为提高变电站的工具管理和作业效率,提出一种基于射频识别(Radio Frequency Identification,RFID)技术的智能工具箱系统。采用超高频RFID标签、读写器、天线及数据处理单元,通过模块化设计实现工具的实时识别、状态监控和作业优化。实...为提高变电站的工具管理和作业效率,提出一种基于射频识别(Radio Frequency Identification,RFID)技术的智能工具箱系统。采用超高频RFID标签、读写器、天线及数据处理单元,通过模块化设计实现工具的实时识别、状态监控和作业优化。实验结果表明,RFID系统显著提高了工具管理的准确性,降低了工具丢失率,优化了作业流程。展开更多
利用射频识别(Radio Frequency Identification,RFID)技术对机器人轨迹进行误差测量时,因RFID相位观测值的非连续属性,导致代价函数难以求解,从而使得轨迹误差测量准确性较低。为此,开展了针对RFID智能引导下自动盘点机器人轨迹误差测...利用射频识别(Radio Frequency Identification,RFID)技术对机器人轨迹进行误差测量时,因RFID相位观测值的非连续属性,导致代价函数难以求解,从而使得轨迹误差测量准确性较低。为此,开展了针对RFID智能引导下自动盘点机器人轨迹误差测量技术的研究。在构建的RFID解缠相位-位置模型中,采用相位解缠策略对非连续的RFID相位观测值进行预处理,在包含相位偏移值和相位周期性模糊值的补偿相位辅助下,输出与空间相位值存在平行关系的连续性解缠相位值,解决了非连续属性导致的代价函数难以求解问题,进而实现对机器人位置的精准定位。在此基础上,分别计算机器人当前位置在x、y方向上的误差,并通过微分操作,输出连续的轨迹误差。在100 m×80 m的实验环境中,所提技术可以精准定位机器人位置,其在x方向轨迹误差测量偏差≤0.5 cm,y方向偏差≤0.1 cm,显著提升了轨迹误差测量的准确性与稳定性。因此,研究为RFID引导下机器人定位与轨迹精度评估提供了一种可靠的技术途径,对仓储自动化、机器人智能巡检等应用具有实际意义。展开更多
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 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.展开更多
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 su...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展开更多
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 iden...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.展开更多
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 causin...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.展开更多
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 m...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.展开更多
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 physiol...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.展开更多
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...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%.展开更多
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 Inne...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.展开更多
文摘为提高变电站的工具管理和作业效率,提出一种基于射频识别(Radio Frequency Identification,RFID)技术的智能工具箱系统。采用超高频RFID标签、读写器、天线及数据处理单元,通过模块化设计实现工具的实时识别、状态监控和作业优化。实验结果表明,RFID系统显著提高了工具管理的准确性,降低了工具丢失率,优化了作业流程。
基金supported by the Aviation Science Foundation(ASFC-20181352009).
文摘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.
基金Supported by the Project of the National "948" (2006-Z12)
文摘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
基金supported in part by the National Natural Science Foundation of China(61762093)the 17th Batch of Young and Middle-aged Leaders in Academic and Technical Reserved Talents Project of Yunnan Province(2014HB019)the Program for Innovative Research Team(in Science and Technology)in University of Yunnan Province
文摘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.
基金This work was supported in part by the National Natural Science Foundation of China under project contracts Nos.61701082,61701116,61601093,61971113 and 61901095in part by National Key R&D Program under project Nos.2018YFB1802102 and 2018AAA0103203+3 种基金in part by Guangdong Provincial Research and Development Plan in Key Areas under project contract Nos.2019B010141001 and 2019B010142001in part by Sichuan Provincial Science and Technology Planning Program under project contracts Nos.2018HH0034,2019YFG0418,2019YFG0120 and 2018JY0246in part by the fundamental research funds for the Central Universities under project contract No.ZYGX2016J004in part by Science and Technology on Electronic Information Control Laboratory.
文摘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.
基金supported by Guangdong Province Key Research and Development Project(2019B090909001)National Natural Science Foundation of China(52175236)+1 种基金the Natural Science Foundation of China(Grant 51705268)China Postdoctoral Science Foundation Funded Project(Grant 2017M612191).
文摘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.
文摘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.
基金supported by National Natural Science Foundation of China(No.62101298)Collaborative Education Project between Industry and Academia,China(22050609312501)。
文摘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%.
基金Supported by Science and Technology Project of Lightning Warning&Protection Center in Inner Mongolia,China(nmldkjcx201301)
文摘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.
