RFID Localization Research Articles

Vehicle Monitoring and Tracking System

In this paper we present a vehicle monitoring and tracking system. Previous systems focus solely on either theft detection or car/driver monitoring. In this paper we provide an integrated solution that provide both theft detection, tracking and driver behavior monitoring. Our system performs well in detecting theft attempts through RFID and tracking location by GPS. It also monitors the driver behavior using OBD reader. Combining both features in one system has great advantages like cost efficiency, space saving and the possibility of adding new features.

A Novel Active RFID and TinyML based system for livestock Localization in Pakistan

Localization of livestock is a vital component of good livestock management in Pakistan. This abstract describes a unique method for livestock localization in Pakistan that makes use of Active RFID technology and Tiny Machine Learning (TinyML) approaches. The incorporation of Active RFID technology allows for precise and long-range livestock tracking, while TinyML provides on-device analysis and decision-making. This method has a number of advantages, including high precision, real-time localization, and less reliance on external infrastructure. Accurate triangulation-based localization is obtained by putting Active RFID tags on cattle and carefully positioning Active RFID anchors in specific regions. TinyML integration on resource-constrained microcontrollers within Active RFID tags allows for efficient on-device analysis of Active RFID signals. The suggested system has the potential to significantly improve livestock management practices in Pakistan, including animal tracking and monitoring, behavior analysis, and increased animal welfare. To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies

MRPSO-Loc: Multi-targets UHF RFID localization system based on MRPSO algorithm

Existing RFID localization techniques mainly focus on the location of a single target, which do not fully utilize the multi-targets identification merit of UHF RFID systems. In this paper, a multi-targets localization algorithm called merged re-shaken particle swarm optimization (MRPSO) is proposed. The ranging information and the angle information, which are obtained by using multi-frequency phase information with the help of frequency hopping technique, are merged together during the iteration process of MRPSO. In addition, based on the traditional PSO algorithm, a low weight particle filtering method was proposed, and a re-shaken scheme was introduced to improve localization accuracy. By allocating particles to each target, MRPSO can obtain each target location simultaneously after PSO process, which avoids time consuming. The experimental results show that MRPSO can achieve single-station multi-target localization with a median accuracy of 9.64 cm.

Location privacy protection of nodes in the perception layer of the Internet of things based on Radio Frequency Identification location aware algorithm

AbstractTo ensure the security of node location privacy in the perception layer of the Internet of Things, this study proposes a location privacy protection method based on RFID location awareness algorithm. This method first introduces an adaptive multi tree anti‐collision algorithm based on collision trees when perceiving and locating the location information of nodes in the perception layer of the Internet of Things, to prevent signal collisions between multiple readers and writers. Then, based on the obtained node location results, a IoT perception layer node location privacy protection scheme based on virtual ring strategy is used to randomly initiate directed co hop routing using the virtual nodes generated after random walking, avoiding the visible area of the source node location, and transmitting data to the aggregation node in the form of the shortest routing path to protect the privacy and security of the node location. Finally, experiments are carried out to prove the progressiveness of the proposed method. The experimental results show that this method can prolong the security period of the source and aggregation nodes in the perception layer of the Internet of Things, protect the privacy and security of node positions, and has great application value.

Underground Passive LF RFID Localization Method Based on Magnetic Field Model of Reader Coil Antenna

Underground Passive LF RFID Localization Method Based on Magnetic Field Model of Reader Coil Antenna

A novel holographic technique for RFID localization in indoor environments

A novel holographic technique for RFID localization in indoor environments

Research on RFID Localization Algorithm of Refrigerator Foods Based on Improved DenseNet Model

Long-term storage of food items often leads to expiration, as the user gradually forgets about their existence. Under this background, efficiently locating and managing food items in a complex environment is a bottleneck that must be solved for future refrigerators to substantially improve life quality for their users. This letter proposes an RFID fingerprint localization algorithm based on an improved DenseNet model combined with the Attention Mechanism to solve this problem. Compared with traditional CNNs, the improved model is 48.19% smaller in terms of the number of parameters and has better accuracy.

A Portable RFID Localization Approach for Mobile Robots

Localizing RFID-tagged objects by a mobile robot plays an important role in many Internet of Things (IoT) applications. Existing RFID localization systems are infeasible, since they either demand bulky RFID infrastructures or cannot achieve sufficient localization accuracy. In this article, a portable localization (POLO) system is developed for a mobile robot to locate RFID-tagged objects. POLO consists of an RFID reader, a tag array, and a lightweight receiver. The reader is used for interrogating the RFID tag on an object. The tag array is designed to reflect the RFID signal from an object into multipath signals. The receiver captures such signals and estimates their multipath channel coefficients by a tag-array-assisted channel estimation (TCE) mechanism. Such channel coefficients are further exploited to determine the object’s direction by a spatial smoothing direction estimation (SSDE) algorithm. To resist the impact of multipath reflections from surroundings, more spatial information is exploited by placing the tag elements densely and collecting the channel coefficients during the robot’s movement. Based on the object’s direction, POLO guides the robot to approach the object. When the object is in proximity, its 3-D location is finally determined by a near-range positioning (NRP) algorithm. Moreover, POLO is designed to be compatible with commercial RFID systems. POLO is prototyped and evaluated via extensive experiments. Results show that the average angular error is within 1 degree when the object is in the far range (2–6 m), and the average location error is within 6 cm while the object is in the near range (~1 m).

Timing: Tag Interference Modeling for RFID Localization in Dense Deployment

Due to low cost and low complexity, passive ultrahigh-frequency radio-frequency identification (UHF RFID) is gaining popularity in indoor localization. According to current RFID channel models, multipath propagation and noise are two significant factors that affect the accuracy of measured RF signals. To minimize the impacts of measurement errors on localization, scene analysis algorithms are proposed and got lots of attention in recent years. These algorithms make use of reference tags as similarity markers in neighboring locations to improve localization accuracy. However, densely deployed tags induce a new challenge, antenna interference, leading to the poor signal similarity between nearby tags. Nonetheless, there are no refined channel models for explaining the effect of spacing distances between tags on RF signal fluctuations, thus the choice of spacing distances becomes an outstanding issue for scene analysis localization algorithms. In this article, we propose Timing, the Tag Interference ModelING, for analyzing the relationship between signal fluctuations and spacing distances. Unlike inductive coupling in the near field, as the tags are all located at the far field of interacted antenna, we introduce microwave transmission line theory for channel model analysis. The experimental results verify that Timing is well suited to authentic situations. Additionally, we examine the performance of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -nearest neighbor ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -NN) algorithm under various spacing distances. The findings demonstrate that the spacing distance identified by Timing as a stable point achieves better accuracy with scene analysis algorithms. Therefore, Timing could be used as a critical foundation for the choice of spacing distances in future tag deployment applications.

Sing-Ant: RFID Indoor Positioning System Using Single Antenna with Multiple Beams Based on LANDMARC Algorithm

RFID localization methods have been widely used in indoor positioning systems (IPS). Most localization techniques involve the use of multiple antennas and the placement of antennas and readers in order to ensure accurate positioning results. However, most localization techniques are complex and require high overhead costs in terms of needing multiple antennas and RFID readers. In this paper, we proposed a method to use a single antenna to perform all the reads and rely rather on the antenna beams to acquire multiple positioning data. A single array of antennas is configured to have multiple angles of operation and rely on different power levels as compared to regular antennas. By manipulating the beam pattern, direction and power, multiple sub-antennas can be conceived and the method utilizes antenna beams and relies mainly on one antenna to realize two-dimensional localization.

A Cost-Efficient Hybrid UHF RFID and Odometry-Based Mobile Robot Self-Localization Technique With Centimeter Precision

This paper presents an indoor localization approach that determines the absolute position of a mobile robot platform with centimeter precision by fusing RFID localization results based on cost-effective, standard passive UHF RFID technology with the robot&#x2019;s odometry data. The mobile robot platform is equipped with a multistatic UHF RFID interrogation system, and several RFID tags are arbitrarily placed within the localization environment, serving as landmarks. The RFID localization concept is based on phase evaluations. To overcome the problem of ambiguous position estimations due to the 2&#x03C0;-phase ambiguity of the RFID signal phase and mitigate the linearization problem of the nonlinear system, a novel algorithm based on an iterative multihypothesis Kalman filter is introduced. A realistic simulation setup is developed to validate the proposed filter algorithm. By tracking a UHF RFID-equipped mobile robot platform in a real-world office environment, the proposed approach is also practically tested in terms of real-time capability, everyday suitability, and multipath resistance. Given that centimeter precision is only achieved in environments with weak multipath propagation, the RFID localization results are fused with odometry data provided by the robot. This effectively compensates for offset and drift in the odometry sensor, achieving a root-mean-square localization error of 2.7 cm.

Laboratory to Develop a Practical Hand-Made Monopulse Antenna for RFID Localization Systems

Laboratory to Develop a Practical Hand-Made Monopulse Antenna for RFID Localization Systems

2d Phase-Based RFID Localization for On-Site Landslide Monitoring

2d Phase-Based RFID Localization for On-Site Landslide Monitoring

Real-Time, Robot-Based, 3D Localization of RFID Tags, by Transforming Phase Measurements to a Linear Optimization Problem

In this paper, we propose a prototype method for fast and accurate 3D localization of RFID-tagged items by a mobile robot. The robot performs Simultaneous Localization of its own pose and Mapping of the surrounding environment (SLAM). It is equipped with RFID readers and antennas placed at different heights, collecting phase-measurements by all tags. Thanks to the self-localization property of the robot, a synthetic aperture is created for each tag. In this paper, we have manipulated the set of phase-measurements, combined with the known poses of the robot to craft an overdetermined system of linear equations which pinpoints the location of the tag. The linearity of the system preserves that localization is achieved rapidly. The problem is solved for any arbitrary movement of the robot and extended in three dimensions. The proposed method is experimentally compared against the state-of-the-art in SAR-based RFID localization. It is the fastest and the most accurate, when the robot moves along straight-paths. Its accuracy slightly worsens, when the robot moves along non-straight paths, while preserving its exceptionally small running-time. It can be applied in real-time 3D localization problems, demonstrating mean 3D accuracy below 20 cm.

Electromagnetic Characterization of UHF-RFID Fixed Reader in Healthcare Centers Related to the Personal and Labor Health

Hospitals and healthcare centers are experiencing a remarkable implementation of new systems based on wireless communications technologies. Many of these systems provide location services and identification of materials, instrumentation and even patients, which promotes the increase of the quality and the efficiency of healthcare. A tracking system based on short-range radio frequency, UHF-RFID is evaluated. This system helps with location of orthopedic prosthesis according to the criteria and requirements of a specific hospital environment. It is characterized the influence of UHF-RFID system in the electromagnetic environment by measuring the parameters and characteristics of the emission levels. The results of the assessment are represented through 2D contour maps and simulations have been performed by means of an in-house 3D-RL algorithm. The proposed graph aims to provide a methodology of studying the electromagnetic environments and the evaluation of the safety conditions of workers, patients, and people in general. E field exposure levels due to the RFID localization system were analyzed in order to verify regulations concerning the safety of patients and the general public in the labor and healthcare fields. Localized electromagnetic field exposure at levels which may cause electromagnetic hazards in the specific healthcare environment have been found and potentially excessive exposure to EMF emitted by UHF RFID devices may apply to patients or bystanders. In all cases, insufficient electromagnetic immunity of electronic devices (including AIMD and other medical devices) should be considered and the electromagnetic hazards may be limited also by relevant preventive measures, as also shown in this paper, together with the principles of an in-situ evaluation of electromagnetic hazards near the UHF-RFID devices.

Robust RFID Localization in Multipath With Phase-Based Particle Filtering and a Mobile Robot

This work revisits particle filtering RFID localization methods, solely based on phase measurements. The reader is installed on a low-cost robotic platform, which performs autonomously (and independently from the RFID reader) open source simultaneous localization and mapping (SLAM). In contrast to prior art, the proposed methods introduce a weight metric for each particle-measurement pair, based on geometry arguments, robust to phase measurement noise (e.g., due to multipath). In addition, the methods include the unknown constant phase offset as a parameter to be estimated. No reference tags are employed, no assumption on the tags' topology is assumed and special attention is paid for reduced execution time. It is found that the proposed phase-based localization methods offer robust performance in the presence of multipath, even when the tag phase measurements are variable in number and sporadic. The methods can easily accommodate a variable number of reader antennas. Mean absolute 3D localization error in the order of 24 cm for RFID tags in a library was shown, even though the system did not exploit excessive bandwidth or any reference tags. As a collateral dividend, the proposed methods also offer a concrete way to classify the environment as multipath-rich or not.

Tracking and Localization of Retained Foreign Objects using RFID TechnologyTracking and Localization of Retained Foreign Objects using RFID Technology

Tracking and Localization of Retained Foreign Objects using RFID TechnologyTracking and Localization of Retained Foreign Objects using RFID Technology

Computer Vision-Assisted 3D Object Localization via COTS RFID Devices and a Monocular Camera

In most RFID localization systems, acquiring a reader antenna's position at each sampling time is challenging, especially for those antenna-carrying robot or drone systems with unpredictable trajectories. In this article, we present RF-MVO that fuses RFID and computer vision for stationary RFID localization in 3D space by attaching a light-weight 2D monocular camera to two reader antennas in parallel. First, the existing monocular visual odometry only recovers a camera/antenna trajectory in the camera view from 2D images. By combining it with RF phase, we design a model to estimate a scale factor for real-world trajectory transformation, along with spatial directions of an RFID tag relative to a virtual antenna array due to the mobility of each antenna. Then we propose a novel RFID localization algorithm that does not require exhaustively searching all possible positions within the pre-specified region. Second, to speed up the searching process and improve localization accuracy, we propose a coarse-to-fine optimization algorithm. Third, we introduce the concept of horizontal dilution of precision (HDOP) to measure the confidence level of localization results. Our experiments demonstrate the effectiveness of proposed algorithms and show RF-MVO can achieve 6.23 cm localization error.

Design and Evaluation of an RFID Localization System based on Read Count

In this paper, we propose a new robust algorithm to improve the localization accuracy without using additional materials. This algorithm is based on a probabilistic approach which only uses the read count (number of detection) of reference and target tags. The localization is performed through two steps. The first step consists of estimating a local position of object tags in a given zone, while in the second step, all estimated local positions are used to calculate one global position. Furthermore, a complementary study concerning the influence of reference tags positions, the movement nature and the coverage of the work area is presented and discussed. For the proof of concept, a series of tests were elaborated with the proposed localization system created comprising conventional passive EPCglobal Class-1 Gen-2 UHF RFID tags, a commercial UHF RFID reader and a laptop. Measurements are carried out in an indoor environment where the 5.5 m×1.25 m measurement zone was placed on drywalls. The experimental results show that the present algorithm gives higher localization accuracy than the conventional ones.

Designing and validating a low-cost real time locating system to continuously assess patient wait times.

Outpatient clinics lack infrastructure to easily measure and understand patient wait times. Our objective was to design a low-cost, portable passive real time locating system within an outpatient clinic setting to measure patient wait times and patient-provider interactions. Direct observation was used to determine workflow in an outpatient glaucoma clinic at the University of Michigan. We used off-the shelf, antenna-integrated ultra-high frequency (UHF) RFID readers (ThingMagic, Astra-Ex, Woburn, MA) and UHF re-useable passive RFID tags (Zebra Impinj Monza 4QT, Seattle, WA). We designed a custom RFID management application in the Java programming language that was equipped with 'live' device administration to collect time and location data from patients and providers. These hardware choices enabled low cost system installation. Hidden Markov Modeling (HMM) was used to smooth patient and provider location data. Location data were validated against direct observations and EHR evaluation. The HMM smoothed RFID system data accurately predicted patient location 80.6% of the time and provider location 79.1% of the time, compared to direct observation locations, an improvement over the raw RFID location data (65.0% and 77.9% accurate, respectively). Patient process time was on average 42.8min (SD=27.5) and wait time was 47.9min (SD=33.1). The installation and recurring capital costs of the system are approximately 10% of available commercially-supplied patient/provider tracking systems. Passive RFID time study systems can enable real-time localization of people in clinic, facilitating continuous capture of patient wait times and patient-provider interactions. The system must be tailored to the clinic to accurately reflect patient and provider movement. Capturing wait time data continuously and passively can empower continuous clinical quality improvement initiatives to enhance the patient experience.