The design and development of multi-agent based RFID middleware system for data and devices management

Thesis (D. Tech. (Electrical Engineering)) - Central University of technology, Free State, 2012Radio frequency identification technology (RFID) has emerged as a key technology for automatic identification and promises to revolutionize business processes. While RFID technology adoption is improving rapidly, reliable and widespread deployment of this technology still faces many significant challenges. The key deployment challenges include how to use the simple, unreliable raw data generated by RFID deployments to make business decisions; and how to manage a large number of deployed RFID devices. In this thesis, a multi-agent based RFID middleware which addresses some of the RFID data and device management challenges was developed. The middleware developed abstracts the auto-identification applications from physical RFID device specific details and provides necessary services such as device management, data cleaning, event generation, query capabilities and event persistence. The use of software agent technology offers a more scalable and distributed system architecture for the proposed middleware. As part of a multi-agent system, application-independent domain ontology for RFID devices was developed. This ontology can be used or extended in any application interested with RFID domain ontology. In order to address the event processing tasks within the proposed middleware system, a temporal-based RFID data model which considers both applications’ temporal and spatial granules in the data model itself for efficient event processing was developed. The developed data model extends the conventional Entity-Relationship constructs by adding a time attribute to the model. By maintaining the history of events and state changes, the data model captures the fundamental RFID application logic within the data model. Hence, this new data model supports efficient generation of application level events, updating, querying and analysis of both recent and historical events. As part of the RFID middleware, an adaptive sliding-window based data cleaning scheme for reducing missed readings from RFID data streams (called WSTD) was also developed. The WSTD scheme models the unreliability of the RFID readings by viewing RFID streams as a statistical sample of tags in the physical world, and exploits techniques grounded in sampling theory to drive its cleaning processes. The WSTD scheme is capable of efficiently coping with both environmental variations and tag dynamics by automatically and continuously adapting its cleaning window size, based on observed readings

Dense and long-term monitoring of Earth surface processes with passive RFID -- a review

Billions of Radio-Frequency Identification (RFID) passive tags are produced yearly to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing to monitor earth surface processes. Indeed, passive tags can cost 10 to 100 times less than wireless sensors networks and require little maintenance, facilitating years-long monitoring with ten's to thousands of tags. This study reviews the existing and potential applications of RFID in geosciences. The most mature application today is the study of coarse sediment transport in rivers or coastal environments, using tags placed into pebbles. More recently, tag localization was used to monitor landslide displacement, with a centimetric accuracy. Sensing tags were used to detect a displacement threshold on unstable rocks, to monitor the soil moisture or temperature, and to monitor the snowpack temperature and snow water equivalent. RFID sensors, available today, could monitor other parameters, such as the vibration of structures, the tilt of unstable boulders, the strain of a material, or the salinity of water. Key challenges for using RFID monitoring more broadly in geosciences include the use of ground and aerial vehicles to collect data or localize tags, the increase in reading range and duration, the ability to use tags placed under ground, snow, water or vegetation, and the optimization of economical and environmental cost. As a pattern, passive RFID could fill a gap between wireless sensor networks and manual measurements, to collect data efficiently over large areas, during several years, at high spatial density and moderate cost.Comment: Invited paper for Earth Science Reviews. 50 pages without references. 31 figures. 8 table

Wireless sensor system for infrastructure health monitoring

In this thesis, radio frequency identification (RFID)-based wireless sensor system for infrastructure health monitoring (IHM) is designed and developed. It includes mountable semi-passive tag antenna integrated sensors capable of measuring critical responses of infrastructure such as dynamic acceleration and strain. Furthermore, the system is capable of measuring structural displacement. One of the most important parts of this system is the relatively small, tunable, construction material mountable RFID tag antenna. The tag antenna is electronically integrated with the sensors. Leading to the process of developing tag antenna integrated sensors having satisfactory wireless performance (sensitivity and read range) when mounted on concrete and metal structural members, the electromagnetic performance of the tag antenna is analyzed and optimized using both numerical and experimental procedures. Subsequently, it is shown that both the simulation and the experimental measurement results are in good agreement. The semi-passive RFID-based system is implemented in a wireless IHM system with multiple sensor points to measure dynamic acceleration and strain. The developed system can determine the natural frequencies of infrastructure and identify any state changes of infrastructure by measuring natural frequency shifts. Enhancement of the spectral bandwidth of the system has been performed under the constraints of the RFID hardware. The influence of the orientation and shape of the structural members on wireless power flow in the vicinity of those members is also investigated with the RFID reader-tag antenna system in both simulation and experiments. The antenna system simulations with a full-scale structural member have shown that both the orientation and the shape of the structural member influence the wireless power flow towards and in the vicinity of the member, respectively. The measurement results of the conducted laboratory experiments using the RFID antenna system in passive mode have shown good agreement with simulation results. Furthermore, the system’s ability to measure structural displacement is also investigated by conducting phase angle of arrival measurements. It is shown that the system in its passive mode is capable of measuring small structural displacements within a short wireless distance. The benchmarking of the developed system with independent, commercial, wired and wireless measurement systems has confirmed the ability of the RFID-based system to measure dynamic acceleration and strain. Furthermore, it has confirmed the system’s ability to determine the natural frequency of an infrastructure accurately. Therefore, the developed system with wireless sensors that do not consume battery power in data transmission and with the capability of dynamic response measurement is highly applicable in IHM

Integrated ZigBee RFID sensor networks for resource tracking and monitoring in logistics management

The Radio Frequency Identification (RFID), which includes passive and active systems and is the hottest Auto-ID technology nowadays, and the wireless sensor network (WSN), which is one of the focusing topics on monitoring and control, are two fast-growing technologies that have shown great potential in future logistics management applications. However, an information system for logistics applications is always expected to answer four questions: Who, What, When and Where (4Ws), and neither of the two technologies is able to provide complete information for all of them. WSN aims to provide environment monitoring and control regarded as When and What , while RFID focuses on automatic identification of various objects and provides Who (ID). Most people usually think RFID can provide Where at all the time. But what normal passive RFID does is to tell us where an object was the last time it went through a reader, and normal active RFID only tells whether an object is presenting on site. This could sometimes be insufficient for certain applications that require more accurate location awareness, for which a system with real-time localization (RTLS), which is an extended concept of RFID, will be necessary to answer Where constantly. As WSN and various RFID technologies provide information for different but complementary parts of the 4Ws, a hybrid system that gives a complete answer by combining all of them could be promising in future logistics management applications. Unfortunately, in the last decade those technologies have been emerging and developing independently, with little research been done in how they could be integrated. This thesis aims to develop a framework for the network level architecture design of such hybrid system for on-site resource management applications in logistics centres. The various architectures proposed in this thesis are designed to address different levels of requirements in the hierarchy of needs, from single integration to hybrid system with real-time localization. The contribution of this thesis consists of six parts. Firstly, two new concepts, Reader as a sensor and Tag as a sensor , which lead to RAS and TAS architectures respectively, for single integrations of RFID and WSN in various scenarios with existing systems; Secondly, a integrated ZigBee RFID Sensor Network Architecture for hybrid integration; Thirdly, a connectionless inventory tracking architecture (CITA) and its battery consumption model adding location awareness for inventory tracking in Hybrid ZigBee RFID Sensor Networks; Fourthly, a connectionless stochastic reference beacon architecture (COSBA) adding location awareness for high mobility target tracking in Hybrid ZigBee RFID Sensor Networks; Fifthly, improving connectionless stochastic beacon transmission performance with two proposed beacon transmission models, the Fully Stochastic Reference Beacon (FSRB) model and the Time Slot Based Stochastic Reference Beacon (TSSRB) model; Sixthly, case study of the proposed frameworks in Humanitarian Logistics Centres (HLCs). The research in this thesis is based on ZigBee/IEEE802.15.4, which is currently the most widely used WSN technology. The proposed architectures are demonstrated through hardware implementation and lab tests, as well as mathematic derivation and Matlab simulations for their corresponding performance models. All the tests and simulations of my designs have verified feasibility and features of our designs compared with the traditional systems

Developing a person guidance module for hospital robots

This dissertation describes the design and implementation of the Person Guidance Module (PGM) that enables the IWARD (Intelligent Robot Swarm for attendance, Recognition, Cleaning and delivery) base robot to offer route guidance service to the patients or visitors inside the hospital arena. One of the common problems encountered in huge hospital buildings today is foreigners not being able to find their way around in the hospital. Although there are a variety of guide robots currently existing on the market and offering a wide range of guidance and related activities, they do not fit into the modular concept of the IWARD project. The PGM features a robust and foolproof non-hierarchical sensor fusion approach of an active RFID, stereovision and cricket mote sensor for guiding a patient to the X-ray room, or a visitor to a patient’s ward in every possible scenario in a complex, dynamic and crowded hospital environment. Moreover, the speed of the robot can be adjusted automatically according to the pace of the follower for physical comfort using this system. Furthermore, the module performs these tasks in any unconstructed environment solely from a robot’s onboard perceptual resources in order to limit the hardware installation costs and therefore the indoor setting support. Similar comprehensive solution in one single platform has remained elusive in existing literature. The finished module can be connected to any IWARD base robot using quick-change mechanical connections and standard electrical connections. The PGM module box is equipped with a Gumstix embedded computer for all module computing which is powered up automatically once the module box is inserted into the robot. In line with the general software architecture of the IWARD project, all software modules are developed as Orca2 components and cross-complied for Gumstix’s XScale processor. To support standardized communication between different software components, Internet Communications Engine (Ice) has been used as middleware. Additionally, plug-and-play capabilities have been developed and incorporated so that swarm system is aware at all times of which robot is equipped with PGM. Finally, in several field trials in hospital environments, the person guidance module has shown its suitability for a challenging real-world application as well as the necessary user acceptance

FRAMEWORK FOR IMPROVING PERFORMANCE OF PROTOCOLS FOR READING RADIO FREQUENCY IDENTIFICATION TAGS

Radio-frequency Identification (RFID) is a highly sought-after wireless technology used to track and manage inventory in the supply chain industry. It has varied applications ranging from automated toll collection and security access management to supply chain logistics. Miniaturization and low tag costs of RFID tags have lead to item-level tagging, where not just the pallet holding products is tagged but each product inside has a tag attached to it. Item-level tagging of goods improves the accuracy of the supply chain but it significantly increases the number of tags that an RFID reader must identify and track. Faster identification is crucial to cutting cost and improving efficiency. Existing RFID protocols were designed to primarily handle static scenarios with both RFID tags and readers not being in motion. This research addresses the problem of inventory tracking within a warehouse in multitude of scenarios that involves mobile tags, multiple readers and high density environments. Mobility models are presented and frameworks are developed for the following scenarios: a) mobile tags on a conveyor belt with multiple fixed readers; b) mobile reader in a warehouse with stationary tags in shelves; and c) high density tag population with Near-Field (NF) communication. The proposed frameworks use information sharing among readers to facilitate protocol state handoff and segregation of tags into virtual zones to improve tag reading rates in mobile tag and mobile reader scenarios respectively. Further, a tag’s ability to listen to its Near-Field neighboring tags transmissions is exploited to assist the reader in resolving collisions and hence enhancing throughput. The frameworks discussed in this research are mathematically modeled with a probabilistic analysis of protocols employed in conjunction with framework. With an increased number of tags to be identified, mathematically understanding the performance of the protocol in these large-scale RFID systems becomes essential. Typically, this analysis is performed using Markov-chain models. However, these analyses suffer from the common state-space explosion problem. Hence, it is essential to come up with a scalable analysis, whose computation model is insensitive to the number of tags. The following research analyzes the performance of tag identification protocols in highly dense tag scenarios, and proposes an empirical formula to estimate the approximate time required to read all the tags in a readers range without requiring protocol execution

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