498 research outputs found

    Realising context-sensitive mobile messaging

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    Mobile technologies aim to assist people as they move from place to place going about their daily work and social routines. Established and very popular mobile technologies include short-text messages and multimedia messages with newer growing technologies including Bluetooth mobile data transfer protocols and mobile web access.Here we present new work which combines all of the above technologies to fulfil some of the predictions for future context aware messaging. We present a context sensitive mobile messaging system which derives context in the form of physical locations through location sensing and the co-location of people through Bluetooth familiarity

    Advanced signal processing techniques for WiFi-based Passive Radar for short-range surveillance

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    In this work, advanced signal processing techniques for a Passive Radar (PR) based on WiFi transmissions are considered. The possibility to exploit such a ubiquitous and accessible source is shown to be an appropriate choice for the detection, localization and imaging of vehicles, people and aircrafts within short ranges in both outdoor and indoor environments

    Indoor Localization Using Wi-Fi Signals

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    RÉSUMÉ Plusieurs approches ont été développées pour localiser des appareils mobiles à l'intérieur de bâtiments d’une façon précise. Certaines donnent une précision de moins d'un mètre, mais elles nécessitent des infrastructures et du matériel spécifiques. D'autres utilisent une infrastructure qui est déjà déployée, mais donnent une position avec une précision inférieure. Dans ce mémoire, nous proposons plusieurs méthodes de positionnement basées sur les mesures de l'intensité du signal reçu d'une infrastructure Wi-Fi existant. Le but de ces méthodes de positionnement est de localiser le plus précisément possible l'emplacement du dispositif mobile utilisé. La première méthode de positionnement que nous proposons transforme la puissance du signal reçue en une entité appelée signature. Cette entité caractérise chaque emplacement de l'environnement où la localisation doit être effectuée. Pour localiser l'appareil mobile, la signature calculée est jumelée avec les signatures de référence les plus représentatives et qui sont déjà enregistrées dans une base de données. Dans ce mémoire, nous proposons deux approches pour produire les signatures de référence: une empirique et une théorique. La deuxième méthode de positionnement que nous proposons dans ce mémoire est de localiser les appareils mobiles en utilisant la différence entre les mesures de puissance de signaux reçus. On a appelé cette méthode la différence de puissances des signaux reçues (RSSD). Cette méthode consiste à convertir la différence de puissances des signaux reçues en des distances et d’utiliser ces distances pour estimer la position des appareils mobiles. Ensuite, nous décrivons les expériences qui nous ont conduits à développer la méthode de traitement du signal et les algorithmes de localisation. Les algorithmes et les méthodes proposés ont conduit à un système de localisation précis qui atteint 2 mètres de précision dans 90% des cas. Les résultats actuels des systèmes proposés montrent que les emplacements estimés sont précis (moins de 2 mètres) dans un environnement fermé en utilisant la méthode des signatures et une localisation précise dans les espaces ouverts en utilisant la méthode de la RSSD. Certains endroits critiques ont besoin de plus de collecte de données et plus d'informations sur l'environnement pour atteindre le même niveau de précision. Les résultats obtenus sont décrits et discutés à l’aide de cartes et de statistiques.----------ABSTRACT Several approaches have been developed to provide an accurate estimation of the position of mobile devices inside buildings. Some of them give a precision of less than one meter but they require special infrastructure and materials. Some others use an infrastructure that is already deployed but gives a position with lower precision. In this thesis, we propose several positioning methods based on the received signal strength (RSS) measurements of an existing Wi-Fi infrastructure. The aim of these positioning methods is to locate a mobile device as accurately as possible. The first method that we propose transforms the RSS to an entity called signature. This entity characterises each location of the environment where the localization should be performed. This computed signature is matched with the most representative reference signatures already recorded in a database in order to locate the mobile device. In this thesis, we propose two approaches to produce the reference signatures: an empirical and a theoretical one. The second method that we propose in this thesis is about locating the mobile devices using the difference between the received signals strength measurements. We call this method the received signal strength difference (RSSD) method. We then describe the experiments that led us to develop the signal processing method and the localization algorithms. The algorithm proposed led to an accurate localization system that reaches 2 meters of accuracy in 90% of the cases. Current results of the proposed systems show that the estimated locations are accurate (less than 2 meters) in closed environments when using the fingerprinting method and in open spaces when using the RSSD method. Some critical locations need more collected data and more information about the environment to reach the same level of accuracy. The results obtained are described and discussed using maps and statistics

    Internet of things for disaster management: state-of-the-art and prospects

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    Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster's occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and flexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems. © 2013 IEEE

    Ag-IoT for crop and environment monitoring: Past, present, and future

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    CONTEXT: Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production. Growers could make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Traditionally, data collection in agricultural fields, which largely relies on human labor, can only generate limited numbers of data points with low resolution and accuracy. During the last two decades, crop monitoring has drastically evolved with the advancement of modern sensing technologies. Most importantly, the introduction of IoT (Internet of Things) into crop, soil, and microclimate sensing has transformed crop monitoring into a quantitative and data-driven work from a qualitative and experience-based task. OBJECTIVE: Ag-IoT systems enable a data pipeline for modern agriculture that includes data collection, transmission, storage, visualization, analysis, and decision-making. This review serves as a technical guide for Ag-IoT system design and development for crop, soil, and microclimate monitoring. METHODS: It highlighted Ag-IoT platforms presented in 115 academic publications between 2011 and 2021 worldwide. These publications were analyzed based on the types of sensors and actuators used, main control boards, types of farming, crops observed, communication technologies and protocols, power supplies, and energy storage used in Ag-IoT platforms

    WLAN-paikannuksen elinkaaren tukeminen

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    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

    Bayesian algorithms for mobile terminal positioning in outdoor wireless environments

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