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关键词： 存货管理   物联网   RFID技术   联合库存管理模式  

摘要： 随着我国乳品需求量扩大和行业竞争加剧,企业为抢占市场份额纷纷扩大其生产规模,存货管理效率的提升成为企业取得竞争优势的关键,如何准确预测市场需求、控制存货质量、加快存货周转,对提升存货管理效率和降低存货管理成本具有重要意义。物联网作为一种数据交互通信网络,在数据信息的采集、传递、处理和物品的定位、检测、控制等方面具有信息化、智能化、精确化的特点,开始被乳品企业应用于优化存货管理。本文运用文献研究法、案例分析法、比较分析法,在通过研读文献形成物联网背景下企业存货管理优化的理论基础上,选取采用物联网技术进行存货管理的GM乳业为研究对象,通过对其2016—2020年的存货总量、存货结构、存货周转率以及存货跌价准备等指标的分析,发现物联网技术对其存货管理有一定的效果,但在与同行业企业和行业均值的比较,发现仍存在以下存货管理问题:存货构成中产成品占用资金过大、产成品周转速度缓慢、原材料跌价准备计提比例过高、存货分类核算不合理等。结合该企业存货管理模式、行业竞争、战略布局、行业风险等角度,深入分析问题的成因是产能过剩、产品市场占有率低、销售渠道落后、原奶市场价格下降等,并针对性的提出了物联网背景下GM乳业存货管理的优化建议:(1)建立基于物联网的联合库存管理模式,完善存货销售管理和需求预测管理,加强联盟间存货信息共享;(2)加大研发投入同时配合乳品质量追溯以提高产品竞争力;(3)协同物联网冷链物流来拓宽销售渠道;(4)加强上游智慧牧场建设以推进全国奶源布局;(5)加强基于物联网的存货精细化核算。本文的创新之处表现在结合物联网技术与乳品行业存货管理,研究物联网技术在案例企业存货管理中存在的问题,并提出优化建议,从乳品供应链整体上完善GM乳业存货管理流程,实现降低存货管理成本、提高存货管理效率、提升企业竞争力的目的,以期对物联网技术在企业存货管理中的深入应用提供案例参考。

关键词： 室内定位   射频识别技术   到达角   天线孔径   神经网络  

摘要： 正在蓬勃发展的新一代信息技术为人们生产生活的各个领域带来了深刻的变革。作为国家命脉的工业和制造业正在逐渐转化升级为以人工智能和大数据技术赋能的工业互联网,工业自动化、智能化水平不断提高。基于物品位置的服务(Location-Based Services,LBS)能够极大提升工业自动化的效率。射频识别技术(Radio Frequency Identification,RFID)具有价格低廉、无源、低功耗等优点,能够便捷地提供大致的位置信息,目前已在后勤管理、智能物流、机器人导航等多种领域被广泛应用。由于无线信号传播中存在多径效应和噪声等不利因素的影响,现有的基于RFID的定位方法存在不足,往往难以兼顾硬件复杂度、时延和定位精度。本文面向当前日益增长的室内定位应用需求,以提高室内定位精度、降低部署复杂度为目标,研究了基于双RFID标签的室内定位技术。首先,本文提出了一种综合大小孔径的双RFID标签定位算法。本文通过实际环境中的信号采样,分析了RFID信号相位与信号传播距离的对应关系,以及信号相位进行定位所面临的实际问题。接下来,针对实际环境中信号相位校准难的问题,收集了不同位置和方向的标签数据并对相位偏移进行统计分析,设计了基于双标签的定位方案以消除随机的相位偏移。针对由相位“2π混淆”带来了信号-距离映射不唯一的问题,本文采用了基于信号到达角(Angle of Arrive,Ao A)的定位原则,并且利用不同观察孔径所具有的特性提升定位性能。具体地,本文提出利用由天线所构成的大观察孔径获得较高的定位精度,同时由双RFID标签所构成的小观察孔径消除相位混淆所造成的定位错误。本文使用商业现成RFID设备搭建了硬件实验环境。实验结果表明,本文所提出的算法能够达到厘米级的定位精度,优于其他的具有类似硬件配置的定位算法。其次,本文提出一种基于机器学习的采样信号偏差修正技术。由于无线传播环境的复杂性,RFID信号中存在一定的观测偏差,对定位精度造成不利的影响。本文通过实际数据测定了采样信号与理论信号的采样偏差,发现该偏差虽然复杂多样,难以通过数学模型进行精确描述,但存在一定的与传播环境相关的稳定特征。针对此特点,本研究提出利用神经网络学习实际应用环境中真实RFID信号采样偏差的分布,并据此对采样信号的偏差进行修正,以提升信号质量。据此,本文提出了一种基于多层感知机的采样数据偏差修正网络。实验表明,本文所提出的基于神经网络的采样数据修正方法,能够有效提升双RFID标签定位算法的性能,其中位置估计精度提升50%,方向估计精度提升12%,达到了良好的定位效果。

关键词： 数字矿山   人员安全管控   人脸识别   RFID技术   数据融合  

摘要： 矿井人员的安全保障是矿山行业的重中之重,而且下井人员的一体化全流程精准管控一直是矿山安全管理研究人员面临的主要课题。特别是在复杂环境条件下,各种风险因素错综交织给矿井人员安全带来巨大威胁,随着近年来矿山“两化深度融合”的推进,给矿山发展注入了强劲的科技力量,矿山数字化和智能化管理水平进一步提升,同时矿山安全管控在新时代下也应适应于矿山智能化水平,当前在矿井工人智能一体化安全管控推进过程中面临主要问题为:矿井人员唯一性检测方面,常用的检测设备在矿山复杂工况环境下缺乏实用性,容易受环境因素影响,出现识别率低问题;在下井过程人员管控方面,罐笼普遍存在人员超载问题,罐笼中实时人数受罐笼运行方式的制约,难以精确统计,由于受诸多条件影响,罐笼人员统计缺乏有效技术精准管控,致使人员上下井过程存在管理盲区;目前大多数矿山依靠单一井下定位考勤系统,完成员工考勤统计确定员工工作时长,易出现一人多卡,人卡不一考勤作弊情况,并且在矿山单系统单业务模式下多系统数据分离,信息孤岛突出,业务互联不足导致数据采集和处理决策过于分散,难以形成管控合力,不利于矿山数字化和智能化的发展。针对上述问题,在阅读分析大量相关文献资料基础上,本文主要研究工作阐述如下:(1)改进图像预处理算法。在矿井启用人脸识别进行人员认证管控,为解决矿山环境下突出的低质人脸图像识别问题,在充分研究相关图像增强算法及理论后,改进一种面部图像预处理增强算法,使用该算法对矿山复杂情况下的一些人员面部图像进行处理,实验结果证明其有显著的增强作用,该算法对矿山复杂环境下人脸识别的预处理研究有一定的参考价值。(2)优化设计罐笼人员检测系统。针对人员提升罐笼易出现超载罐内乘载人员情况无法精确实时获知的问题,提出一种基于RFID技术的人员检测系统,通过在各中段面增设大屏显示设备实时展示乘罐人员状态信息,以解决罐笼超载问题,并且可以减少矿工无效等待时间,提升在矿井恶劣工作环境下矿工的舒适度和安全性。(3)构建数据管控融合平台。结合矿山原有的井下人员定位系统,搭建人脸识别身份认证系统、罐笼人员检测系统,三个系统数据相融合的管控平台,统一数据格式和风格描述,通过数据集中处理和综合分析,实现协同控制业务联动,为有效解决矿山人员精准管控,优化生产组织结构提供技术支撑,解决矿山复杂环境下长期存在的下井人员的一体化全流程综合管控难题。

关键词： Service robots   Robot sensing systems   Inventory management   Fourth Industrial Revolution   Statistics   Social factors   Unmanned aerial vehicles   Radiofrequency identification   Gazebo   industry 40   inventory   KEONN   retail   RFID plugin   RFID technology   robotics   ROS   UAV  

摘要： Simulation, robotics, and Radio Frequency Identification (RFID) technology have significant roles in the new industrial revolution and their applications are key aspects of making Industry 4.0 a reality. Developing efficient use cases in Industry 4.0 almost always requires accurate simulation tools to be used in the digital world. The problem of simulating RFID readers for robotics in environments where high populations of RFID tags exist is addressed in this paper. This paper will discuss the design of an RFID system plugin based on Robot Operating System (ROS) and Gazebo simulator and the probability-based model on which the plugin is based. To assess the performance of the proposed system model, the simulation results of the designed plugin are compared with experiments. We also prove that the proposed simulator is flexible enough to be used on any robot platform, including aerial and ground robots. We show initial results of the simulation of having an Unmanned Aerial Vehicle (UAV) and a Unmanned Ground Vehicle (UGV) equipped with an RFID reader, navigating in an environment in which RFID tags have been placed. The robots will be reading tags in different map layouts using RFID antennas, with different orientations. We compare the simulation and experimental results in terms of the total unique tag readings vs. time, for various map-layouts. Finally, we show how this plugin can be used in robotics research by using it to simulate a novel, RFID-based stigmergic navigation strategy. We illustrate, the accurate navigation of the UAV using the proposed plugin.

关键词： Internet of Things   RFID passive tags   RFID reader   sniffer   higgs 4   multipath propagation   USRP   reader evaluation   tag-reader communication   retail store environment  

摘要： The development of UHF RFID technology has reached significant performance advancement in the last 20 years. Both tags and readers are now improved with better sensitivity levels providing a potential for achieving greater tag read ranges. However, the performances of the technology are also limited by complexity and electromagnetic (EM) properties of the environment in which the system operates. The aim of this contribution is to evaluate how well the state-of-the-art UHF RFID systems behave in an actual retail store environment rather than in a controlled anechoic setting. An extensive empirical study is performed and data for the performance analysis are collected from both a commercial reader and an USRP-based sniffer. It is shown that physical and MAC layer should be considered cooperatively in order to improve the overall system performance. Specifically, although the tag responsiveness depends on the products' EM properties as well as the number of products and their relative position in the basket, still the appropriate reader mode of operation can ensure a reliable and stable reading process. For the item identification and localization in the smart IoT stores, the EM properties of retail products should be taken into account in the data classification.

关键词： 结构健康监测   特征模理论   射频识别   天线传感器  

摘要： 桥梁、铁路等工程结构上的重要承载部件经常会由于结构损伤带来不可控的危险隐患,如果没有及时对这些损伤进行检测则会导致结构失效并带来严重的不可逆损失以及高昂的修复费用。尤其是这些结构中的金属部件,会在长期处于服役过程中由于环境侵蚀、承受动载荷等因素而逐渐产生裂缝。结构健康监测（Structural Health Monitoring,SHM）通过在结构关键部位安装各种传感装置对结构损伤进行定期的无损检测（Non-Destructive Testing,NDT）,是一项预防重大灾难性事故的重要措施。但传统的一些传感器由于严重依靠电缆、布局复杂、寿命较短,已不能满足结构健康监测对某些应用场景进行无源无线以及多点监测的需求。本文以SHM为研究背景,基于特征模理论（Theory of Characteristic Modes,TCM）,设计了双频窄带天线传感器以及射频识别（Radio Frequency Identification,RFID）标签天线传感器,并对这两款天线传感器检测金属裂缝的传感机理进行了研究,为天线传感器对金属裂缝进行无源无线和多点监测提供了理论支撑。研究内容具体包括:（1）分析了金属裂缝对微带贴片天线的电流分布产生的影响,推导出微带天线谐振频率的偏移可以用于表征金属裂缝大小的传感原理。针对该传感原理,设计了基于特征模理论的双频窄带天线传感器,通过仿真和实测验证了天线传感器的谐振频率对裂缝的表征性能。实测结果表明此天线传感器可以对裂缝位置方向和大小进行监测,其对水平方向裂缝宽度和深度检测灵敏度都为-21.5MHz/mm2;对竖直方向裂缝检测的深度和宽度检测灵敏度分别为-44MHz/mm2和-47.25MHz/mm2。（2）为了实现微带天线传感器的多点检测功能,设计了基于特征模理论的RFID标签天线传感器。为了让传感器拥有良好的工作效率,应用TCM确定了馈电端口的位置,并采用共轭匹配技术实现了标签芯片和标签天线的阻抗匹配,同时确定了标签天线的尺寸参数。通过仿真验证了标签天线传感器的谐振频率对金属裂缝的表征性能。仿真结果显示,此标签天线传感器可以对金属裂缝的扩展方向和大小以及对竖直方向上的天线疲劳裂纹的长度进行监测。

关键词： Radiofrequency identification   Personal protective equipment   Pandemics   Sensors   COVID-19   Monitoring   Supply chains   RFID   COVID-19   pandemic   social distancing   contact tracing   healthcare Internet of Things   personal protective equipment  

摘要： The COVID-19 pandemic drastically changed our way of living. To minimize life losses, multi-level strategies requiring collective efforts were adopted while waiting for the vaccines' rollout. The management of such complex processes has taken benefit from the rising framework of the Internet of Things (IoT), and particularly the Radiofrequency Identification (RFID) since it is probably the most suitable approach to both the micro (user) and the macro (processes) scale. Hence, a single infrastructure can support both the logistic and monitoring issues related to the war against a pandemic. Based on the COVID-19 experience, this paper is a survey on how state-of-the-art RFID systems can be employed in facing future pandemic outbreaks. The three pillars of the contrast of the pandemic are addressed: 1) use of Personal Protective Equipment (PPE), 2) access control and social distancing, and 3) early detection of symptoms. For each class, the envisaged RFID devices and procedures are discussed based on the available technology and the current worldwide research. This survey shows that RFID could generate an extraordinary amount of data so that complementary paradigms of Edge Computing and Artificial intelligence can be tightly integrated to extract profiles and identify anomalous events in compliance with privacy and security.

关键词： Belts   Radiofrequency identification   Sensors   Monitoring   Impedance   Maintenance engineering   Temperature measurement   UHF RFID sensor   conveyor belt   monitoring system   crack detection  

摘要： This paper presents the design and analysis of a novel passive Ultra High Frequency (UHF) radio frequency identification (RFID) based sensor for crack detection in coal mining conveyor belts. The proposed sensor is built on an interdigital capacitor (IDC) based resonator integrated with a commercial UHF RFID chip. The paper illustrates the theoretical sensing principles of the sensor along with its design requirements. To enable the operation of the conveyor belt sample in the UHF band, a dielectric characterization of the belt is performed. This characterization helps obtain the material parameters of the belt, such as the dielectric constant and loss tangent. A thorough analysis of the proposed sensor in terms of simulation and experiment is also exemplified in this paper. Both simulated and experimental studies cater to a robust sensor performance for detecting cracks in the conveyor belt environment. The simulated analysis illustrates the variation of different sensing parameters, including impedance, gain, and backscattered power, with respect to different crack widths, orientations, and locations. The experimental results of fabricated sensor prototypes eventually manifest the backscattered power variation of the sensor into the change of received signal strength indicator (RSSI). An extensive analysis of the experimentally obtained results demonstrates that the proposed sensor can reliably and efficiently detect the presence and growth of cracks along with their variation in widths and orientations. The validation of simulated results through experiments essentially lays the basis for adopting machine learning based crack characterization in the future.

关键词： Sensors   Radiofrequency identification   Medical services   Intelligent sensors   Temperature sensors   Sensor systems   Biomedical monitoring   Chipless radio frequency identification (RFID) sensors   healthcare   Internet of Things (IoT)   radar cross section (RCS)   wearable tag  

摘要： Currently, there is a great demand for low-cost solutions in connected healthcare and real-time wireless patient monitoring remotely. Radio frequency identification (RFID) is a rapidly emerging wireless technique for remote data capturing utilized in multifarious applications such as healthcare, automated identification, object tracking, security and authentication, food packaging, and automobile tracking. The projected cost of conventional RFID technology hampers it from being used widely. Chipless RFID sensors with the Internet of Things (IoT) technology have the full potential to meet the requirements of the growing demand. With the development of present technologies, the IoT-based solutions are no longer a challenging vision that offers various potential benefits to today's world, especially healthcare which is an encouraging field of IoT. The design and development of chipless sensors for health monitoring have gathered the attention of the researchers in last few years. This article provides a comprehensive review of chipless RFID sensors that play a vital role in cost-effective healthcare applications. The working principle of a chipless sensing system, fabrication techniques, and classifications of different chipless RFID sensors along with the smart sensing materials are highlighted. This article throws light on numerous chipless RFID sensors for IoT-based healthcare applications including their challenges and future directions. In addition to that, a comparison table of recent developments in the area of IoT-based healthcare is prepared.

关键词： 室内定位   RFID   载波相位   多目标   PSO  

摘要： 室内环境的定位服务需求日益激增,室内定位技术成为近年来的研究热点。射频识别(Radio Frequency Identification,RFID)技术在非接触式信息交互领域得到广泛应用,将RFID系统赋予高精度定位功能将大大提升RFID技术的应用场景及商业价值。RFID系统结构简单、收发同频,能消除载波频偏的影响,且其无源标签反射信号特征明显,因此可实现对无源标签的高精度定位。基于此,本文开展基于RFID载波相位的室内单站定位技术研究,搭建测试验证平台实现对多个目标的厘米级定位。本文主要研究内容如下: 首先,开展了相位误差修正及短距离场景下的单站定位算法研究。为提高定位精度,对定位平台采集数据进行误差分析,提出基于参考点的相位误差修正方法,并利用修正后的多频点相位实现高精度测距;在多重信号分类(Multiple Signal Classification,MUSIC)算法基础上,分析了因室内信号传播距离较短,导致天线阵列入射信号不平行对MUSIC算法参数估计精度的影响,提出了测距结果与MUSIC算法结合的协同坐标检索方法提升单站定位精度。 其次,提出了基于载波相位和群体智能的多目标定位算法。利用多频点载波相位计算粒子权重,通过粒子群优化(Particle Swarm Optimization,PSO)算法提高协同检索效率,并结合RFID身份识别功能实现对多个无源标签的并行定位;同时,针对PSO算法在检索时有概率陷入局部最优,以及PSO算法检索精度过于依赖粒子密度的问题,改进PSO算法,有效降低其陷入局部最优的概率,减少了粒子密度对定位精度的影响,进一步提高了算法检索效率和定位精度。 最后,使用软件定义无线电(Software Defined Radio,SDR)设备搭建RFID单站定位平台,对定位算法进行实测验证。实测结果表明,本文定位算法对5个目标的平均定位用时为2.8s,其中90%定位结果的平均绝对定位误差为6.67cm。