Deep Learning Methods for Fingerprint-Based Indoor and Outdoor Positioning

Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold: First, a Convolutional Neural Network (CNN)-based method for localizing a smartwatch indoors using geomagnetic field measurements is presented. The proposed method was tested on real world data in an indoor environment composed of three corridors of different lengths and three rooms of different sizes. Experimental results show a promising location classification accuracy of 97.77% with a mean localization error of 0.14 meter (m). Second, a method that makes use of cellular signals emitting from a serving eNodeB to provide symbolic indoor positioning is presented. The proposed method utilizes Denoising Autoencoders (DAEs) to mitigate the effects of cellular signal loss. The proposed method was evaluated using real-world data collected from two different smartphones inside a representative apartment of eight symbolic spaces. Experimental results verify that the proposed method outperforms conventional symbolic indoor positioning techniques in various performance metrics. Third, an investigation is conducted to determine whether Variational Autoencoders (VAEs) and Conditional Variational Autoencoders (CVAEs) are able to learn the distribution of the minority symbolic spaces, for a highly imbalanced fingerprinting dataset, so as to generate synthetic fingerprints that promote enhancements in a classifier\u27s performance. Experimental results show that this is indeed the case. By using various performance evaluation metrics, the achieved results are compared to those obtained by two state-of-the-art oversampling methods known as Synthetic Minority Oversampling TEchnique (SMOTE) and ADAptive SYNthetic (ADASYN) sampling. Fourth, a novel dataset of outdoor location fingerprints is presented. The proposed dataset, named OutFin, addresses the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions which can constitute a high entry barrier for studies. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 Reference Points (RPs). Before OutFin was made available to the public, several experiments were conducted to validate its technical quality

Алгоритм локального позиціонування об'єкта на основі технології Bluetooth beacon

В роботі розроблено алгоритм локального позиціонування об'єкта на основі технології Bluetooth beacon за виміром RSS, з урахуванням критерію мінімальної прийнятої потужності. Мета та завдання. Підвищення точності локального позиціонування об’єкта на основі технології Bluetooth beacon за рахунок критерію мінімальної прийнятої потужності. Об’єкт дослідження. Процес локального позиціонування об’єкта в приміщенні на основі технології Bluetooth beacon. Предмет дослідження. Методи визначення локального позиціонування об’єкта. Методи дослідження. В роботі використовувалися методи статистичної теорії прийняття рішень, статистичного моделювання на ЕОМ і метод експериментального дослідження.The algorithm of local positioning of the object on the basis of Bluetooth beacon technology according to RSS measurement, taking into account the criterion of the minimum received power, is developed in the work. Purpose and objectives. Improve the accuracy of local positioning of the object based on Bluetooth beacon technology due to the criterion of minimum received power. Object of study. The process of locally positioning an object in a room based on Bluetooth beacon technology. Subject of study. Methods for determining the local positioning of an object. Research methods. The methods of statistical theory of decision-making, statistical modeling on a computer and the method of experimental research were used in the work

Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot

The always best positioned paradigm for mobile indoor applications

In this dissertation, methods for personal positioning in outdoor and indoor environments are investigated. The Always Best Positioned paradigm, which has the goal of providing a preferably consistent self-positioning, will be defined. Furthermore, the localization toolkit LOCATO will be presented, which allows to easily realize positioning systems that follow the paradigm. New algorithms were developed, which particularly address the robustness of positioning systems with respect to the Always Best Positioned paradigm. With the help of this toolkit, three example positioning-systems were implemented, each designed for different applications and requirements: a low-cost system, which can be used in conjunction with user-adaptive public displays, a so-called opportunistic system, which enables positioning with room-level accuracy in any building that provides a WiFi infrastructure, and a high-accuracy system for instrumented environments, which works with active RFID tags and infrared beacons. Furthermore, a new and unique evaluation-method for positioning systems is presented, which uses step-accurate natural walking-traces as ground truth. Finally, six location based services will be presented, which were realized either with the tools provided by LOCATO or with one of the example positioning-systems.In dieser Doktorarbeit werden Methoden zur Personenpositionierung im Innen- und Außenbereich von Gebäuden untersucht. Es wird das ,,Always Best Positioned” Paradigma definiert, welches eine möglichst lückenlose Selbstpositionierung zum Ziel hat. Weiterhin wird die Lokalisierungsplattform LOCATO vorgestellt, welche eine einfache Umsetzung von Positionierungssystemen ermöglicht. Hierzu wurden neue Algorithmen entwickelt, welche gezielt die Robustheit von Positionierungssystemen unter Berücksichtigung des ,,Always Best Positioned” Paradigmas angehen. Mit Hilfe dieser Plattform wurden drei Beispiel Positionierungssysteme entwickelt, welche unterschiedliche Einsatzgebiete berücksichtigen: Ein kostengünstiges System, das im Zusammenhang mit benutzeradaptiven öffentlichen Bildschirmen benutzt werden kann; ein sogenanntes opportunistisches Positionierungssystem, welches eine raumgenaue Positionierung in allen Gebäuden mit WLAN-Infrastruktur ermöglicht, sowie ein metergenaues Positionierungssystem, welches mit Hilfe einer Instrumentierung aus aktiven RFID-Tags und Infrarot-Baken arbeitet. Weiterhin wird erstmalig eine Positionierungsevaluation vorgestellt, welche schrittgenaue, natürliche Bewegungspfade als Referenzsystem einsetzt. Im Abschluss werden 6 lokationsbasierte Dienste vorgestellt, welche entweder mit Hilfe von LOCATO oder mit Hilfe einer der drei Beispiel-Positionierungssysteme entwickelt wurden

Planification visuelle et interactive d'interventions dans des environnements d'accélérateur de particules émettant des rayonnements ionisants

Les radiations sont omniprésentes. Elles ont de nombreuses applications dans des domaines variés: en médecine, elles permettent de réaliser des diagnostiques et de guérir des patients; en communication, tous les systèmes modernes utilisent des formes de rayonnements électromagnétiques; et en science, les chercheurs les utilisent pour découvrir la composition et la structure des matériaux, pour n'en nommer que quelques-unes. Concrètement, la radiation est un processus au cours duquel des particules ou des ondes voyagent à travers différents types de matériaux. La radiation peut être très énergétique, et aller jusqu'à casser les atomes de la matière ordinaire. Dans ce cas, on parlera de radiation ionisante. Il est communément admis que la radiation ionisante peut être bien plus nocif pour les êtres vivants que la radiation non ionisante. Dans cette dissertation, nous traiterons de la radiation ionisante. La radioactivité est le processus d'émission des radiations ionisantes. Elle existe sous forme naturelle, et est présente dans les sols, dans l'air et notre planète entière est bombardée en permanence de rayonnements cosmiques énergétiques. Depuis le début du XXe siècle, les chercheurs sont capables de créer artificiellement de la matière radioactive. Cette découverte a offert de multiples avancées technologiques, mais a eu également de lourdes conséquences pour l'humanité comme l'ont démontrés les évènements de Tchernobyl et de Fukushima ou d'autres accidents dans le monde médical. Cette dangerosité a conduit à l'élaboration d'un système de radioprotection. Dans la pratique, la radioprotection est principalement mise en œuvre en utilisant la méthode ALARA. Cette méthodologie consiste à justifier, optimiser et limiter les doses reçues. Elle est utilisée conjointement avec les limites légales. Le facteur d'optimisation est contraint par le fait que l'exposition volontaire d'un travailleur aux radiations lors d'une opération doit être plus bénéfique que si aucune intervention humaine n'était conduite dans une situation donnée. Dans le monde industriel et scientifique, il existe des infrastructures qui émettent des rayonnements ionisants. La plupart d'entre elles nécessitent des opérations de maintenance. Dans l'esprit du principe ALARA, ces interventions doivent être optimisées pour réduire l'exposition des travailleurs aux rayonnements ionisants. Cette optimisation ne peut pas être réalisée de manière automatique car la faisabilité des interventions nécessite dans tous les cas une évaluation humaine. La planification des interventions peut cependant être facilitée par des moyens techniques et scientifiques comme par exemple un outil informatique. Dans le contexte décrit ci-dessus, cette thèse regroupe des considérations techniques et scientifiques, et présente la méthodologie utilisée pour développer des outils logiciels pour la mise en œuvre de la radioprotection.Radiation is omnipresent. It has many interesting applications: in medicine, where it allows curing and diagnosing patients; in communication, where modern communication systems make use of electromagnetic radiation; and in science, where it is used to discover the structure of materials; to name a few. Physically, radiation is a process in which particles or waves travel through any kind of material, usually air. Radiation can be very energetic, in which case it can break the atoms of ordinary matter (ionization). If this is the case, radiation is called ionizing. It is known that ionizing radiation can be far more harmful to living beings than non-ionizing radiation. In this dissertation, we are concerned with ionizing radiation. Naturally occurring ionizing radiation in the form of radioactivity is a most natural phenomenon. Almost everything is radioactive: there is radiation emerging from the soil, it is in the air, and the whole planet is constantly undergoing streams of energetic cosmic radiation. Since the beginning of the twentieth century, we are also able to artificially create radio-active matter. This has opened a lot of interesting technological opportunities, but has also given a tremendous responsibility to humanity, as the nuclear accidents in Chernobyl and Fukushima, and various accidents in the medical world have made clear. This has led to the elaboration of a radiological protection system. In practice, the radiological protection system is mostly implemented using a methodology that is indicated with the acronym ALARA: As Low As Reasonably Achievable. This methodology consists of justifying, optimizing and limiting the radiation dose received. This methodology is applied in conjunction with the legal limits. The word "reasonably" means that the optimization of radiation exposure has to be seen in context. The optimization is constrained by the fact that the positive effects of an operation might surpass the negative effects caused by the radiation. Several industrial and scientific procedures give rise to facilities with ionizing radiation. Most technical and scientific facilities also need maintenance operations. In the spirit of ALARA, these interventions need to be optimized in terms of the exposure of the maintenace workers to ionizing radiation. This optimization cannot be automated since the feasibility of the intervention tasks requires human assessment. The intervention planning could however be facilitated by technical-scientific means, e.g. software tools. In the context sketched above, this thesis provides technical-scientific considerations and the development of technical-scientific methodologies and software tools for the implementation of radiation protection.In particular, this thesis addresses the need for an interactive visual intervention planning tool in the context of high energy particle accelerator facilities.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Performance and limits of KNN-based positioning methods for GSM networks over leaky feeder in underground tunnels

Localisation techniques have long been of major importance for safety systems and a lot of research has been conducted in the distributed computing field regarding its functionality and reliability. In the specific scenario of long yet narrow tunnels existing at CERN, localisation methods will enable a number of applications and processes to substantially reduce human intervention. In this article, we evaluate the use of fingerprinting techniques with GSM signal available throughout the LHC tunnel via a radiating cable and compare some methods to estimate the location. In the tests, 16 variants of the K-Nearest Neighbour algorithm, employing different distance weighting methods and fingerprint grouping functions, are taken into consideration and their performance is assessed with a specific rating algorithm. The existing GSM infrastructure and tunnel conditions seem to be favourable to the adoption of these fingerprinting methods. Nevertheless, significant variations in the signal have been observed which might be traced back to the presence of bulky equipment and different operational states of the accelerator. The performance limits of these fingerprinting methods are discussed for the current scenario and, based on that, an outlook for future research is given aiming at improving the system’s accuracy under such challenging conditions

CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen