A review of RFID based solutions for indoor localization and location-based classification of tags

Wireless communication systems are very used for indoor localization of items. In particular, two main application field can be identified. The former relates to detection or localization of static items. The latter relates to real-time tracking of moving objects, whose movements can be reconstructed over identified timespans. Among the adopted technologies, Radio-Frequency IDentification (RFID), especially if based on cheap passive RFID tags, stands out for its affordability and reasonable efficiency. This aspect makes RFID suitable for both the above-mentioned applications, especially when a large number of objects need to be tagged. The reason lies in a suitable trade-off between low cost for implementing the position sensing system, and its precision and accuracy. However, RFID-based solutions suffer for limited reading range and lower accuracy. Solutions have been proposed by academia and industry. However, a structured analysis of developed solutions, useful for further implementations, is missing. The purpose of this paper is to highlight and review the recently proposed solutions for indoor localization making use of RFID passive tags. The paper focuses on both precise and qualitative location of objects. The form relates to (i) the correct position of tags, namely mapping their right position in a 2D or 3D environment. The latter relates to the classification of tags, namely the identification of the area where the tag is regardless its specific position

Sulautettu ohjelmistototeutus reaaliaikaiseen paikannusjärjestelmään

Asset tracking often necessitates wireless, radio-frequency identification (RFID). In practice, situations often arise where plain inventory operations are not sufficient, and methods to estimate movement trajectory are needed for making reliable observations, classification and report generation. In this thesis, an embedded software application for an industrial, resource-constrained off-the-shelf RFID reader device in the UHF frequency range is designed and implemented. The software is used to configure the reader and its air-interface operations, accumulate read reports and generate events to be reported over network connections. Integrating location estimation methods to the application facilitates the possibility to make deploying middleware RFID solutions more streamlined and robust while reducing network bandwidth requirements. The result of this thesis is a functional embedded software application running on top of an embedded Linux distribution on an ARM processor. The reader software is used commercially in industrial and logistics applications. Non-linear state estimation features are applied, and their performance is evaluated in empirical experiments.Tavaroiden seuranta edellyttää usein langatonta radiotaajuustunnistustekniikkaa (RFID). Käytännön sovelluksissa tulee monesti tilanteita joissa pelkkä inventointi ei riitä, vaan tarvitaan menetelmiä liikeradan estimointiin luotettavien havaintojen ja luokittelun tekemiseksi sekä raporttien generoimiseksi. Tässä työssä on suunniteltu ja toteutettu sulautettu ohjelmistosovellus teolliseen, resursseiltaan rajoitettuun ja kaupallisesti saatavaan UHF-taajuusalueen RFID-lukijalaitteeseen. Ohjelmistoa käytetään lukijalaitteen ja sen ilmarajapinnan toimintojen konfigurointiin, lukutapahtumien keräämiseen ja raporttien lähettämiseen verkkoyhteyksiä pitkin. Paikkatiedon estimointimenetelmien integroiminen ohjelmistoon mahdollistaa välitason RFID-sovellusten toteuttamisen aiempaa suoraviivaisemin ja luotettavammin, vähentäen samalla vaatimuksia tietoverkon kaistanleveydelle. Työn tuloksena on toimiva sulautettu ohjelmistosovellus, jota ajetaan sulautetussa Linux-käyttöjärjestelmässä ARM-arkkitehtuurilla. Lukijaohjelmistoa käytetään kaupallisesti teollisuuden ja logistiikan sovelluskohteissa. Epälineaarisia estimointiominaisuuksia hyödynnetään, ja niiden toimivuutta arvioidaan empiirisin kokein

The Design and Implementation of a Mobile RFID Tag Sorting Robot

Libraries, manufacturing lines, and offices of the future all stand to benefit from knowing the exact spatial order of RFID-tagged books, components, and folders, respectively. To this end, radio- based localization has demonstrated the potential for high accuracy. Key enabling ideas include motion-based synthetic aperture radar, multipath detection, and the use of different frequencies (channels). But indoors in real-world situations, current systems often fall short of the mark, mainly because of the prevalence and strength of "multipath" reflections of the radio signal off nearby objects. In this paper we describe the design and implementation of MobiTagbot, an autonomous wheeled robot reader that conducts a roving survey of the above such areas to achieve an exact spatial order of RFID- tagged objects in very close (1–6 cm) spacings. Our approach leverages a serendipitous correlation between the changes in multipath reflections that occur with motion and the effect of changing the carrier frequency (channel) of the RFID query. By carefully observing the relationship between channel and phase, MobiTagbot detects if multipath is likely prevalent at a given robot reader location. If so, MobiTagbot excludes phase readings from that reader lo- cation, and generates a final location estimate using phase readings from other locations as the robot reader moves in space. Experimentally, we demonstrate that cutting-edge localization algorithms including Tagoram are not accurate enough to exactly order items in very close proximity, but MobiTagbot is, achieving nearly 100% ordering accuracy for items at low (3–6 cm) spacings and 86% accuracy for items at very low (1–3 cm) spacings

A new methods of mobile object measurement by using radio frequency identification

In this study, the mobile robot conducts tag of RFID and the antennas’ reader was scattered at the indoor-outdoor environment, which represents the novelty of the study, as this has not been done in the previous studies. This protects the mobile robot from weight increase reduces the consumption of the battery. Moreover, mobile object increase demands an increase in cheap passive Radio Frequency Identification tags in the system of navigation. Techniques of Signal processing utilize both accompanied by the theories of electromagnetics in locating the robot’s position. Numerous antennas usage provides a breadth of comparisons. In this work, have been provide a new RFID tracking approach that can also be used for interior positioning. This technique employs RSS to gather the signal intensity of reference tags before they are used. The next step is to send a signal. Setting up Power Level ranges via reference tags uses strength as a setting parameter. Then, based on the intensity of the signal, you can determine how far away you are. Reference tags are used to match the signal intensity of track tags. Finally, when track tags are installed in indoor locations, they can be used to monitor the movement of people. It will use the arithmetic mean of the positions of surrounding reference tags to determine the location. Values. According to preliminary results from an experiment, our approach is more precise than the antenna system. Approximately 10 to 20 lines

Hybrid and Cooperative Positioning Solutions for Wireless Networks

In this thesis, some hybrid and cooperative solutions are proposed and analyzed to locate the user in challenged scenarios, with the aim to overcome the limits of positioning systems based on single technology. The proposed approaches add hybrid and cooperative features to some conventional position estimation techniques like Kalman filter and particle filter, and fuse information from different radio frequency technologies. The concept of cooperative positioning is enhanced with hybrid technologies, in order to further increase the positioning accuracy and availability. In particular, wireless sensor networks and radio frequency identification technology are used together to enhance the collected data with position information. Terrestrial ranging techniques (i.e., ultra-wide band technology) are employed to assist the satellite-based localization in urban canyons and indoors. Moreover, some advanced positioning algorithms, such as energy efficient, cognitive tracking and non-line-of-sight identification, are studied to satisfy the different positioning requirements in harsh indoor environments. The proposed hybrid and cooperative solutions are tested and verified by first Monte Carlo simulations then real experiments. The obtained results demonstrate that the proposed solutions can increase the robustness (positioning accuracy and availability) of the current localization system

Wireless Localization Systems: Statistical Modeling and Algorithm Design

Wireless localization systems are essential for emerging applications that rely on context-awareness, especially in civil, logistic, and security sectors. Accurate localization in indoor environments is still a challenge and triggers a fervent research activity worldwide. The performance of such systems relies on the quality of range measurements gathered by processing wireless signals within the sensors composing the localization system. Such range estimates serve as observations for the target position inference. The quality of range estimates depends on the network intrinsic properties and signal processing techniques. Therefore, the system design and analysis call for the statistical modeling of range information and the algorithm design for ranging, localization and tracking. The main objectives of this thesis are: (i) the derivation of statistical models and (ii) the design of algorithms for different wire- less localization systems, with particular regard to passive and semi-passive systems (i.e., active radar systems, passive radar systems, and radio frequency identification systems). Statistical models for the range information are derived, low-complexity algorithms with soft-decision and hard-decision are proposed, and several wideband localization systems have been analyzed. The research activity has been conducted also within the framework of different projects in collaboration with companies and other universities, and within a one-year-long research period at Massachusetts Institute of Technology, Cambridge, MA, USA. The analysis of system performance, the derived models, and the proposed algorithms are validated considering different case studies in realistic scenarios and also using the results obtained under the aforementioned projects