养殖RFID测温定位电子耳标研究——基于智慧农业区块链

首先,介绍了区块链和物联网技术在智慧农业应用的概念;然后,基于结构、温度传感器、RSSI定位和天线等多个模块实现了对测温定位电子耳标的设计;最后,为了验证该RFID测温定位电子耳标的性能,设计了一套放养羊群的养殖信息监测系统,对每只羊的实际位置和体温进行监测。测试结果表明:系统可以准确测量山羊的体温和位置,响应快,稳定性高,符合设计需求。

System error iterative identification for underwater positioning based on spectral clustering

The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by considering the underwater tar-get as a mass point,as well as the observation system error,the traditional error model best estimation trajectory(EMBET)with little observed data and too many parameters can lead to the ill-condition of the parameter model.In this paper,a multi-station fusion system error model based on the optimal polynomial con-straint is constructed,and the corresponding observation sys-tem error identification based on improved spectral clustering is designed.Firstly,the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization.Then a multi-sta-tion non-oriented graph network is established,which can address the problem of the inaccurate identification for the sys-tem errors.Moreover,the similarity matrix of the spectral cluster-ing is improved,and the iterative identification for the system errors based on the improved spectral clustering is proposed.Finally,the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accu-rately identify the system errors,and moreover can improve the positioning accuracy for the underwater target positioning.

Improved adaptive genetic algorithm based RFID positioning

The existing active tag-based radio frequency identi-fication(RFID)localization techniques show low accuracy in practical applications.To address such problems,we propose a chaotic adaptive genetic algorithm to align the passive tag ar-rays.We use chaotic sequences to generate the intersection points,the weakest single point intersection is used to ensure the convergence accuracy of the algorithm while avoiding the optimization jitter problem.Meanwhile,to avoid the problem of slow convergence and immature convergence of the algorithm caused by the weakening of individual competition at a later stage,we use adaptive rate of change to improve the optimiza-tion efficiency.In addition,to remove signal noise and outliers,we preprocess the data using Gaussian filtering.Experimental results demonstrate that the proposed algorithm achieves high-er localization accuracy and improves the convergence speed.

基于单天线视轴信号传播模型的RFID定位方法

为了解决现有单天线超高频RFID技术在室内静态目标定位中精度不高的问题,本文提出了一种基于天线视轴信号传播模型的RFID定位新方法。该方法首先通过天线纵向扫描确定目标的高度位置;其次,调整天线高度与目标高度一致,然后步进旋转扫描以识别目标的方向角;进一步的,利用麻雀搜索算法优化的反向传播神经网络建立路径损耗模型并用于测距;最后,综合高度、方向角和距离数据完成目标的定位。实验结果表明,在室内环境测试中,所提出的方法平均定位误差为7.2 cm,能够满足一般室内场景下物品的定位需求。

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

基于无源超高频RFID的农产品包装智能定位方法

射频识别(radio frequency identification,RFID)技术为工业物联网(industrial internet of things)带来了巨大的进步,作为实现智能仓储的关键技术之一,广泛应用于库存管理和智能定位等场景,然而现有的绝对/相对定位方法易受仓储环境、包装材料、货架材质等因素影响。为了进一步提升室内定位精度,该研究提出了一种基于接收信号强度指示器(receive signal strength indicator,RSSI)和测量相位融合的无源RFID定位方法(RFID positioning based on received signal strength indicator and phase measurement,RP-RaP)。首先,使用MATLAB软件进行仿真模拟,在已知测量相位统计学分布的前提下,采用最大似然估计法对标签进行水平定位,同时基于双天线阅读器所测得的RSSI差值对标签进行垂直定位,实现了无源超高频RFID标签的水平和垂直定位仿真。其次,以农产品包装场景为例,在仓库中搭建射频定位测试系统,通过滑轨搭载射频阅读器及天线,对货架物品上的贴附标签进行水平和垂直定位分析,最后将无源标签分别贴附于金属盒、油桶、纸箱、面粉袋和大米袋,并以未贴附标签的测量结果作为对比。试验结果表明,与传统的室内定位算法LANDMARC相比,RP-RaP定位精度明显提升,平均水平和垂直定位精度分别达到94.6%和94.3%,基于接收信号强度指示器和测量相位融合的定位方法有效提升了农产品包装定位精度。研究结果可为大型农产品仓储智能化管理与应用提供参考。

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.

Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

Electric vehicle charging identification and positioning is critically important to achieving automatic charging.In terms of the problem of automatic charging for electric vehicles,a dual recognition and positioning method based on deep learning is proposed.The method is divided into two parts:global recognition and localization and local recognition and localization.In the specific implementation process,the collected pictures of electric vehicle charging attitude are classified and labeled.It is trained with the improved YOLOv4 networkmodel and the corresponding detectionmodel is obtained.The contour of the electric vehicle is extracted by the BiSeNet semantic segmentation algorithm.The minimum external rectangle is used for positioning of the electric vehicle.Based on the location relationship between the charging port and the electric vehicle,the rough location information of the charging port is obtained.The automatic charging equipment moves to the vicinity of the charging port,and the camera near the charging gun collects pictures of the charging port.The model is detected by the Hough circle,the KM algorithmis used for featurematching,and the homography matrix is used to solve the attitude.The results show that the dual identification and location method based on the improved YOLOv4 algorithm proposed in this paper can accurately locate the charging port.The accuracy of the charging connection can reach 80%.It provides an effective way to solve the problems of automatic charging identification and positioning of electric vehicles and has strong engineering practical value.

RFID Positioning and Physiological Signals for Remote Medical Care

The safety of patients and the quality of medical care provided to them are vital for their wellbeing.This study establishes a set of RFID(Radio Fre-quency Identification)-based systems of patient care based on physiological sig-nals in the pursuit of a remote medical care system.The RFID-based positioning system allows medical staff to continuously observe the patient's health and location.The staff can thus respond to medical emergencies in time and appropriately care for the patient.When the COVID-19 pandemic broke out,the proposed system was used to provide timely information on the location and body temperature of patients who had been screened for the disease.The results of experiments and comparative analyses show that the proposed system is superior to competing systems in use.The use of remote monitoring technology makes user interface easier to provide high-quality medical services to remote areas with sparse populations,and enables better care of the elderly and patients with mobility issues.It can be found from the experiments of this research that the accuracy of the position sensor and the ability of package delivery are the best among the other related studies.The presentation of the graphical interface is also the most cordial among human-computer interaction and the operation is simple and clear.

High-Accuracy NLOS Identification Based on Random Forest and High-Precision Positioning on 60 GHz Millimeter Wave

60 GHz millimeter wave(mmWave)system provides extremely high time resolution and multipath components(MPC)separation and has great potential to achieve high precision in the indoor positioning.However,the ranging data is often contaminated by non-line-of-sight(NLOS)transmission.First,six features of 60GHz mm Wave signal under LOS and NLOS conditions are evaluated.Next,a classifier constructed by random forest(RF)algorithm is used to identify line-of-sight(LOS)or NLOS channel.The identification mechanism has excellent generalization performance and the classification accuracy is over 97%.Finally,based on the identification results,a residual weighted least squares positioning method is proposed.All ranging information including that under NLOS channels is fully utilized,positioning failure caused by insufficient LOS links can be avoided.Compared with the conventional least squares approach,the positioning error of the proposed algorithm is reduced by 49%.

Application of Lightning Monitoring and Positioning Data in Investigation and Identification of Lightning Disaster in Inner Mongolia

The lightning current magnitude and other characteristics are important basic data of the lightning disaster investigation and identification. The characteristics of lightning monitoring and positioning system in Inner Mongolia were introduced and studied in the lightning accident analysis based on the lightning monitoring and positioning data of the lightning stroke accidents. The positioning error of lightning monitoring and positioning system was analyzed. The results showed that lightning current intensity and the position precision were very important data in the lightning disaster investigation. Finally, a variety of meteorological data should be applied in the lightning disaster investigation and identification.

基于RFID技术的公共交通自动到站播报系统设计

随着城市公共交通的迅速发展,如何提升乘客乘车的体验与提高交通系统的管理效率变得愈发重要。本文研究基于射频识别技术(RFID),设计智能化的公共交通自动到站播报系统,经过需求分析、架构设计及硬件和软件实现等步骤,助力创建出一个高效可靠的自动到站播报系统。该系统能够准确实时定位车辆并触发到站播报,让乘客出行变得更加便捷,并有利于将整个公共交通体系推向更高程度的智能化阶段。

RFID技术在食品智能包装和供应链追溯中的应用研究

目的介绍RFID技术,综述其在智能包装、食品供应链追溯的应用进展,以期为RFID技术的发展提供一定的理论基础。方法阐述RFID系统的组成、分类、工作原理及该技术的优点;分析RFID技术在监测食品包装内温度、湿度、pH、气体含量等参数的应用潜力;综述RFID技术在整个食品供应链(生产、加工、储运和销售环节)中的追溯进展;讨论目前RFID技术在实际应用中面临的问题和今后的发展方向。结论通过全面综述RFID技术在智能包装、食品溯源等方面的应用,表明RFID技术在食品领域具有广泛的应用前景,这对食品质量控制具有重要的意义。

Vehicle Positioning Method Based on RFID in Vehicular Ad-Hoc Networks

With the rapid development of vehicular ad hoc network( VANET) technology,VANET applications such as safe driving and emergency rescue demand high position accuracy,but traditional GPS is difficult to meet new accuracy requirements. To overcome this limitation,a new vehicle positioning method based on radio frequency identification( RFID) is proposed. First RFID base stations are divided into three categories using fuzzy technology,and then Chan algorithm is used to calculate three vehicles' positions,which are weighed to acquire vehicles' accurate position. This method can effectively overcome the problem that vehicle positioning accuracy is not high resulting from the factors such as ambient noise and base distribution when Chan algorithm is used. Experimental results show that the performance of the proposed method is superior to Chan algorithm and 2-step algorithm based on averaging method,which can satisfy the requirements of vehicle positioning in VANETs.

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.

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.

基于RFID的铁路巡检人员定位系统研究

分析当前铁路列车巡检人员现状及发展趋势,设计了一种基于RFID技术的铁路列车检修人员定位装置。系统以STM32F103C8T6为控制核心,利用型号为nRF24LE1的RFID无限射频芯片进行巡检人员电子标签信息的收发,主控模块根据TOA(Time of Arriving)定位算法计算出标签的位置信息,利用均值滤波算法进行位置信息的校正处理,采用无线通信GPRS模块将巡检人员的位置信息实时传送到调度中心。该系统可实现完整的巡检人员智能定位,有效提升铁路列车运维效率。

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。