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关键词： Accuracy   cluster count   cluster head   centrality   energy   RFID   dynamic cluster head selection (DCHS)   fuzzy logic  

摘要： This paper uses radio frequency signals for non-contact tracking and localization utilising Radio Frequency Identification (RFID) technology. The clustering approach is quite useful when dealing with large RFID readers. This method stimulates the expansion of RFID nodes without compromising the overall network performance. The Cluster Head (CH) is the most critical node in a clustered RFID system. This research presents a method for dynamically selecting the cluster head that takes the connectivity and power of each RFID reader into account. In dynamic mode, selecting a new cluster head is based on Fuzzy Logic. Based on these data, the energy level of 0.443 and centrality of 0.809 are the thresholds at which a node has a 91.8 % chance of becoming a CH. Managing massive RFID networks is also handled, with cluster numbers increasing at different intervals. The RFID network's effectiveness is determined by measuring throughput, accuracy, delay, success, and error rates. The network may accommodate up to a thousand nodes with 13 node leaders for improved capacity. The results show a 97.8 % success rate, 0.22 % accuracy, a 2.64 % error rate, and a 36.91 second latency.

关键词： Gesture recognition   Radiofrequency identification   Antennas   Accuracy   Convolutional neural networks   Backscatter   Medical services   Feature extraction   Character recognition   Wireless sensor networks   RFID   Markov transition field   fine-grained recognition   neural network  

摘要： Gesture recognition serves as a foundation for Human-Computer Interaction (HCI). Although Radio Frequency Identification (RFID) is gaining popularity due to its advantages (non-invasive, low-cost, and lightweight), most existing research has only addressed the recognition of simple sign language gestures or body movements. There is still a significant gap in the recognition of fine-grained gestures. In this paper, we propose RF-AIRCGR as a fine-grained hand gesture recognition system for Chinese characters. It enables information input and querying through gestures in contactless scenarios, which is of great significance for both medical and educational applications. This system has three main advantages: First, by designing a tag matrix and dual-antenna layout, it fully captures fine-grained gesture data for handwritten Chinese characters. Second, it uses a variance-based sliding window method to segment continuous gesture actions. Lastly, the phase signals of Chinese characters are innovatively transformed into feature images using the Markov Transition Field. After a series of preprocessing steps, the improved C-AlexNet model is employed for deep training and experimentation. Experimental results show that RF-AIRCGR achieves average recognition accuracies of 97.85% for new users and 97.15% for new scenarios. The accuracy and robustness of the system in recognizing Chinese character gestures have been validated.

关键词： Firebase   RFID   售货机   反向自动售货机  

摘要： 背景与意义: 全球科技飞速发展,柬埔寨仍有大多数教育机构仍然使用传统的纸质学生证。学生证主要用于身份识别,在课堂出勤和食堂支付等方面同样也发挥着重要作用,而传统的纸质卡片已无法满足现代化管理的需求。因此,为提高学生证的便利性和实用性,本研究设计了基于Google Firebase数据库的RFID卡自动售货机和反向自动售货机支付和存款系统,可以对废旧瓶子进行回收计费。基于RFID卡射频技术,数据存储于Google Firebase数据库。为实现上述功能,所设计系统由管理机、自动售货机和反向自动售货机构成,管理机主要用于将数据上传到谷歌Firebase,自动售货机基于RFID卡射频技术销售产品,反向自动售货机用于回收废弃瓶子。所设计系统在智能化应用、RFID射频技术应用和资源回收利用等方面具有重要的促进作用。 研究内容: 本研究所设计系统重点利用谷歌Firebase数据库进行数据存储编辑,与其他数据库相比,Firebase数据库具有实时数据同步、可扩展性、离线支持、实时查询、跨平台兼容性、安全性以及与其他Firebase服务的集成等优势。 实时数据同步确保了数据的即时更新,避免了传统数据库在数据同步方面可能出现的延迟和误差,提高了系统的响应速度和数据准确性。同时,通过将数据存储在云端,用户可以在任何地点通过任何设备访问和更新数据,极大地提高了系统的可扩展性和灵活性。离线支持则是Firebase数据库的另一大优势。在网络不稳定或中断的情况下,系统仍然可以执行基本操作,确保了系统的稳定性和可靠性。这种特性尤其适用于像柬埔寨这样的国家,网络基础设施尚有待完善,需要更加稳定的系统来保证数据的安全性和一致性。系统实时查询则提高了数据处理效率。用户可以立即获得他们所需数据,避免了等待数据传输和处理的时间。这对于需要快速响应用户查询的系统来说至关重要,如自动售货机和反向自动售货机,它们需要快速处理用户请求,提供即时的反馈。跨平台兼容性使得系统能够在不同的设备上无缝运行,无论用户使用的是哪种操作系统,都可以使用该系统。这对于提升用户体验和扩大用户群体非常重要。安全性是Firebase数据库的另一大优势。它采用了严格的数据加密和安全措施,确保数据不被非法获取或篡改。这对于保护用户的支付信息和交易数据至关重要,确保了系统的安全性。与其他Firebase服务的集成进一步增强了系统的功能。例如,通过与Firebase Authentication集成,系统可以提供安全的用户身份验证和授权机制,确保只有授权用户可以访问和操作数据。此外,通过与Firebase Cloud Messaging集成,系统可以发送实时通知和提醒给用户,提供更个性化的体验。综上所述,Firebase数据库的这些优势使其成为本项目的理想选择。通过利用Firebase数据库的实时数据同步、可扩展性、离线支持、实时查询、跨平台兼容性、安全性以及与其他Firebase服务的集成,本研究成功设计和实现了一个基于RFID的支付和存款系统,该系统在自动售货机和反向自动售货机中表现出了出色的性能和用户体验。 为实现上述研究功能,本研究设计了基于Google Firebase数据库的RFID卡自动售货机和反向自动售货机支付和存款系统,由管理机、自动售货机和反向自动售货机构成。使用RFID卡射频技术,简化支付流程,提高交易效率。 管理机作为项目主要构成,它与Google Firebase通信,存储数据,创建学生号和删除账户,充值和取款,控制库存。管理机采用ESP 8266、RFID RC522、步进电机、人机界面显示和电源等单元。使用DC5V/5A电源供电,采用HMI显示器进行触摸控制,从而实现RFID卡数据读写操作。 用户管理:基于Firebase数据库实现用户创建和删除,同时可实现充值操作。具体操作如下:选择管理用户,在新窗口中选择添加用户或删除用户,若添加用户,使用学生ID,将RFID卡数据上传并写入Firebase数据库;若删除用户,输入学生ID,确认删除后,将学生ID数据从Firebase数据库中删除,结束当前操作。 资金管理:用于RFID卡的充值和取款。首先登录系统,选择资金管理,在显示的新窗口选择充值和取款。当选择充值或取款时,输入金额确认。如果需要取款,只需在数字前输入减号(-)即可。下一步将RFID卡数据上传并及时更新到Firebase实时数据库。 库存:用于查询自动售货机的库存、添加库存以及更改饮料价格。首先登录系统,然后选择库存,在新窗口中显示自动售货机库存余额和产品价格。若需更新库存或价格,只需在其对应类别上键入数据并触摸“更新”按钮,这样数据就会更新到Firebase,自动售货机也会更新日期。 自动售货机由RFID、HMI显示器、Arduino Uno、步

关键词： 在线管理系统   RFID   目标检测   工厂化育苗  

摘要： 随着现代农业及生态农业迅速发展,育苗产业不断创新,近年来涌现出越来越多的育苗工厂,相较于传统的人工育苗方式,工厂化育苗采用“流水线”作业模式,生产效率高,出苗质量好。工厂化育苗蓬勃发展的过程中,随着育苗工厂规模不断扩大,生产管理过程中的问题逐渐显露:当穴盘数量和幼苗品种过多,依靠人工跟踪穴盘位置、判断种苗合格率开始变得困难,易造成穴盘流转信息丢失、位置跟踪不准确、种苗合格率误判等问题。针对上述问题,使用RFID技术,将RFID标签、穴盘以及种苗三者绑定,实现穴盘的信息化,通过读取RFID标签实现对应穴盘和种苗的实时跟踪与定位;使用目标检测技术识别幼苗,判定穴盘出苗率,为补苗做准备;再结合物联网技术、互联网技术等,整合各项实时生产数据,开发工厂化育苗在线管理系统,实现育苗工厂的无接触、智能化、远程在线管理,提升育苗工厂管理效率,助力育苗工厂实现农业智慧化转型。主要研究内容如下: (1)结合工厂化育苗的管理特点,确定了工厂化育苗的生产管理主要是对于穴盘的管理。在此基础上,对工厂化育苗在线管理系统的功能需求进行了分析,确定了系统的主要功能。进行系统的总体设计,确定了系统的总体架构和功能模块划分。 (2)对硬件系统进行了设计。主要包括主控单元、RFID读写设备、图像采集设备、环境状态检测设备四部分,采用模块化设计的方式,首先设计主控单元的关键组件,然后分别对其余功能模块进行详细设计,包括关键设备选型以及相关电路设计。 (3)进行了穴盘全过程跟踪与坐标定位的研究与设计。首先使用RFID非测距定位方法识别穴盘所在区域以及管理穴盘出入库,完成了穴盘的全过程跟踪。接着使用RFID测距定位方法实现穴盘坐标定位,对原始LANDMARC算法进行改进,优化了定位区域的参考标签布置,让改进的算法更好地适应于育苗工厂的实际场景,优化了邻近标签权重公式,让算法具有更强的扛噪声能力;使用改进前后的算法做定位仿真实验,测试算法改进效果,改进后的算法平均误差为0.180 m(50次实验),提高定位精度14.59%,且抵抗噪声的能力更强;然后使用改进算法进行现场定位实验,50次定位实验的最高误差为0.492 m,最低误差为0.019 m,平均误差为0.247 m,即使误差最高的一次也能满足实际生产过程中穴盘坐标定位的需求。 (4)实现了穴盘幼苗检测及其出苗率判定。在YOLOv7 tiny网络模型中添加了ECANet注意力机制模块,得到改进后的模型ECANet-YOLOv7 tiny。建立穴盘幼苗数据集,采集了3016张刚完成催芽的穴盘种苗照片并标记幼苗,按照6:2:2划分训练集、验证集、测试集。对改进模型的检测性能进行分析,首先将ECANet-YOLOv7 tiny与其他注意力机制改进的模型进行了对比试验,然后将其与目前主流先进模型进行对比实验,两次对比试验的结果都表明该模型在穴盘幼苗检测中有着更优的表现,其召回率为89.21%、精确率为91.97%、F1得分为0.91、m AP为93.34%、GFLOPS为13.18 G、参数数量6.01 M、FPS为83.00,该模型性能优异,能高效完成穴盘幼苗检测。进行穴盘幼苗检测模型的部署,并使用精确度和召回率优化了出苗率计算公式。 (5)完成了信息管理软件和WEB可视化大屏的设计与开发。设计了数据库以及各数据表格之间的关联查询关系,基于QT开发了信息管理软件,主要包括员工信息、种苗信息、穴盘信息和农资及设备信息4个模块,设计开发了WEB数据可视化大屏,分析其数据加载流程,然后开发了首页、穴盘全过程跟踪、种苗生产统计、出苗统计、数据监测、农资农事6个信息展示界面。最后进行了用户管理模块、信息管理软件和WEB可视化大屏的功能测试,一共使用24个用例进行测试,全部通过,表明所有功能正常无误;对WEB数据可视化大屏进行性能测试和兼容性测试,全部通过测试。

关键词： RFID   software-based shielding   fashion retail   industrial environment   machine learning  

摘要： PURPOSE: The present paper investigates the real performances of Software-Based Shielding (SBS) in two different stores of fashion retailers located in Northern Italy. DESIGN/METHODOLOGY/APPROACH: The study is based on a double case study analysis. Six different factors have been chosen, with two levels each. Namely, we investigated two different (i) stores;(ii) reader models;(iii) power levels;(iv) classification methods;(v) training data sets and (vi) settings of reference tags. The results have been evaluated in terms of overall and specific accuracies, and in percentage of false front (i.e., tags wrongly located in the sales floor area). FINDINGS: SBS proves to be a sound method for classifying tags' location during normal operations in real-life stores, with overall accuracy up to 0.95. Of the two readers, reader A shows better results in terms of both overall and front accuracy, whereas reader B performs better in terms of rear accuracy and percentage of false front. With respect to the classification method, the combination of Method 2 with reads from reader A provides the best results. With respect to the training data, the use of front and back reads for training performs mostly better than the training with sole front data. ORIGINALITY: We are not aware of any other study that performed and reported results of SBS testing under normal operations in real stores. To the best of our knowledge, this study is the first one to report such results. RESEARCH LIMITATIONS: Main limitations of our research are the limited set of factors and levels, and the specific classification methods that we used, labelled as Method 1 and Method 2. Also, we did not consider tags disposition and density in our study. PRACTICAL IMPLICATIONS: We prove that SBS is a feasible option that could replace physical shielding in retail stores. We call to action for further research on this topic, and for retailers to test it in different store locations.

关键词： RFID   anti-collision   partition   bit-mapping   empty-slot avoidance  

摘要： In RFID systems, many anti-collision algorithms, driven by the concept of rescheduling the response sequence between the reader and unidentified tags, have been put forward to solve tag collision problem, including ALOHA-based, tree-based and hybrid algorithms. In this paper, we propose a novel RFID anti-collision algorithm called EAQ-CBB, which adopts three main approaches: tag population estimation based on collided bit detection method, optimal partitions and trimmed query tree based on the strategy of collided block bit-mapping (QTCBB). The relatively accurate estimation of tag backlog and optimal partition ensure a great reduction of collisions in the initial phase. For each collided partition, a QTCBB process is introduced immediately, which eliminates all the empty slots and significantly reduces the collided slots. Simulation results show that EAQ-CBB performs good stability and scalability when the key parameters change. Compared with the existing algorithms, such as DFSA, QTI, T-GDFSA and CT, EAQ-CBB outperforms the others with high system throughput, low normalized latency and low normalized overhead at a low cost of energy, which makes it easier to be used widely in the efficient-aware and energy-aware applications.

标准号: GB/T 43495-2023

摘要： 本文件规定了基于不同技术（植入式、补片式、粘贴式）的轮胎用射频识别（RFID）电子标签（以下简称RFID电子标签）应用，用于用户理解其差异、目标、可能的应用及局限性。本文件包括：每项技术的通用要求;RFID 轮胎的推荐识别标识。