Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

Application of Radio Frequency Identification (RFID) in Dairy Information Management

As a kind of brand-new technology, radio frequency identification management, data control and acquisition. This paper introduced food safety system construction, analyzed the advantages and problems in dairy modem suggestions for solution according to the practical situation. （RFID） plays an important role in dairy information tracing and culture function extension of managing breeding technology, and finally put forward some

Capture-aware Bayesian RFID Tag Estimate for Large-scale Identification

Dynamic framed slotted Aloha algorithm is one of popular passive radio frequency identification(RFID) tag anticollision algorithms. In the algorithm, a frame length requires dynamical adjustment to achieve higher identification efficiency.Generally, the adjustment of the frame length is not only related to the number of tags, but also to the occurrence probability of capture effect. Existing algorithms could estimate both the number of tags and the probability of capture effect. Under large-scale RFID tag identification, however, the number of tags would be much larger than an initial frame length. In this scenario, the existing algorithm's estimation errors would substantially increase. In this paper, we propose a novel algorithm called capture-aware Bayesian estimate, which adopts Bayesian rules to accurately estimate the number and the probability simultaneously. From numerical results, the proposed algorithm adapts well to the large-scale RFID tag identification. It has lower estimation errors than the existing algorithms. Further,the identification efficiency from the proposed estimate is also higher than the existing algorithms.

A Cross Layer Protocol for Fast Identification of Blocked Tags in Large-Scale RFID Systems

Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causing a collision of message replies.In many practical scenarios,the number of blocked tags may vary,or even be small.For example,the attacker may only block the important customers or high-value items.To avoid the disclosure of privacy and economic losses,it is of great importance to fast pinpoint these blocked ones.However,existing works do not take into account the impact of the number of blocked tags on the execution time and suffer from incomplete identification of blocked tags,long identification time or privacy leakage.To overcome these limits,we propose a cross layer blocked tag identification protocol(CLBI).CLBI consists of multiple rounds,in which it enables multiple unblocked tags to select one time slot and concurrently verify them by using tag estimation in physical layer.Benefiting from the utilization of most collision slots,the execution time can be greatly reduced.Furthermore,for efficient identification of blocked tags under different proportions,we propose a hybrid protocol named adaptive cross layer blocked tag identification protocol(A-CLBI),which estimates the remaining blocked tag in each round and adjusts the identification strategy accordingly.Extensive simulations show that our protocol outperforms state-of-the-art blocked tags identification protocol.

基于RFID的笼内小鼠定位跟踪系统设计

常见的定位技术用于笼内小鼠跟踪准确度不高。为提高笼内小鼠定位准确性,提出了一种基于射频识别(RFID)技术的笼内小鼠定位跟踪和行为分析系统,通过放置在饲养笼下方的RFID读写器天线阵列板实现定位跟踪,上位机软件可实时显示小鼠的活动轨迹图以便科研人员对小鼠进行行为分析。通过模拟实验和生物实验,该系统可准确定位4×6阵列中小鼠位置,定位准确率可达95%以上,其中,组成阵列的单元格尺寸仅为45 mm×45 mm。

Dynamically Enlarge and Shrink Power Coverage to Speed Up Tag Identification in an RFID System

In this paper, we present a power adjustment scheme to dynamically enlarge and shrink power coverage to speed up tag identification in an RFID system. By dividing a TDMA frame into time slots, the proposed power adjustment scheme can adaptively increase or decrease the transmission power of a reader. Specifically, due to the contention for a TDMA slot from numerous tags, three states of a slot could exist;they are respectively referred to as successful, collided, and idle states. An adjustment factor based on the three states is designed to dynamically adjust the transmission power of a reader. The design of the adjustment factor considers two different aspects. When the number of idle state far exceeds the number of collided state, the first aspect will enlarge the power such that more tags within the coverage can be concurrently identified. On the other hand, when the number of idle state is much smaller than the number of collided state, the second aspect will shrink the power such that the number of tags within the coverage is significantly reduced. The proposed power adjustment scheme is simulated using NS-3. In the simulation, we design three different topologies which place tags in three distributions, uniform, random, and hotspot. From the simulation results, we demonstrate that the proposed power adjustment scheme can speed up the tag identification and save energy consumption, particularly when a large number of tags are placed in hotspot distribution.

基于RFID的人体姿态识别方法研究

人体姿态感知是未来智能护理场景的主要挑战之一。然而,视觉技术会涉及遮挡、光线条件、侵犯隐私等问题;可穿戴运动跟踪设备会增加人体负担,降低舒适性。针对以上问题,提出了一种基于射频识别(RFID)的方法进行全肢体姿态估计,能够有效克服遮挡、穿戴舒适性差等问题。首先基于相位差信息提出了一种细粒度肢体运动模型,通过构建似然函数来进行人体关节角度估计;引入正运动学构建多肢体联合运动模型,结合双天线融合算法进行三维关节角度估计;最后结合人体骨骼模型与肢体关节角度来重建人体姿态。实验结果以Kinect 2.0为标准,测得的四肢平均关节角度误差约为6°,平均关节位置误差约为4cm,表明该系统可以有效地实时监测全肢体姿态。

基于切比雪夫混沌映射和PUF的RFID三方认证协议

针对射频识别(RFID)三方认证协议存在的安全需求和资源开销的平衡问题,利用切比雪夫多项式的半群性质以及混沌性质提出了一个基于切比雪夫混沌映射和物理不可克隆函数(PUF)的RFID三方认证协议:使用切比雪夫混沌映射来实现标签、阅读器和服务器三方共享秘密;使用随机数实现协议每轮会话的新鲜性以抵抗重放攻击,同时也实现了阅读器与标签的匿名性;使用PUF函数实现标签本身的安全认证以及抵抗物理克隆攻击。安全分析表明,该协议能有效抵抗追踪、重放、物理克隆和去同步攻击等多种恶意攻击,使用BAN逻辑分析方法和Scyther工具验证了其安全性。与近期协议对比分析表明,该协议弥补了同类RFID协议的安全缺陷,在满足各种安全属性需求的同时尽量平衡硬件开销,契合了RFID硬件资源受限的处境,适用于RFID三方认证场景。

RFID射频技术在物流教学中的运用

RFID射频技术在物流教学中的运用正逐渐受到广泛关注和研究。其作为一种自动识别和追踪技术,具有高效、精确、实时等特点,为物流管理提供了全新的解决方案。在物流教学中引入RFID射频技术可以帮助学生更好地了解与应用物流管理的知识和技术。因此,文章针对RFID射频技术在物流教学中的应用展开研究,以期在教学内容、教学方法和教学模式改革等方面为相关人员提供参考。

RFID 技术在实验室信息化管理中的运用分析

实验室是衡量高校实验教学水平的关键,也是培养学生综合素质和创新能力的重要场所。随着教学任务的不断增加和实验设备的更新升级,对实验室教学和管理提出了更高的要求。基于无线射频识别(Radio Frequency Identification,RFID)技术的设备管理系统,利用无源标签、门禁设备以及手持读写器构建硬件系统,借助数据库构建软件系统,旨在通过管理系统的构建提升设备管理的效率,为实验室信息化管理水平的提升奠定坚实的基础。

RFID技术在通信数据安全传输中的应用研究

射频识别(Radio Frequency Identification,RFID)技术作为一种无线通信技术,通过无线电波实现数据的自动识别和跟踪,已广泛应用于商品管理、供应链管理以及门禁控制等领域。随着技术的普及和应用范围的扩大,如何借助RFID技术提升通信数据传输的安全性,防止数据泄露、篡改或非法访问,已成为一个急需解决的问题。文章主要介绍RFID技术的基本原理和不同类型的RFID系统,明确通信数据安全传输的基本要求,包括数据的完整性、机密性以及安全认证等方面。深入探讨RFID技术在通信数据安全传输中的具体应用,包括RFID系统的安全架构设计、加密算法的选择与应用以及认证过程与协议制定,通过采取相应的安全措施,有效提升RFID系统在数据传输过程中的安全性。

基于RFID管理实验室设备实施的关键问题研究

随着高校仪器设备数量的不断增加,智能、高效、数字化、网络化的管理实验室和实验设备已经成为现代化高校的发展趋势。主要考虑使用射频识别(RFID)技术来管理实验设备,实现对仪器设备的批量识别,更加智能高效地管理实验室。重点分析了实施过程中的几个关键技术问题:距离和频率的选择、有源/无源标签的选择、天线的选择、仪器为金属材质的问题、标签冲突防碰撞问题和价钱费用问题,以及附加定位问题等,为高校引入RFID技术管理实验室设备提供了关键技术选择、技术分析和应用。

植入安全工器具RFID标签的无线性能测试分析

电力安全工器具植入射频识别(RFID)标签后具有无线通信、定位、感知、数据交互、工作票联动等功能。针对RFID标签植入工器具后无线通信性能将受工器具材质等因素的影响而下降开展研究:首先,分析了RFID的传输特性与主要性能指标;然后,采用HFSS电磁仿真软件建立植入工器具RFID标签的仿真模型,研究植入深度与材料的介电常数对RFID标签信号传输性能的影响;最后,搭建RFID性能测试平台,测试不同介电常数与植入深度的读取距离以及输入匹配参数和谐振频率,并对不同测试距离的信噪比和接收信号强度指示(RSSI)进行测试。研究表明,RFID标签的植入深度与材质的介电常数将影响RFID的性能,植入工器具的RFID芯片传输距离将减小。

基于反射信号特征的RFID标签和移动终端跨域互联方法

随着物联网、人工智能等技术的飞速发展,基于物联网的“人-机-物”智能感知识别技术成为当前研究的热点方向。在众多的感知识别技术中,射频识别技术(Radio Frequency Identification, RFID)作为物联网的核心技术之一,被广泛应用在物流追踪、身份认证和室内定位等各个领域。由于目前广泛使用的个人移动设备并不支持RFID信息读取,限制了RFID技术的大范围应用。针对智能手机不能直接读取RFID标签信息的问题,提出一种利用用户预定义的基于RFID反射信号的手势特征实现面向智能手机和RFID标签之间的跨域互联方法。该方法不需要对部署的RFID系统或智能手机进行任何硬件修改,通过用户在感兴趣标签面前做出手势而产生的RFID相位特征,并与智能手机捕获到的运动传感器数据的相关时间戳进行匹配,从而实现了智能手机与RFID标签的关联配对。最后,通过实验验证了文中提出的跨域互联方法的可行性。

模糊贴近度在RFID定位系统中的应用

针对LANDMARC室内定位系统的缺点,提出一种基于模糊最大最小贴近度的射频识别(RFID)室内定位系统.该定位系统将参考标签划分成四个正方形区域,先通过阅读器与定位标签的能量等级确定目标标签所属的正方形区域,再计算目标标签与该区域内的参考标签的模糊贴近度.实验表明,相比于经典的LANDMARC定位系统,该定位系统具有较好的定位精度,所提定位系统可以有效地避开不相关区域阅读器与参考标签对定位的影响.

基于RFID技术的图书馆自助服务系统设计

设计一种基于射频识别(Radio Frequency Identification,RFID)技术的图书馆自助服务系统,以提高图书馆的运作效率和用户体验,实现图书借阅、归还和定位等功能的自动化处理。采用RFID技术作为核心技术,通过将RFID标签粘贴在每本图书上,并在图书馆各个关键位置安装RFID读写器,实现对图书的无线识别和追踪。经过实际测试和数据分析得出,基于RFID技术的图书馆自助服务系统能够大幅提升图书馆的运作效率和用户体验,自助借阅和归还的速度更快,减少了等待时间。

大规模RFID系统中未知标签的快速可靠识别

未知标签的存在可能会给供应链系统、仓储管理等带来不可忽略的经济损失或安全隐患,因此未知标签的识别研究对射频识别系统意义重大。为减少冲突时隙的比例,传统协议通常需要设置较大的帧长,导致对未知标签识别效率较低,且协议中大多存在冲突时隙被直接废弃、时隙利用率低的问题。提出冲突分解法(CRM)协议,通过把大部分的冲突时隙转变为有用时隙,将没有未知标签参与的冲突时隙内已知标签灭活,对有未知标签参与的冲突时隙进行区分码的解缠绕,以提取并识别冲突时隙中的未知标签。通过优化帧长设置,提高时隙利用率,增大已知标签的灭活效率及未知标签的识别效率。实验结果表明,CRM协议对未知标签的识别效率分别可达到UTI-SBF、HUTI、PTI、FUTI协议的2.5、2.2、1.4、1.5倍。

Automated Identification Algorithm Using CNN for Computer Vision in Smart Refrigerators

Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications.In particular the need for automating the process of real-time food item identification,there is a huge surge of research so as to make smarter refrigerators.According to a survey by the Food and Agriculture Organization of the United Nations(FAO),it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself.Smart refrigerators have been very successful in playing a pivotal role in mitigating this problem of food wastage.But a major issue is the high cost of available smart refrigerators and the lack of accurate design algorithms which can help achieve computer vision in any ordinary refrigerator.To address these issues,this work proposes an automated identification algorithm for computer vision in smart refrigerators using InceptionV3 and MobileNet Convolutional Neural Network(CNN)architectures.The designed module and algorithm have been elaborated in detail and are considerably evaluated for its accuracy using test images on standard fruits and vegetable datasets.A total of eight test cases are considered with accuracy and training time as the performance metric.In the end,real-time testing results are also presented which validates the system’s performance.

面向RFID的轻量级双向认证协议

为了提高无线射频识别(RFID)系统执行身份认证的效率和解决通信双方身份隐私保护问题,提出一种新的轻量级RFID双向认证协议,该协议主要采用ECC密码算法和Hash函数。基于Hash函数、ECC密码算法与或运算,使用随机数生成器生成不可预测的消息认证码以保障双向认证时传输消息的新鲜性;通过椭圆曲线加密算法隐藏通信双方的真实身份,基于ECDLP(椭圆曲线离散对数问题)困难问题,在保证身份隐私的前提下,采用两轮消息交互的模式让通信双方相互验证新鲜的消息认证码来实现协议的双向认证;通过指定密钥种子协商出标签和服务器的共享会话密钥,并设计密钥自动更新机制以实现双方的密钥同步。与部分典型的双向认证协议进行分析对比,所提出的双向认证协议相较同类的双向认证协议最多节省近40%的计算时间和25%的存储空间,并且能够支持多种安全需求和抵抗不同的恶意攻击。

《血站合格血液储存库射频识别(RFID)技术应用规范》地方标准编制研究

血液储存精细化管理是血液质量与安全的保障。苏州市中心血站编制了《血站合格血液储存库射频识别(RFID)技术应用规范》地方标准,规范了血站合格血液储存库射频识别(RFID)技术应用过程中的应用模型、RFID电子标签的要求、RFID读写设备的要求、信息系统的功能要求、典型应用场景以及异常情况预防与处理等内容,保障临床用血安全,促进无偿献血事业高质量发展。