rate inside the shelf and no error reading outside.

关键词： bedload dispersion   bedload transport   gravel-bed rivers   RFID tracing   sediment management  

摘要： Soon after their first deployment in rivers in the early 2000s, RFID tags rapidly became the reference technology for bedload tracing in rivers. We can estimate from the literature that during the last 20 years, more than 30,000 RFID tracers have been injected in gravel-bed rivers all around the world to study bedload transport. Many field experiments have been reported in a great diversity of fluvial environments, complemented by many laboratory experiments and methodological developments. This paper proposes a review of these works, notably based on the compilation of more than 350 RFID surveys, complemented by 97 magnetic surveys, for a total of 125 study sites. The meta-analysis of this database shows that RFID tracers have improved our understanding of sediment transport in fluvial environments with rapid bedload dispersion. It is also shown that central positions of tracer plumes are moving faster over time than tracer leading fronts, as attested by a general relation between maximum and mean distances of transport. The most recent methodological developments based on the use of active UHF RFID tags show that it is now possible to conduct efficient bedload tracing experiments not only in small streams, but also in large gravel-bed rivers or very active braided channels. Other addressed topics include RFID deployment and survey in river channels, controlling factors of tracer mobility (flow conditions, grain-size and shape, channel morphology), bedload monitoring approaches using RFID tracers, and applications of RFID tracers for evaluating human effects on bedload transport. Key challenges of bedload tracing with RFID tags are also proposed. A review of field and laboratory radio frequency identification (RFID) bedload tracing experiments is proposed, including a meta-analysis of data coming from 459 tracer surveys for a total of 125 study sites. RFID tracers open new avenues for exploring fluvial environments prone to rapid bedload dispersion. The most recent

关键词： Internet of Things   intelligent transportation systems   unknown tag identification   COTS RFID tag   analog hash  

摘要： Over the last decade, the Internet of Things (IoT) technology has advanced significantly in a variety of fields. As a pivotal application of IoT, intelligent transportation systems (ITS) have harvested great attention from the research community. Radio frequency identification (RFID) which is an essential technology in IoT plays a key role in ITS to identify tagged vehicles. Unknown tag identification which aims at identifying the existing unknown tags is crucial to monitor the newly entering vehicles in the RFID-assisted intelligent transportation systems. However, the COTS (commercial-off-the-shelf) RFID tags that harvest energy from the reader can not support the hash function in reality, which hinders the widespread deployment of hash-enabled unknown tag identification protocols. To conquer this tough issue, we propose two approaches to efficiently identify unknown COTS RFID tags. We first propose a Single-Point Selective unknown tag identification approach called SPS, where an analog hash pattern using the EPC (Electronic Product Code) segments is deployed to exclusively identify unknown tags. An unknown tag will be identified when it selects a singleton slot to reply. To improve the time efficiency of SPS, we further propose a Multi-Point Selective unknown tag identification approach called MPS. In MPS, two techniques of batch identification and batch division are developed to reduce the number of empty slots and avoid tag collisions, respectively. Then the parameters are theoretically analyzed to maximize the identification efficiency. The effectiveness of the proposed approaches is validated via both the simulations and COTS RFID device based experiments.