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关键词： Wireless communication   Resistance   Privacy   Protocols   Authentication   Communication channels   Security  

摘要： As open and wireless RFID air interfaces suffer from severe threats, concerns with respect to the security and privacy problems are increasingly becoming noteworthy issues. The paper proposes an ultralightweight RFID authentication protocol based on Random partition (RPAP) to achieve security and efficiency. The protocol adopts multiple mechanisms (i.e. random partition, dynamic update, and mutual authentication) as safeguards in the air interface. Specifically, random partition mechanism is used to divide the pseudorandom identifier and pre-shared secret value for bitwise operations; dynamic update mechanism enhances the freshness during identifications; double-entity-round mutual authentication mechanism provides stratified access control. Meanwhile, attack models are established to analyze the resistance to typical attacks (i.e. replay, spoofing, tracking, and tampering) in the primary and further authentication. Furthermore, security and performance are analyzed to prove that the protocol owns high security, high efficiency, and low complexity. The protocol is practical for the low-cost and resource-limited RFID applications.

关键词： Location awareness   Data models   Radiofrequency identification  

摘要： We analyzed the relationship between the nearest neighbor algorithm and the arrangement of reference tags used in LANDMARC, and propose an isosceles triangular placement of reference tags. Results of simulations and experiments reveal that the precision of indoor localization can be improved by using isosceles triangular arrangement from 9.1% to 14.2% over square arrangement without data pre-processing.

关键词： Breast cancer   Non-palpable lesions   Patients comfort   Wireless breast localization   Radio-frequency tags  

摘要： Background Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death in women. Approximately 50% of breast cancers are discovered at an early stage in patients for whom conservative surgery is indicated. Intraoperative localization of non-palpable breast lesions is generally accomplished using a hook wire to mark the area of concern under ultrasound or stereotactic localization. But this technique has several drawbacks (painful, stressful horizontal ellipsis ). We propose the use of a wire-free breast lesion system using miniature radiofrequency identification (RFID) tags. This technique could improve patient comfort and surgical comfort for surgeons. We therefore propose a study to assess the interest of introducing the RFID localization technique at the Jean PERRIN comprehensive cancer *** This is a single-center prospective trial designed to assess the interest in introducing the RFID localization technique at the Jean Perrin center. It aims to show the superiority of the RFID technique in terms of patient tolerance compared to the gold-standard (hook wire). A sequential inclusion in time will be performed: 20 inclusions in the gold-standard group, then 20 patients in the RFID group before repeating the inclusion scheme. Any patient requiring preoperative localization will receive a senology consultation. The RFID tag will be placed during this consultation. The hook wire localization will be done the day before the surgery. Patients will fill out a Hospital Anxiety and Depression scale (HAD) questionnaire at the time of inclusion. They will then fill out a satisfaction questionnaire in 2 steps: during the placement of the device (RFID tag or hook wire) or during the postoperative consultation at 1 month. Radiologists and surgeons will fill out a questionnaire to evaluate the localization technique, respectively after the localization and surgery *** The RFID study is the first study in France which s

关键词： Radiofrequency identification   Holography   Synthetic aperture radar  

摘要： Presents corrections to the paper, Crucial or Unnecessary? Analysis on Phase Differential in Holographic SAR RFID Localization.

关键词： E-logistics   exploration   inventory robots   navigation   radio frequency identification (RFID)  

摘要： Inventory robots produce accurate results while reducing costs. Such robots are specialized in navigating around store/warehouse facilities while reading radio frequency identification (RFID) tags. However, commercial stores pose a serious challenge to navigation capabilities since these scenarios are likely to be modified relatively frequently. Current solutions involve having to remap the modified layout and redesign the robots' routes. This means that a human operator must direct the robot through the target area, reducing the autonomy and scalability of these solutions. The main goals of this article are: first, assessing the feasibility of RFID-based exploration to enable autonomous mapping of inventory environments, and second, comparing the classical robotic navigation based on waypoints to the RFID-based navigation strategy. It will be shown that RFID-based strategies can be used to successfully build maps autonomously and obtain similar inventory accuracies when compared to the current nonautonomous strategies.

关键词： Backscatter communication   common-off-the-shelf (COTS)   phase evaluation   radio-frequency identification (RFID)   rotation sensing   WSN  

摘要： Phase-based sensing using ultra-high frequency (UHF) radio-frequency identification (RFID) has, in recent years, yielded numerous additions to the Internet of Things (IoT). This work presents a polarization diversity-based rotation sensing methodology using common-off-the-shelf (COTS) UHF RFID tags identified with a software-defined radio (SDR) UHF RFID reader. The proposed methodology uses the tag-to-reader message after fully coherent demodulation to calculate a difference signal of the backscatter load modulation states. This sequence is then used to compute the rotation speed by evaluating its phase change over time. Experimental results are used to validate the theoretical model and to evaluate the performance and limitiations of the proposed system.

摘要： Introduction:Radiofrequency Identification (RFID) is becoming a ubiquitous technology that provides methods of tracking and organizing complex processes, and has had previously described benefits when used in medical and clinical situations such as disaster and mass casualty incidents. However, the potential benefits of this technology have not yet been examined or applied to mass gathering events such as music festivals using the medical ***:RFID at music festivals was observed and characterized at a Canadian multi-day festival through a combination of (1) observation of real world application of the use of RFID-enabled attendee wristbands and (2) the development of a proposed implementation framework using expert input in event medical care, public health, festival safety and event organization. Potential roles for RFID technology in enhancing attendee safety, facilitating event medical care and collaborating with other on-site services, and promoting research agendas for these unique events were ***:Observed and theoretical roles for RFID fell into four main domains: (1) the presence of important encoded personal health data and contacts specific to individuals that would be accessible in case of an emergency, (2) the unique, anonymous identification of attendees who access (and re-access) medical as well as other services, including during handovers between these services, (3) support for any larger public health research projects aimed at understanding the behaviors and flow of attendees, including recreational substance use and related harm reduction efforts, and (4) the storage of festival-tailored data throughout the event on RFID-enabled wristbands (eg previous medical visit details, self-entered substance use history, etc).Conclusion:The use of RFID at music festivals has clear benefits. It allows for the dynamic access and retrieval of important data that can aid safety and support the provision of timely and tailored medical care. Se

关键词： Internet of Things   RFID   Linguistic features   Natural language processing   CRF model   Intelligent identification  

摘要： This study aims to enhance language comprehension and interaction and foster the advancement of Chinese information processing technology in the domains of comprehension and artificial intelligence. Firstly, the study elucidates the methodology employed for intelligent recognition of noun phrases, utilizing a combination of Radio Frequency Identification and Internet of Things (IoT) technologies. Secondly, it delves into the linguistic features involved in the intelligent recognition process of noun phrases. Subsequently, it expounds upon the learning process of the Conditional Random Field (CRF) model, drawing upon the advancements in natural language processing within noun phrase recognition research. Lastly, the study constructs a noun phrase recognition model based on the CRF model and IoT, followed by an analysis of noun phrase intelligent recognition with regard to their distinctive characteristics.

关键词： Building information modeling   Radio frequency identification   Wireless sensor network   IoT   Delphi method   AECO  

摘要： Purpose The purpose of this study is to identify, classify and prioritize the benefits, challenges and risks for the integrated use of building information modeling (BIM), radio frequency identification (RFID) and wireless sensor network (WSN) in the architecture, engineering, construction and operation (AECO) industry. Design/methodology/approach This study relies on the mixed method approach which consists of systematic literature review, semistructured interviews and Delphi technique. A systematic literature review was performed and face-to-face semistructured interviews with seven subject matter experts (SMEs) were conducted for identification and classification purposes. Delphi method was applied in two structured rounds with eleven SMEs for prioritization purpose. These three research techniques were chosen to reach the most accurate data by combining different perspectives on the subject matter. Data gathered by these three methods was triangulated to increase the validity and reliability of this research. Findings Thirteen benefits, ten challenges and four risks for the integrated use of BIM, RFID and WSN were identified. The results could aid the practitioners and researchers comprehend the pros and cons of this integration by representing SMEs' valuable insights and perspectives about the current and future status, trends, limitations and requirements of the AECO industry. The identified risks and challenges show the requirements for future studies while the benefits demonstrate the capabilities and the potential contributions of this hybrid integration to the AECO industry. Originality/value The integration of BIM, RFID and WSN is still not commonly implemented in the AECO industry. Some studies focused on this topic;however, none of them reveals the benefits, risks and challenges for integrating BIM, RFID and WSN in a holistic manner. This research makes a significant contribution to the AECO literature and industry by uncovering the benefits, challenges

关键词： action segmentation   deep learning   deep residual network   fall detection   RFID  

摘要： Since falls of the elderly can easily cause serious health problems in daily life, fall detection has received the attention of researchers. Traditionally, wearable sensors have been used to detect whether a person has fallen. However, wearable sensors may bring inconvenience to users' activities and affect user experience. In this paper, a fall detection approach based on RFID is proposed. In the proposed approach, non-contact passive tags are used to construct an array of tags. Fall detection will be performed without the user wearing the device. The RSSI and phase data are collected when the reader queries the tags. Furthermore, an action segmentation algorithm is designed to quickly extract human action information based on the short-term variance change of the phase signal. Subsequently, a deep residual network is built to classify fall movements and daily movements. Experiments show that the system can handle differences among users and locations and has an excellent performance in terms of recognition accuracy and efficiency, with an average accuracy rate of 96.77%.