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

Guided Target Control System Final Design Report

Daimler Automotive, the parent company of Mercedes-benz requires improved methods for testing their Autonomous Emergency Braking Systems. To this end they have presented a series of four senior projects to California Polytechnic State University in San Luis Obispo. One of the Projects is to build a facsimile of a human crossing the street. The other three projects of which this is a part; are to produce an autonomous car facsimile. These projects are intended for use in testing new Autonomous Emergency Braking Systems and may serve as the basis for future senior projects

Mapping, Path Following, and Perception with Long Range Passive UHF RFID for Mobile Robots

Service robots have shown an impressive potential in providing assistance and guidance in various environments, such as supermarkets, shopping malls, homes, airports, and libraries. Due to the low-cost and contactless way of communication, radio-frequency identification (RFID) technology provides a solution to overcome the difficulties (e.g. occlusions) that the traditional line of sight sensors (e.g. cameras and laser range finders) face. In this thesis, we address the applications of using passive ultra high frequency (UHF) RFID as a sensing technology for mobile robots in three fundamental tasks, namely mapping, path following, and tracking. An important task in the field of RFID is mapping, which aims at inferring the positions of RFID tags based on the measurements (i.e. the detections as well as the received signal strength) received by the RFID reader. The robot, which serves as an intelligent mobile carrier, is able to localize itself in a known environment based on the existing positioning techniques, such as laser-based Monte Carlo localization. The mapping process requires a probabilistic sensor model, which characterizes the likelihood of receiving a measurement, given the relative pose of the antenna and the tag. In this thesis, we address the problem of recovering from mapping failures of static RFID tags and localizing non-static RFID tags which do not move frequently using a particle filter. The usefulness of negative information (e.g. non-detections) is also examined in the context of mapping RFID tags. Moreover, we present a novel three dimensional (3D) sensor model to improve the mapping accuracy of RFID tags. In particular, using this new sensor model, we are able to localize the 3D position of an RFID tag by mounting two antennas at different heights on the robot. We additionally utilize negative information to improve the mapping accuracy, especially for the height estimation in our stereo antenna configuration. The model-based localization approach, which works as a dual to the mapping process, estimates the pose of the robot based on the sensor model as well as the given positions of RFID tags. The fingerprinting-based approach was shown to be superior to the model-based approach, since it is able to better capture the unpredictable radio frequency characteristics in the existing infrastructure. Here, we present a novel approach that combines RFID fingerprints and odometry information as an input of the motion control of a mobile robot for the purpose of path following in unknown environments. More precisely, we apply the teaching and playback scheme to perform this task. During the teaching stage, the robot is manually steered to move along a desired path. RFID measurements and the associated motion information are recorded in an online-fashion as reference data. In the second stage (i.e. playback stage), the robot follows this path autonomously by adjusting its pose according to the difference between the current RFIDmeasurements and the previously recorded reference measurements. Particularly, our approach needs no prior information about the distribution and positions of the tags, nor does it require a map of the environment. The proposed approach features a cost-effective alternative for mobile robot navigation if the robot is equipped with an RFID reader for inventory in RFID-tagged environments. The capability of a mobile robot to track dynamic objects is vital for efficiently interacting with its environment. Although a large number of researchers focus on the mapping of RFID tags, most of them only assume a static configuration of RFID tags and too little attention has been paid to dynamic ones. Therefore, we address the problem of tracking dynamic objects for mobile robots using RFID tags. In contrast to mapping of RFID tags, which aims at achieving a minimum mapping error, tracking does not only need a robust tracking performance, but also requires a fast reaction to the movement of the objects. To achieve this, we combine a two stage dynamic motion model with the dual particle filter, to capture the dynamic motion of the object and to quickly recover from failures in tracking. The state estimation from the particle filter is used in a combination with the VFH+ (Vector Field Histogram), which serves as a local path planner for obstacle avoidance, to guide the robot towards the target. This is then integrated into a framework, which allows the robot to search for both static and dynamic tags, follow it, and maintain the distance between them. [untranslated]Service-Roboter bergen ein großes Potential bei der Unterstützung, Beratung und Führung von Kunden oder Personal in verschiedenen Umgebungen wie zum Beispiel Supermärkten, Einkaufszentren, Wohnungen, Flughäfen und Bibliotheken. Durch die geringen Kosten und die kontaktlose Kommunikation ist die RFID Technologie in der Lage vorhandene Herausforderungen traditioneller sichtlinienbasierter Sensoren (z.B. Verdeckung beim Einsatz von Kameras oder Laser-Entfernungsmessern) zu lösen. In dieser Arbeit beschäftigen wir uns mit dem Einsatz von passivem Ultrahochfrequenz (UHF) RFID als Sensortechnologie für mobile Roboter hinsichtlich drei grundlegender Aufgabenstellungen Kartierung, Pfadverfolgung und Tracking. Kartierung nimmt eine wesentliche Rolle im Bereich der Robotik als auch beim Einsatz von RFID Sensoren ein. Hierbei ist das Ziel die Positionen von RFID-Tags anhand von Messungen (die Erfassung der Tags als solche und die Signalstärke) zu schätzen. Der Roboter, der als intelligenter mobiler Träger dient, ist in der Lage, sich selbst in einer bekannten Umgebung auf Grundlage der bestehenden Positionierungsverfahren, wie Laser-basierter Monte-Carlo Lokalisierung zurechtzufinden. Der Kartierungsprozess erfordert ein probabilistisches Sensormodell, das die Wahrscheinlichkeit beschreibt, ein Tag an einer gegebenen Position relativ zur RFID-Antenne (ggf. mit einer bestimmten Signalstärke) zu erkennen. Zentrale Aspekte dieser Arbeit sind die Regeneration bei fehlerhafter Kartierung statischer RFID-Tags und die Lokalisierung von nicht-statischen RFID-Tags. Auch wird die Verwendbarkeit negativer Informationen, wie z.B. das Nichterkennen von Transpondern, im Rahmen der RFID Kartierung untersucht. Darüber hinaus schlagen wir ein neues 3D-Sensormodell vor, welches die Genauigkeit der Kartierung von RFID-Tags verbessert. Durch die Montage von zwei Antennen auf verschiedenen Höhen des eingesetzten Roboters, erlaubt es dieses Modell im Besonderen, die 3D Positionen von Tags zu bestimmen. Dabei nutzen wir zusätzlich negative Informationen um die Genauigkeit der Kartierung zu erhöhen. Dank der Eindeutigkeit von RFID-Tags, ist es möglich die Lokalisierung eines mobilen Roboters ohne Mehrdeutigkeit zu bestimmen. Der modellbasierte Ansatz zur Lokalisierung schätzt die Pose des Roboters auf Basis des Sensormodells und den angegebenen Positionen der RFID-Tags. Es wurde gezeigt, dass der Fingerprinting-Ansatz dem modellbasierten Ansatz überlegen ist, da ersterer in der Lage ist, die unvorhersehbaren Funkfrequenzeigenschaften in der vorhandenen Infrastruktur zu erfassen. Hierfür präsentieren wir einen neuen Ansatz, der RFID Fingerprints und Odometrieinformationen für die Zwecke der Pfadverfolgung in unbekannten Umgebungen kombiniert. Dieser basiert auf dem Teaching-and-Playback-Schema. Während der Teaching-Phase wird der Roboter manuell gelenkt, um ihn entlang eines gewünschten Pfades zu bewegen. RFID-Messungen und die damit verbundenen Bewegungsinformationen werden als Referenzdaten aufgezeichnet. In der zweiten Phase, der Playback-Phase, folgt der Roboter diesem Pfad autonom. Der vorgeschlagene Ansatz bietet eine kostengünstige Alternative für die mobile Roboternavigation bei der Bestandsaufnahme in RFID-gekennzeichneten Umgebungen, wenn der Roboter mit einem RFID-Lesegerät ausgestattet ist. Die Fähigkeit eines mobilen Roboters dynamische Objekte zu verfolgen ist entscheidend für eine effiziente Interaktion mit der Umgebung. Obwohl sich viele Forscher mit der Kartierung von RFID-Tags befassen, nehmen die meisten eine statische Konfiguration der RFID-Tags an, nur wenige berücksichtigen dabei dynamische RFID-Tags. Wir wenden uns daher dem Problem der RFID basierten Verfolgung dynamischer Objekte mit mobilen Robotern zu. Im Gegensatz zur Kartierung von RFID-Tags, ist für die Verfolgung nicht nur eine stabile Erkennung notwendig, es ist zudem erforderlich schnell auf die Bewegung der Objekte reagieren zu können. Um dies zu erreichen, kombinieren wir ein zweistufiges dynamisches Bewegungsmodell mit einem dual-Partikelfilter. Die Zustandsschätzung des Partikelfilters wird in Kombination mit dem VFH+ (Vektorfeld Histogramm) verwendet, um den Roboter in Richtung des Ziels zu leiten. Hierdurch ist es dem Roboter möglich nach statischen und dynamischen Tags zu suchen, ihnen zu folgen und dabei einen gewissen Abstand zu halten

Data Fusion for Materials Location Estimation in Construction

Effective automated tracking and locating of the thousands of materials on construction sites improves material distribution and project performance and thus has a significant positive impact on construction productivity. Many locating technologies and data sources have therefore been developed, and the deployment of a cost-effective, scalable, and easy-to-implement materials location sensing system at actual construction sites has very recently become both technically and economically feasible. However, considerable opportunity still exists to improve the accuracy, precision, and robustness of such systems. The quest for fundamental methods that can take advantage of the relative strengths of each individual technology and data source motivated this research, which has led to the development of new data fusion methods for improving materials location estimation. In this study a data fusion model is used to generate an integrated solution for the automated identification, location estimation, and relocation detection of construction materials. The developed model is a modified functional data fusion model. Particular attention is paid to noisy environments where low-cost RFID tags are attached to all materials, which are sometimes moved repeatedly around the site. A portion of the work focuses partly on relocation detection because it is closely coupled with location estimation and because it can be used to detect the multi-handling of materials, which is a key indicator of inefficiency. This research has successfully addressed the challenges of fusing data from multiple sources of information in a very noisy and dynamic environment. The results indicate potential for the proposed model to improve location estimation and movement detection as well as to automate the calculation of the incidence of multi-handling

Privacy in rfid and mobile objects

Los sistemas RFID permiten la identificación rápida y automática de etiquetas RFID a través de un canal de comunicación inalámbrico. Dichas etiquetas son dispositivos con cierto poder de cómputo y capacidad de almacenamiento de información. Es por ello que los objetos que contienen una etiqueta RFID adherida permiten la lectura de una cantidad rica y variada de datos que los describen y caracterizan, por ejemplo, un código único de identificación, el nombre, el modelo o la fecha de expiración. Además, esta información puede ser leída sin la necesidad de un contacto visual entre el lector y la etiqueta, lo cual agiliza considerablemente los procesos de inventariado, identificación, o control automático. Para que el uso de la tecnología RFID se generalice con éxito, es conveniente cumplir con varios objetivos: eficiencia, seguridad y protección de la privacidad. Sin embargo, el diseño de protocolos de identificación seguros, privados, y escalables es un reto difícil de abordar dada las restricciones computacionales de las etiquetas RFID y su naturaleza inalámbrica. Es por ello que, en la presente tesis, partimos de protocolos de identificación seguros y privados, y mostramos cómo se puede lograr escalabilidad mediante una arquitectura distribuida y colaborativa. De este modo, la seguridad y la privacidad se alcanzan mediante el propio protocolo de identificación, mientras que la escalabilidad se logra por medio de novedosos métodos colaborativos que consideran la posición espacial y temporal de las etiquetas RFID. Independientemente de los avances en protocolos inalámbricos de identificación, existen ataques que pueden superar exitosamente cualquiera de estos protocolos sin necesidad de conocer o descubrir claves secretas válidas ni de encontrar vulnerabilidades en sus implementaciones criptográficas. La idea de estos ataques, conocidos como ataques de “relay”, consiste en crear inadvertidamente un puente de comunicación entre una etiqueta legítima y un lector legítimo. De este modo, el adversario usa los derechos de la etiqueta legítima para pasar el protocolo de autenticación usado por el lector. Nótese que, dada la naturaleza inalámbrica de los protocolos RFID, este tipo de ataques representa una amenaza importante a la seguridad en sistemas RFID. En esta tesis proponemos un nuevo protocolo que además de autenticación realiza un chequeo de la distancia a la cual se encuentran el lector y la etiqueta. Este tipo de protocolos se conocen como protocolos de acotación de distancia, los cuales no impiden este tipo de ataques, pero sí pueden frustrarlos con alta probabilidad. Por último, afrontamos los problemas de privacidad asociados con la publicación de información recogida a través de sistemas RFID. En particular, nos concentramos en datos de movilidad que también pueden ser proporcionados por otros sistemas ampliamente usados tales como el sistema de posicionamiento global (GPS) y el sistema global de comunicaciones móviles. Nuestra solución se basa en la conocida noción de k-anonimato, alcanzada mediante permutaciones y microagregación. Para este fin, definimos una novedosa función de distancia entre trayectorias con la cual desarrollamos dos métodos diferentes de anonimización de trayectorias.Els sistemes RFID permeten la identificació ràpida i automàtica d’etiquetes RFID a través d’un canal de comunicació sense fils. Aquestes etiquetes són dispositius amb cert poder de còmput i amb capacitat d’emmagatzematge de informació. Es per això que els objectes que porten una etiqueta RFID adherida permeten la lectura d’una quantitat rica i variada de dades que els descriuen i caracteritzen, com per exemple un codi únic d’identificació, el nom, el model o la data d’expiració. A més, aquesta informació pot ser llegida sense la necessitat d’un contacte visual entre el lector i l’etiqueta, la qual cosa agilitza considerablement els processos d’inventariat, identificació o control automàtic. Per a que l’ús de la tecnologia RFID es generalitzi amb èxit, es convenient complir amb diversos objectius: eficiència, seguretat i protecció de la privacitat. No obstant això, el disseny de protocols d’identificació segurs, privats i escalables, es un repte difícil d’abordar dades les restriccions computacionals de les etiquetes RFID i la seva naturalesa sense fils. Es per això que, en la present tesi, partim de protocols d’identificació segurs i privats, i mostrem com es pot aconseguir escalabilitat mitjançant una arquitectura distribuïda i col•laborativa. D’aquesta manera, la seguretat i la privacitat s’aconsegueixen mitjançant el propi protocol d’identificació, mentre que l’escalabilitat s’aconsegueix per mitjà de nous protocols col•laboratius que consideren la posició espacial i temporal de les etiquetes RFID. Independentment dels avenços en protocols d’identificació sense fils, existeixen atacs que poden passar exitosament qualsevol d’aquests protocols sense necessitat de conèixer o descobrir claus secretes vàlides, ni de trobar vulnerabilitats a les seves implantacions criptogràfiques. La idea d’aquestos atacs, coneguts com atacs de “relay”, consisteix en crear inadvertidament un pont de comunicació entre una etiqueta legítima i un lector legítim. D’aquesta manera, l’adversari utilitza els drets de l’etiqueta legítima per passar el protocol d’autentificació utilitzat pel lector. Es important tindre en compte que, dada la naturalesa sense fils dels protocols RFID, aquests tipus d’atacs representen una amenaça important a la seguretat en sistemes RFID. En aquesta dissertació proposem un nou protocol que, a més d’autentificació, realitza una revisió de la distància a la qual es troben el lector i l’etiqueta. Aquests tipus de protocols es coneixen com a “distance-boulding protocols”, els quals no prevenen aquests tipus d’atacs, però si que poden frustrar-los amb alta probabilitat. Per últim, afrontem els problemes de privacitat associats amb la publicació de informació recol•lectada a través de sistemes RFID. En concret, ens concentrem en dades de mobilitat, que també poden ser proveïdes per altres sistemes àmpliament utilitzats tals com el sistema de posicionament global (GPS) i el sistema global de comunicacions mòbils. La nostra solució es basa en la coneguda noció de privacitat “k-anonymity” i parcialment en micro-agregació. Per a aquesta finalitat, definim una nova funció de distància entre trajectòries amb la qual desenvolupen dos mètodes diferents d’anonimització de trajectòries.Radio Frequency Identification (RFID) is a technology aimed at efficiently identifying and tracking goods and assets. Such identification may be performed without requiring line-of-sight alignment or physical contact between the RFID tag and the RFID reader, whilst tracking is naturally achieved due to the short interrogation field of RFID readers. That is why the reduction in price of the RFID tags has been accompanied with an increasing attention paid to this technology. However, since tags are resource-constrained devices sending identification data wirelessly, designing secure and private RFID identification protocols is a challenging task. This scenario is even more complex when scalability must be met by those protocols. Assuming the existence of a lightweight, secure, private and scalable RFID identification protocol, there exist other concerns surrounding the RFID technology. Some of them arise from the technology itself, such as distance checking, but others are related to the potential of RFID systems to gather huge amount of tracking data. Publishing and mining such moving objects data is essential to improve efficiency of supervisory control, assets management and localisation, transportation, etc. However, obvious privacy threats arise if an individual can be linked with some of those published trajectories. The present dissertation contributes to the design of algorithms and protocols aimed at dealing with the issues explained above. First, we propose a set of protocols and heuristics based on a distributed architecture that improve the efficiency of the identification process without compromising privacy or security. Moreover, we present a novel distance-bounding protocol based on graphs that is extremely low-resource consuming. Finally, we present two trajectory anonymisation methods aimed at preserving the individuals' privacy when their trajectories are released

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

CAN CITYWIDE MUNICIPAL WIFI BE A FEASIBLE SOLUTION FOR LOCAL BROADBAND ACCESS IN THE US? AN EMPIRICAL EVALUATION OF A TECHNO-ECONOMIC MODEL

Citywide wireless fidelity (WiFi) offers an opportunity for municipalities and BISPs to break through the duopoly broadband market structure that is prevalent in the US. Although municipal WiFi offers low deployment cost, short building time, high capacity, and wide coverage, the competition from the local broadband market makes it difficult to be self-sustainable from public Internet access revenues. Therefore, it is interesting and useful not only to discuss the demographic features of existing WiFi projects but also to evaluate what is necessary for them to be economically sustainable. We propose to study these questions by building a techno-economic model to determine features, sustainability, and necessary subsidy of citywide WiFi for local broadband access. We evaluate this model with data from several existing projects.In order to gain insight from previous experience and to evaluate the feasibility of citywide WiFi, we carried this research out in three steps. The first, we undertook a systematic study to analyze all existing and operating citywide WiFi projects in the US. We were interested in identifying what key geo-demographic differences exist between WiFi cities and non-WiFi cities, and how private ISPs and municipalities implemented citywide projects with various business models and strategies. Next, we built a model linking access point density and network coverage, and used this to build a techno-economic model of municipal WiFi. Finally, we evaluated the effectiveness of the model using existing projects identified in the empirical study and determined how much subsidy could be reasonable from municipality to make WiFi projects sustainable. The outcome of this research is designed to assist policy makers, municipalities, and WiFi ISPs in evaluating, designing and implementing a sustainable project

WLAN-paikannuksen elinkaaren tukeminen

The advent of GPS positioning at the turn of the millennium provided consumers with worldwide access to outdoor location information. For the purposes of indoor positioning, however, the GPS signal rarely penetrates buildings well enough to maintain the same level of positioning granularity as outdoors. Arriving around the same time, wireless local area networks (WLAN) have gained widespread support both in terms of infrastructure deployments and client proliferation. A promising approach to bridge the location context then has been positioning based on WLAN signals. In addition to being readily available in most environments needing support for location information, the adoption of a WLAN positioning system is financially low-cost compared to dedicated infrastructure approaches, partly due to operating on an unlicensed frequency band. Furthermore, the accuracy provided by this approach is enough for a wide range of location-based services, such as navigation and location-aware advertisements. In spite of this attractive proposition and extensive research in both academia and industry, WLAN positioning has yet to become the de facto choice for indoor positioning. This is despite over 20 000 publications and the foundation of several companies. The main reasons for this include: (i) the cost of deployment, and re-deployment, which is often significant, if not prohibitive, in terms of work hours; (ii) the complex propagation of the wireless signal, which -- through interaction with the environment -- renders it inherently stochastic; (iii) the use of an unlicensed frequency band, which means the wireless medium faces fierce competition by other technologies, and even unintentional radiators, that can impair traffic in unforeseen ways and impact positioning accuracy. This thesis addresses these issues by developing novel solutions for reducing the effort of deployment, including optimizing the indoor location topology for the use of WLAN positioning, as well as automatically detecting sources of cross-technology interference. These contributions pave the way for WLAN positioning to become as ubiquitous as the underlying technology.GPS-paikannus avattiin julkiseen käyttöön vuosituhannen vaihteessa, jonka jälkeen sitä on voinut käyttää sijainnin paikantamiseen ulkotiloissa kaikkialla maailmassa. Sisätiloissa GPS-signaali kuitenkin harvoin läpäisee rakennuksia kyllin hyvin voidakseen tarjota vastaavaa paikannustarkkuutta. Langattomat lähiverkot (WLAN), mukaan lukien tukiasemat ja käyttölaitteet, yleistyivät nopeasti samoihin aikoihin. Näiden verkkojen signaalien käyttö on siksi alusta asti tarjonnut lupaavia mahdollisuuksia sisätilapaikannukseen. Useimmissa ympäristöissä on jo valmiit WLAN-verkot, joten paikannuksen käyttöönotto on edullista verrattuna järjestelmiin, jotka vaativat erillisen laitteiston. Tämä johtuu osittain lisenssivapaasta taajuusalueesta, joka mahdollistaa kohtuuhintaiset päätelaitteet. WLAN-paikannuksen tarjoama tarkkuus on lisäksi riittävä monille sijaintipohjaisille palveluille, kuten suunnistamiselle ja paikkatietoisille mainoksille. Näistä lupaavista alkuasetelmista ja laajasta tutkimuksesta huolimatta WLAN-paikannus ei ole kuitenkaan pystynyt lunastamaan paikkaansa pääasiallisena sisätilapaikannusmenetelmänä. Vaivannäöstä ei ole puutetta; vuosien saatossa on julkaistu yli 20 000 tieteellistä artikkelia sekä perustettu useita yrityksiä. Syitä tähän kehitykseen on useita. Ensinnäkin, paikannuksen pystyttäminen ja ylläpito vaativat aikaa ja vaivaa. Toiseksi, langattoman signaalin eteneminen ja vuorovaikutus ympäristön kanssa on hyvin monimutkaista, mikä tekee mallintamisesta vaikeaa. Kolmanneksi, eri teknologiat ja laitteet kilpailevat lisenssivapaan taajuusalueen käytöstä, mikä johtaa satunnaisiin paikannustarkkuuteen vaikuttaviin tietoliikennehäiriöihin. Väitöskirja esittelee uusia menetelmiä joilla voidaan merkittävästi pienentää paikannusjärjestelmän asennuskustannuksia, jakaa ympäristö automaattisesti osiin WLAN-paikannusta varten, sekä tunnistaa mahdolliset langattomat häiriölähteet. Nämä kehitysaskeleet edesauttavat WLAN-paikannuksen yleistymistä jokapäiväiseen käyttöön

Level based sampling techniques for energy conservation in large scale wireless sensor networks

As the size and node density of wireless sensor networks (WSN) increase,the energy conservation problem becomes more critical and the conventional methods become inadequate. This dissertation addresses two different problems in large scale WSNs where all sensors are involved in monitoring,but the traditional practice of periodic transmissions of observations from all sensors would drain excessive amount of energy. In the first problem,monitoring of the spatial distribution of a two dimensional correlated signal is considered using a large scale WSN. It is assumed that sensor observations are heavily affected by noise. We present an approach that is based on detecting contour lines of the signal distribution to estimate the spatial distribution of the signal without involving all sensors in the network. Energy efficient algorithms are proposed for detecting and tracking the temporal variation of the contours. Optimal contour levels that minimize the estimation error and a practical approach for selection of contour levels are explored. Performance of the proposed algorithm is explored with different types of contour levels and detection parameters. In the second problem,a WSN is considered that performs health monitoring of equipment from a power substation. The monitoring applications require transmissions of sensor observations from all sensor nodes on a regular basis to the base station,which is very costly in terms of communication cost. To address this problem,an efficient sampling technique using level-crossings (LCS) is proposed. This technique saves communication cost by suppressing transmissions of data samples that do not convey much information. The performance and cost of LCS for several different level-selection schemes are investigated. The number of required levels and the maximum sampling period for practical implementation of LCS are studied. Finally,in an experimental implementation of LCS with MICAzmote,the performance and cost of LCS for temperature sensing with uniform,logarithmic and a combined version of uniform and logarithmically spaced levels are compared with that using periodic sampling