Radio Frequency Identification(RFID)technology has emerged as a promising solution for real-time tracking and monitoring in the petroleum industry.This study systematically reviews recent advancements in RFID applicat...Radio Frequency Identification(RFID)technology has emerged as a promising solution for real-time tracking and monitoring in the petroleum industry.This study systematically reviews recent advancements in RFID applications for petroleum asset management,logistics,and safety.The research is based on an extensive review of peer-reviewed literature,industry reports,and experimental case studies involving RFID deployment in refinery operations and pipeline monitoring.The study also examines practical implementation challenges,including signal interference due to metal surfaces,high initial costs associated with infrastructure setup,and integration complexities with existing digital systems such as SCADA and IoT platforms.Furthermore,issues related to data security and the potential for unauthorized access are discussed as critical concerns that need to be addressed for large-scale adoption.Despite these limitations,RFID technologydemonstrates significant potential in optimizing supply chain management,enhancing real-time asset tracking,and improving workplace safety in petroleum engineering.The ability to automate inventory management,reduce operational downtime,and enhance predictive maintenance further underscores its strategic importance.Future research should focus on overcoming technical barriers through the development of advanced RFIDtags with higher resistance to extreme environmental conditions and improved data encryption techniques.Additionally,cost-effective deployment strategies andinteroperability standards must be established to facilitate broader industry adoption.Collaborative efforts between researchers,technology developers,and industry stakeholders will be essential in driving innovation and ensuring the successful integration of RFID into the petroleum sector.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
In this paper,we present a Deep Neural Network(DNN)based framework that employs Radio Frequency(RF)hologram tensors to locate multiple Ultra-High Frequency(UHF)passive Radio-Frequency Identification(RFID)tags.The RF h...In this paper,we present a Deep Neural Network(DNN)based framework that employs Radio Frequency(RF)hologram tensors to locate multiple Ultra-High Frequency(UHF)passive Radio-Frequency Identification(RFID)tags.The RF hologram tensor exhibits a strong relationship between observation and spatial location,helping to improve the robustness to dynamic environments and equipment.Since RFID data is often marred by noise,we implement two types of deep neural network architectures to clean up the RF hologram tensor.Leveraging the spatial relationship between tags,the deep networks effectively mitigate fake peaks in the hologram tensors resulting from multipath propagation and phase wrapping.In contrast to fingerprinting-based localization systems that use deep networks as classifiers,our deep networks in the proposed framework treat the localization task as a regression problem preserving the ambiguity between fingerprints.We also present an intuitive peak finding algorithm to obtain estimated locations using the sanitized hologram tensors.The proposed framework is implemented using commodity RFID devices,and its superior performance is validated through extensive experiments.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
The objective of this work is to provide decision-making processes with an updated/real picture of the mobile resources in industrial environments through a constant feedback of information.The combination of identifi...The objective of this work is to provide decision-making processes with an updated/real picture of the mobile resources in industrial environments through a constant feedback of information.The combination of identification technologies and wireless sensor networks(WSN) is proposed as a key development to guarantee an accurate and timely supply of online information regarding the localization and tracking of the mobile wireless devices.This approach uses a cooperative and distributed localization system,called ZigID,which is a WSN based on a Zigbee network with radio frequency identification(RFID) active tags as end nodes.The WSN can recover not only the ID information stored at the tags attached to mobile resources,but also any other useful data captured by specific sensors for acceleration,temperature,humidity and fuel status.This paper also shows the development of ZigID,including devices and information flows,as well as its implementation in ground handling operations at the Ciudad Real Central Airport,Spain.展开更多
The 13.56 MHz analog front-end circuit for ISO/IEC 15693-compatible radio frequency identification (RFID) trans- ponder IC presented in this paper converts RF power to DC and extracts clock and data from the interroga...The 13.56 MHz analog front-end circuit for ISO/IEC 15693-compatible radio frequency identification (RFID) trans- ponder IC presented in this paper converts RF power to DC and extracts clock and data from the interrogator by 10% or 100% ASK modulation. The transponder sends data back to the interrogator by load modulation technology. The electrostatic discharge (ESD) protection circuits function to limit RF voltage to a safe level. An inductive coupling simulation modelling for 13.56 MHz RFID system is presented, with simulation results showing that the transponder operates over a wide range of electromagnetic field strength from Hmin (150 mA/m) to Hmax (5 A/m). The transponder IC is implemented in SMIC 0.35-μm three-metal two-poly mixed signal CMOS technology with embedded EEPROM.展开更多
Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequen...Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.展开更多
Most of the Radio Frequency IDentification (RFID) authentication protocols, proposed to preserve security and privacy, are analysed to show that they can not provide security against some passive or active attacks. In...Most of the Radio Frequency IDentification (RFID) authentication protocols, proposed to preserve security and privacy, are analysed to show that they can not provide security against some passive or active attacks. In this paper, the security of two matrix-based protocols, proposed by Karthikeyan and Nesterenko (KN protocol) and Ramachandra et al. (RRS protocol) that conform to Electronic Product Code Class-1 Generation-2 (EPC Class-1 Gen-2) standard, are investigated. Using the linear relationship of multiplication of matrix and vector, we point out that both protocols can not provide scalability, and they are vulnerable to passive impersonation attack. In addition, both protocols are totally insecure if the adversary can compromise one tag to extract the secrets. A modified lightweight matrix-based authentication protocol is presented, which can resist mainly common attacks on an RFID authentication system including eavesdropping, relay attack, desynchronization attack, impersonation attack and tag tracking attack. The new protocol also has the desirable scalability property and can keep secure under compromising attack.展开更多
In a passive ultra-high frequency(UHF)radio frequency identification(RFID)system,the recovery of collided tag signals on a physical layer can enhance identification efficiency.However,frequency drift is very common in...In a passive ultra-high frequency(UHF)radio frequency identification(RFID)system,the recovery of collided tag signals on a physical layer can enhance identification efficiency.However,frequency drift is very common in UHF RFID systems,and will have an influence on the recovery on the physical layer.To address the problem of recovery with the frequency drift,this paper adopts a radial basis function(RBF)network to separate the collision signals,and decode the signals via FM0 to recovery collided RFID tags.Numerical results show that the method in this paper has better performance of symbol error rate(SER)and separation efficiency compared to conventional methods when frequency drift occurs.展开更多
It is a challenge for passive RFID tags to be mounted on the surface of metal because the parameters of tag antennas,such as the impedance matching,the radiation efficiency and the radiation pattern,are seriously affe...It is a challenge for passive RFID tags to be mounted on the surface of metal because the parameters of tag antennas,such as the impedance matching,the radiation efficiency and the radiation pattern,are seriously affected by the metallic surface.This paper presents the characteristics of the dipole-like antennas of ultra high frequency(UHF) radio frequency identification(RFID) tags that are placed close to metallic surfaces.The finite element method(FEM) and method of moment(MoM) were used to simulate the changes of the antenna parameters near the metallic surface.Two typical dipole-like antennas close to the metallic surface,a closed loop antenna and a loaded meander antenna,were modeled,and the performance was evaluated.Experiment was carried out and the results were in good agreement with the simulation,showing that a distance of 0.05λ～0.1λ(λ is the free space wavelength) from the metallic surface could make the dipole-like UHF RFID tag performance be acceptable.展开更多
A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the per...A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the performance of binary tree algorithm (BTA). In BSBTA, the reader detects collisions by Manchester code and stores colliding prefixes in a stack. The query is composed of a two-bit prefix and an index value. Following every reader query, there are two timeslots for tags whose pointers and identities (IDs) match the query to respond, one for the tag whose next bit is 0 and the other for the tag with 1 as its next bit. Performance analysis and evaluation are also given. The time complexity and the communication complexity of BTA and BSBTA are derived. The simulation results compare the performance of BSBTA with several related anti-collision algorithms. It is shown that BSBTA outperforms BTA in terms of the average number of responded bits and timeslots for one tag identification.展开更多
In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,w...In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,which results in a collision and leads to the degrading of tags identifying efficiency.To improve the multiple tags’identifying efficiency due to collision,a physical layer network coding based binary search tree algorithm(PNBA)is proposed in this paper.PNBA pushes the conflicting signal information of multiple tags into a stack,which is discarded by the traditional anti-collision algorithm.In addition,physical layer network coding is exploited by PNBA to obtain unread tag information through the decoding operation of physical layer network coding using the conflicting information in the stack.Therefore,PNBA reduces the number of interactions between reader and tags,and improves the tags identification efficiency.Theoretical analysis and simulation results using MATLAB demonstrate that PNBA reduces the number of readings,and improve RFID identification efficiency.Especially,when the number of tags to be identified is 100,the average needed reading number of PNBA is 83%lower than the basic binary search tree algorithm,43%lower than reverse binary search tree algorithm,and its reading efficiency reaches 0.93.展开更多
Relay attack is one of the most threatening challenges against radio frequency identification（RFID） now. Distance bounding protocols have been introduced to thwart relay attacks. They form a family of challenge-resp...Relay attack is one of the most threatening challenges against radio frequency identification（RFID） now. Distance bounding protocols have been introduced to thwart relay attacks. They form a family of challenge-response authentication protocols and confirm the round-trip time at the Rapid Bit Exchange phase. They enable a reader to authenticate and to establish an upper bound on the physical distance to an entrusted tag. We design an effective attack against a family of such protocols to launch the spoofing attacks within effective distance successfully, which demonstrates that existing protocols cannot eliminate such attacks completely. The thesis proposes a new program with time- stamping verification to correct the defect and verify the effectiveness.展开更多
Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosen...Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosensory games, and human-computer interaction. However, vision-based pose tracking techniques usually raise privacy concerns, making human pose tracking without vision data usage an important problem. Thus, we propose using Radio Frequency Identification (RFID) as a pose tracking technique via a low-cost wearable sensing device. Although our prior work illustrated how deep learning could transfer RFID data into real-time human poses, generalization for different subjects remains challenging. This paper proposes a subject-adaptive technique to address this generalization problem. In the proposed system, termed Cycle-Pose, we leverage a cross-skeleton learning structure to improve the adaptability of the deep learning model to different human skeletons. Moreover, our novel cycle kinematic network is proposed for unpaired RFID and labeled pose data from different subjects. The Cycle-Pose system is implemented and evaluated by comparing its prototype with a traditional RFID pose tracking system. The experimental results demonstrate that Cycle-Pose can achieve lower estimation error and better subject generalization than the traditional system.展开更多
In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on t...In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on the passive Radio-Frequency IDentification(RFID)technology to precisely track the pose of a handheld controller,and then transfer the pose information to navigate the UAV.A prototype of the handheld controller is created by attaching three or more Ultra High Frequency(UHF)RFID tags to a board.A Commercial Off-The-Shelf(COTS)RFID reader with multiple antennas is deployed to collect the observations of the tags.First,the precise positions of all the tags can be obtained by our proposed method,which leverages a Bayesian filter and Channel State Information(CSI)phase measurements collected from the RFID reader.Second,we introduce a Singular Value Decomposition(SVD)based approach to obtain a 6-DoF(Degrees of Freedom)pose of the controller from estimated positions of the tags.Furthermore,the pose of the controller can be precisely tracked in a real-time manner,while the user moves the controller.Finally,control commands will be generated from the controller's pose and sent to the UAV for navigation.The performance of the RFHUI is evaluated by several experiments.The results show that it provides precise poses with 0.045m mean error in position and 2.5∘mean error in orientation for the controller,and enables the controller to precisely and intuitively navigate the UAV in an indoor environment.展开更多
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...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.展开更多
文摘Radio Frequency Identification(RFID)technology has emerged as a promising solution for real-time tracking and monitoring in the petroleum industry.This study systematically reviews recent advancements in RFID applications for petroleum asset management,logistics,and safety.The research is based on an extensive review of peer-reviewed literature,industry reports,and experimental case studies involving RFID deployment in refinery operations and pipeline monitoring.The study also examines practical implementation challenges,including signal interference due to metal surfaces,high initial costs associated with infrastructure setup,and integration complexities with existing digital systems such as SCADA and IoT platforms.Furthermore,issues related to data security and the potential for unauthorized access are discussed as critical concerns that need to be addressed for large-scale adoption.Despite these limitations,RFID technologydemonstrates significant potential in optimizing supply chain management,enhancing real-time asset tracking,and improving workplace safety in petroleum engineering.The ability to automate inventory management,reduce operational downtime,and enhance predictive maintenance further underscores its strategic importance.Future research should focus on overcoming technical barriers through the development of advanced RFIDtags with higher resistance to extreme environmental conditions and improved data encryption techniques.Additionally,cost-effective deployment strategies andinteroperability standards must be established to facilitate broader industry adoption.Collaborative efforts between researchers,technology developers,and industry stakeholders will be essential in driving innovation and ensuring the successful integration of RFID into the petroleum sector.
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supported in part by the U.S.National Science Foundation(NSF)under Grants ECCS-2245608 and ECCS-2245607。
文摘In this paper,we present a Deep Neural Network(DNN)based framework that employs Radio Frequency(RF)hologram tensors to locate multiple Ultra-High Frequency(UHF)passive Radio-Frequency Identification(RFID)tags.The RF hologram tensor exhibits a strong relationship between observation and spatial location,helping to improve the robustness to dynamic environments and equipment.Since RFID data is often marred by noise,we implement two types of deep neural network architectures to clean up the RF hologram tensor.Leveraging the spatial relationship between tags,the deep networks effectively mitigate fake peaks in the hologram tensors resulting from multipath propagation and phase wrapping.In contrast to fingerprinting-based localization systems that use deep networks as classifiers,our deep networks in the proposed framework treat the localization task as a regression problem preserving the ambiguity between fingerprints.We also present an intuitive peak finding algorithm to obtain estimated locations using the sanitized hologram tensors.The proposed framework is implemented using commodity RFID devices,and its superior performance is validated through extensive experiments.
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.
文摘The objective of this work is to provide decision-making processes with an updated/real picture of the mobile resources in industrial environments through a constant feedback of information.The combination of identification technologies and wireless sensor networks(WSN) is proposed as a key development to guarantee an accurate and timely supply of online information regarding the localization and tracking of the mobile wireless devices.This approach uses a cooperative and distributed localization system,called ZigID,which is a WSN based on a Zigbee network with radio frequency identification(RFID) active tags as end nodes.The WSN can recover not only the ID information stored at the tags attached to mobile resources,but also any other useful data captured by specific sensors for acceleration,temperature,humidity and fuel status.This paper also shows the development of ZigID,including devices and information flows,as well as its implementation in ground handling operations at the Ciudad Real Central Airport,Spain.
文摘The 13.56 MHz analog front-end circuit for ISO/IEC 15693-compatible radio frequency identification (RFID) trans- ponder IC presented in this paper converts RF power to DC and extracts clock and data from the interrogator by 10% or 100% ASK modulation. The transponder sends data back to the interrogator by load modulation technology. The electrostatic discharge (ESD) protection circuits function to limit RF voltage to a safe level. An inductive coupling simulation modelling for 13.56 MHz RFID system is presented, with simulation results showing that the transponder operates over a wide range of electromagnetic field strength from Hmin (150 mA/m) to Hmax (5 A/m). The transponder IC is implemented in SMIC 0.35-μm three-metal two-poly mixed signal CMOS technology with embedded EEPROM.
基金Project(2009BADB9B09)supported by the National Key Technologies R&D Program of China
文摘Warehouse operation has become a critical activity in supply chain. Position information of pallets is important in warehouse management which can enhance the efficiency of pallets picking and sortation. Radio frequency identification(RFID) has been widely used in warehouse for item identifying. Meanwhile, RFID technology also has great potential for pallets localization which is underutilized in warehouse management. RFID-based checking-in and inventory systems have been applied in warehouse management by many enterprises. Localization approach is studied, which is compatible with existing RFID checking-in and inventory systems. A novel RFID localization approach is proposed for pallets checking-in. Phase variation of nearby tags was utilized to estimate the position of added pallets. A novel inventory localization approach combing angle of arrival(AOA) measurement and received signal strength(RSS) is also proposed for pallets inventory. Experiments were carried out using standard UHF passive RFID system. Experimental results show an acceptable localization accuracy which can satisfy the requirement of warehouse management.
基金Supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)the National Natural Science Foundation of China (No.60903181)Nanjing University of Posts and Telecommunications Funds (No.NY208072)
文摘Most of the Radio Frequency IDentification (RFID) authentication protocols, proposed to preserve security and privacy, are analysed to show that they can not provide security against some passive or active attacks. In this paper, the security of two matrix-based protocols, proposed by Karthikeyan and Nesterenko (KN protocol) and Ramachandra et al. (RRS protocol) that conform to Electronic Product Code Class-1 Generation-2 (EPC Class-1 Gen-2) standard, are investigated. Using the linear relationship of multiplication of matrix and vector, we point out that both protocols can not provide scalability, and they are vulnerable to passive impersonation attack. In addition, both protocols are totally insecure if the adversary can compromise one tag to extract the secrets. A modified lightweight matrix-based authentication protocol is presented, which can resist mainly common attacks on an RFID authentication system including eavesdropping, relay attack, desynchronization attack, impersonation attack and tag tracking attack. The new protocol also has the desirable scalability property and can keep secure under compromising attack.
基金supported by the National Natural Science Foundation of China(61762093)the 17th Batches of Young and Middle-aged Leaders in Academic and Technical Reserved Talents Project of Yunnan Province(2014HB019)+1 种基金the Key Applied and Basic Research Foundation of Yunnan Province(2018FA036)the Program for Innovative Research Team(in Science and Technology)in University of Yunnan Province。
文摘In a passive ultra-high frequency(UHF)radio frequency identification(RFID)system,the recovery of collided tag signals on a physical layer can enhance identification efficiency.However,frequency drift is very common in UHF RFID systems,and will have an influence on the recovery on the physical layer.To address the problem of recovery with the frequency drift,this paper adopts a radial basis function(RBF)network to separate the collision signals,and decode the signals via FM0 to recovery collided RFID tags.Numerical results show that the method in this paper has better performance of symbol error rate(SER)and separation efficiency compared to conventional methods when frequency drift occurs.
基金Project (No.2006C12051) supported by the Science and Technology Plan of Zhejiang Province,China
文摘It is a challenge for passive RFID tags to be mounted on the surface of metal because the parameters of tag antennas,such as the impedance matching,the radiation efficiency and the radiation pattern,are seriously affected by the metallic surface.This paper presents the characteristics of the dipole-like antennas of ultra high frequency(UHF) radio frequency identification(RFID) tags that are placed close to metallic surfaces.The finite element method(FEM) and method of moment(MoM) were used to simulate the changes of the antenna parameters near the metallic surface.Two typical dipole-like antennas close to the metallic surface,a closed loop antenna and a loaded meander antenna,were modeled,and the performance was evaluated.Experiment was carried out and the results were in good agreement with the simulation,showing that a distance of 0.05λ～0.1λ(λ is the free space wavelength) from the metallic surface could make the dipole-like UHF RFID tag performance be acceptable.
基金the National Natural Science Foundation of China (No. 61071078)
文摘A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the performance of binary tree algorithm (BTA). In BSBTA, the reader detects collisions by Manchester code and stores colliding prefixes in a stack. The query is composed of a two-bit prefix and an index value. Following every reader query, there are two timeslots for tags whose pointers and identities (IDs) match the query to respond, one for the tag whose next bit is 0 and the other for the tag with 1 as its next bit. Performance analysis and evaluation are also given. The time complexity and the communication complexity of BTA and BSBTA are derived. The simulation results compare the performance of BSBTA with several related anti-collision algorithms. It is shown that BSBTA outperforms BTA in terms of the average number of responded bits and timeslots for one tag identification.
基金the National Natural Science Foundation of China under Grant 61502411Natural Science Foundation of Jiangsu Province under Grant BK20150432 and BK20151299+7 种基金Natural Science Research Project for Universities of Jiangsu Province under Grant 15KJB520034China Postdoctoral Science Foundation under Grant 2015M581843Jiangsu Provincial Qinglan ProjectTeachers Overseas Study Program of Yancheng Institute of TechnologyJiangsu Provincial Government Scholarship for Overseas StudiesTalents Project of Yancheng Institute of Technology under Grant KJC2014038“2311”Talent Project of Yancheng Institute of TechnologyOpen Fund of Modern Agricultural Resources Intelligent Management and Application Laboratory of Huzhou Normal University.
文摘In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,which results in a collision and leads to the degrading of tags identifying efficiency.To improve the multiple tags’identifying efficiency due to collision,a physical layer network coding based binary search tree algorithm(PNBA)is proposed in this paper.PNBA pushes the conflicting signal information of multiple tags into a stack,which is discarded by the traditional anti-collision algorithm.In addition,physical layer network coding is exploited by PNBA to obtain unread tag information through the decoding operation of physical layer network coding using the conflicting information in the stack.Therefore,PNBA reduces the number of interactions between reader and tags,and improves the tags identification efficiency.Theoretical analysis and simulation results using MATLAB demonstrate that PNBA reduces the number of readings,and improve RFID identification efficiency.Especially,when the number of tags to be identified is 100,the average needed reading number of PNBA is 83%lower than the basic binary search tree algorithm,43%lower than reverse binary search tree algorithm,and its reading efficiency reaches 0.93.
基金Supported by the National Natural Science Foundation of China(61332019)
文摘Relay attack is one of the most threatening challenges against radio frequency identification（RFID） now. Distance bounding protocols have been introduced to thwart relay attacks. They form a family of challenge-response authentication protocols and confirm the round-trip time at the Rapid Bit Exchange phase. They enable a reader to authenticate and to establish an upper bound on the physical distance to an entrusted tag. We design an effective attack against a family of such protocols to launch the spoofing attacks within effective distance successfully, which demonstrates that existing protocols cannot eliminate such attacks completely. The thesis proposes a new program with time- stamping verification to correct the defect and verify the effectiveness.
基金supported in part by the US National Science Foundation(NSF)under Grants ECCS-1923163 and CNS-2107190through the Wireless Engineering Research and Education Center at Auburn University.
文摘Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosensory games, and human-computer interaction. However, vision-based pose tracking techniques usually raise privacy concerns, making human pose tracking without vision data usage an important problem. Thus, we propose using Radio Frequency Identification (RFID) as a pose tracking technique via a low-cost wearable sensing device. Although our prior work illustrated how deep learning could transfer RFID data into real-time human poses, generalization for different subjects remains challenging. This paper proposes a subject-adaptive technique to address this generalization problem. In the proposed system, termed Cycle-Pose, we leverage a cross-skeleton learning structure to improve the adaptability of the deep learning model to different human skeletons. Moreover, our novel cycle kinematic network is proposed for unpaired RFID and labeled pose data from different subjects. The Cycle-Pose system is implemented and evaluated by comparing its prototype with a traditional RFID pose tracking system. The experimental results demonstrate that Cycle-Pose can achieve lower estimation error and better subject generalization than the traditional system.
文摘In this paper,we present an RFID based human and Unmanned Aerial Vehicle(UAV)Interaction system,termed RFHUI,to provide an intuitive and easy-to-operate method to navigate a UAV in an indoor environment.It relies on the passive Radio-Frequency IDentification(RFID)technology to precisely track the pose of a handheld controller,and then transfer the pose information to navigate the UAV.A prototype of the handheld controller is created by attaching three or more Ultra High Frequency(UHF)RFID tags to a board.A Commercial Off-The-Shelf(COTS)RFID reader with multiple antennas is deployed to collect the observations of the tags.First,the precise positions of all the tags can be obtained by our proposed method,which leverages a Bayesian filter and Channel State Information(CSI)phase measurements collected from the RFID reader.Second,we introduce a Singular Value Decomposition(SVD)based approach to obtain a 6-DoF(Degrees of Freedom)pose of the controller from estimated positions of the tags.Furthermore,the pose of the controller can be precisely tracked in a real-time manner,while the user moves the controller.Finally,control commands will be generated from the controller's pose and sent to the UAV for navigation.The performance of the RFHUI is evaluated by several experiments.The results show that it provides precise poses with 0.045m mean error in position and 2.5∘mean error in orientation for the controller,and enables the controller to precisely and intuitively navigate the UAV in an indoor environment.
基金This work was supported by Taif University Researchers Supporting Project(TURSP)under number(TURSP-2020/10),Taif University,Taif,Saudi Arabia.
文摘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.
