GNL: GeoFencing Based Smart Outdoor Navigation and Localization

Navigation is a technique used by humans to construct a plan to help them travel within a place using instruments or maps. Navigation in the modern age is done using various electronic systems which provide a real-time map of the place and the step-by-step directions to the desired destination. The technology widely used today is GPS i.e. Global Positioning System. Outdoor navigation using Google maps, here maps or safari is a common go-to for the users but the problem is the map provided by these companies just has an overview of the place and not the detailed information. The GNL approach which authors have used in this paper focuses on the navigation and localization of the gated environment so that the person living and visiting the area will get familiar with the area and understand the area very well. The web app that authors have designed can be used for the College Campus, Fairs, open museums, etc. Comparative analysis of the web app-based approach is done with an existing one. The Presented approach will not only help you in navigation but also provide you with information about the POI (Point of Interests) of those visiting places. The Geofence mechanism will help users to navigate and get information about the area. The aim is to give the user the maximum information about the place with secured transfer of information and better localization. The authors have tested the approach on the real testbed in the gated society and it provides good results for what it promises

Indoor Positioning and Navigating System Application Using Wi-Fi with Fingerprinting Method and Weighted K-Nearest Neighbor Algorithm: English

The need for accurate indoor location determination, object tracking, digital maps and indoor travel routes is increasing along with the construction of buildings that have complex and spacious layouts. The current Global Positioning System navigation system is only effective for outdoor use. However, when used indoors it becomes inaccurate due to factors such as signal attenuation and multipath caused by wall obstructions in the building. This study designed an application of Indoor Positioning and Navigating System Using Wi-Fi with Fingerprinting method and Weighted K-Nearest Neighbor algorithm. In the design process, it is necessary to create a fingerprinting database by considering the number of Access points and environmental conditions. Based on the results of the study, the location results of the application show that from floors 1,2, and 3. Floor 1 has a room accuracy result of 89% and a point accuracy of 86% with an average deviation of 1.42 px or 0.9 m, floor 2 has room accuracy results. of 65% and a point accuracy of 70% with an average deviation of 2.43 px or 1.7 m, and the 3rd floor has a room accuracy of 86% and a point accuracy of 68% with an average deviation of 2.27 or 1.5 m. Based on the data above, this application is proven to be able to detect the position of someone in the room with a success percentage on the 1st floor by 90%, the 2nd floor by 55%, and the 3rd floor by 80%

FID: Function Modeling-based Data-Independent and Channel-Robust Physical-Layer Identification

Trusted identification is critical to secure IoT devices. However, the limited memory and computation power of low-end IoT devices prevent the direct usage of conventional identification systems. RF fingerprinting is a promising technique to identify low-end IoT devices since it only requires the RF signals that most IoT devices can produce for communication. However, most existing RF fingerprinting systems are data-dependent and/or not robust to impacts from wireless channels. To address the above problems, we propose to exploit the mathematical expression of the physical-layer process, regarded as a function $\mathbf{\mathcal{F}(\cdot)}$, for device identification. $\mathbf{\mathcal{F}(\cdot)}$ is not directly derivable, so we further propose a model to learn it and employ this function model as the device fingerprint in our system, namely $\mathcal{F}$ID. Our proposed function model characterizes the unique physical-layer process of a device that is independent of the transmitted data, and hence, our system $\mathcal{F}$ID is data-independent and thus resilient against signal replay attacks. Modeling and further separating channel effects from the function model makes $\mathcal{F}$ID channel-robust. We evaluate $\mathcal{F}$ID on thousands of random signal packets from $33$ different devices in different environments and scenarios, and the overall identification accuracy is over $99\%$.Comment: Accepted to INFOCOM201

Indoor Positioning for BIM

Building Informational Modeling (BIM) is very popular in the construction industry in Norway today, and Omega 365 has created a suite of tools for BIM, including a 3D visualising tool for 3D models of buildings, called a BIMViewer. This tool exists in multiple forms, and one of them is an app for mobile phones, which construction workers carry with them on construction sites. When determining one's own position in the BIMViewer, it may take time to find and select the correct position. This study aims to create a feature for the BIMViewer using new technology, IEEE802.11mc and comparing it with an old method, Wi-Fi received signal strength (RSS) with the Log Distance Path Loss model. In addition, GPS was tried in order to prove it was not usable for this use case and in order to compare it with the other two methods. The main goal is to find a method that is cheap for clients to implement in regards to equipment and installation, but is precise enough to provide a good user experience. Three experiments were conducted for this study, one using only GPS and two for the other two methods. One experiment used only a single floor and the other used two floors. Both of these experiments used only 6 access points and were conducted at NyeSUS, the new hospital in Stavanger which was an active construction zone during the experiments. The experiments showed that GPS was a bad choice for the use case and that both the other methods were usable. The round trip time (RTT) method, which used the IEEE802.11mc measurements was more precise than the RSS method, however suffered from the need for more access points than the RSS method. This study concludes that both the RTT and the RSS methods may be usable, however some improvements would be needed for a truly good user experience. The study also suggests that a mix of the two methods may be beneficial

Outdoor-Indoor tracking systems through geomatic techniques: data analysis for marketing and safety management

Negli ultimi decenni, l'utilizzo di sistemi di gestione delle informazioni nel trattamento dei dati edilizi ha portato a cambiamenti radicali nei metodi di produzione, documentazione e archiviazione dei dati. Dato il crescente interesse per i dati e la loro gestione, l'obiettivo di questa tesi è quello di creare un flusso di lavoro efficace e chiaro a partire dai rilievi geomatici in un'ottica di miglioramento dei dati raccolti sul territorio, sugli edifici circostanti e su quelli relativi al comportamento umano, in modo che possano essere meglio sfruttati e integrati in modelli di gestione intelligenti. Come primo passo, questa tesi mira a comprendere i limiti dell'interoperabilità e dell'integrazione dei dati nei GIS. Per promuovere l'interoperabilità dei dati GIS, è necessario analizzare i metodi di conversione nei diversi modelli di archiviazione dei dati, come CityGML e IndoorGML, definendo un dominio ontologico. Questo ha portato alla creazione di un nuovo modello arricchito, basato sulle connessioni tra i diversi elementi del modello urbano in GIS. Il secondo passo consiste nel raccogliere tutti i dati tradotti in un database a grafo sfruttando il web semantico. Il risultato offrirà vantaggi sostanziali durante l'intero ciclo di vita del progetto. Questa metodologia può essere applicata anche al patrimonio culturale, dove la gestione delle informazioni gioca un ruolo fondamentale. Un altro lavoro di ricerca è stato quello di sviluppare un sistema di gestione SMART per le attività di conservazione dei borghi storici attraverso la gestione di tipologie eterogenee di dati, dal rilievo alla documentazione tecnica. Il flusso di lavoro è stato strutturato come segue: (i) acquisizione dei dati; (ii) modellazione 3D; (iii) modellazione della conoscenza; (iv) modellazione della gestione SMART. Questa ricerca apre la strada allo sviluppo di una piattaforma web in cui importare i dati GIS per un approccio di digital twin. Tutte le ricerche svolte fino a questo punto sono state finalizzate a comprendere la capacità di creare modelli e sistemi informativi intelligenti per capire la fattibilità di ospitare dati eterogenei che potrebbero essere inclusi in futuro. Il passo successivo consiste nel comprendere il comportamento umano in uno spazio. Finora sono pochi i lavori di ricerca che si occupano di sistemi di mappatura e posizionamento che tengono conto sia degli spazi esterni che di quelli interni. Questo argomento, anche se ha pochi articoli di ricerca, rappresenta un aspetto cruciale per molte ragioni, soprattutto quando si tratta di gestire la sicurezza degli edifici danneggiati. Angelats e il suo gruppo di ricerca al CTTC hanno lavorato su questo aspetto, fornendo un sistema in grado di seguire in tempo reale le persone dall'esterno all'interno di spazi chiusi e viceversa. L'uso di sensori GNSS combinato con l'odometria inerziale visiva fornisce una traiettoria continua senza perdere il percorso seguito dall'utente monitorato. Una parte di questa tesi si è concentrata sul miglioramento della traiettoria finale ottenuta con il sistema appena descritto, effettuando test sulla traiettoria esterna del GNSS per capire il comportamento della traiettoria quando si avvicina agli edifici o quando l'utente si sposta in indoor. L'ultimo aspetto su cui si concentrerà la tesi è il tracciamento delle persone in ambienti chiusi. Il comportamento umano è al centro di numerosi studi in diversi campi, come quello scientifico, sociale ed economico. A differenza del precedente caso di studio sul tracciamento delle persone in aree esterne/interne, l'obiettivo è stato quello di raccogliere informazioni sul posizionamento dinamico delle persone in ambienti indoor, sulla base del segnale WiFi. Verrà effettuata una breve analisi dei dati per dimostrare il corretto funzionamento del sistema, per sottolineare l'importanza della conoscenza dei dati e l'uso che se ne può fare.In the last decades, the use of information management systems in the building data processing led to radical changes to the methods of data production, documentation and archiving. Given the ever-increasing interest in data and their management, the aim of this thesis is to create an effective and clear workflow starting from geomatic surveys in a perspective of improving the collected data on the territory, surrounding buildings and those related to human behaviour so they can be better exploited and integrated into smart management models As first step this thesis aims to understand the limits of data interoperability and integration in GIS filed. Before that, the data must be collected as raw data, then processed and interpret in order to obtain information. At the end of this first stage, when the information is well organized and can be well understanded and used it becomes knowledge. To promote the interoperability of GIS data, it is necessary at first to analyse methods of conversion in different data storage models such as CityGML and IndoorGML, defining an ontological domain. This has led to the creation of a new enriched model, based on connections among the different elements of the urban model in GIS environment, and to the possibility to formulate queries based on these relations. The second step consists in collecting all data translated into a specific format that fill a graph database in a semantic web environment, while maintaining those relationships. The outcome will offer substantial benefits during the entire project life cycle. This methodology can also be applied to cultural heritage where the information management plays a key role. Another research work, was to develop a SMART management system for preservation activities of historical villages through the management of heterogeneous types of data, from the survey to the technical documentation. The workflow was structured as follows: (i) Data acquisition; (ii) 3D modelling; (iii) Knowledge modelling; (iv) SMART management modelling. This research paves the way to develop a web platform where GIS data would be imported for a digital twin approach. All the research done up to this point was to understand the capability of creating smart information models and systems in order to understand the feasibility to host heterogeneous data that may be included in the future. The next step consist of understanding human behaviour in a space. So far only a few research papers are addressed towards mapping and positioning systems taking into account both outdoor and indoor spaces. This topic, even though it has few research articles, represents a crucial aspect for many reasons, especially when it comes to safety management of damaged building. Angelats and his research team at CTTC have been working on this aspect providing a system able to track in real time people from outdoor to indoor areas and vice-versa. The use of GNSS sensors combined with Visual Inertial Odometry provide a continuous trajectory without losing the path followed by the monitored user. A part of this thesis focused on enhancing the final trajectory obtained with the described system above, carrying out tests on the outdoor trajectory of GNSS in order to understand behaviour of the trajectory when it gets close to buildings or when the user moves indoor. The last aspect this thesis will focus on is the tracking of people indoor. Human behaviour is at the centre of several studies in different fields such as scientific subjects, social and economics. Differently from the previous case study of tracking people in outdoor/indoor areas, the scope was to collect information about the dynamic indoor positioning of people, based on the WiFi signal. A brief analysis of the data will be made to demonstrate the correct functioning of the system, to emphasise the importance of data knowledge and the use that can be made of it

Autonome Instrumentierung von Altbergbau durch einen mobilen Manipulator

Im Fokus dieser Arbeit steht die Konzeption, Entwicklung und Erprobung eines autonomen Roboters zur Instrumentierung eines untertägigen Bergwerks. Der exemplarische Anwendungsfall umfasst das selbstständige Absetzen intelligenter Sensorstationen durch einen Roboterarm. Der Roboter ist einer der ersten mobilen Manipulatoren für den langfristigen Einsatz unter Tage. Ziel ist es, die Sicherheit für den Bergmann zu erhöhen, indem in gefährlichen Situationen der mobile Manipulator als echte Alternative zur Verfügung steht. Das fordert von dem Roboter selbstständiges und adaptives Handeln in einer Komplexität, die mobile Manipulatoren bisher lediglich in strukturierten Umgebungen leisten. Exemplarisch dafür ist das Platzieren von Technik im Altbergbau - Dunkelheit, Nässe und enge Querschnitte gestalten dies sehr herausfordernd. Der Roboter nutzt seine anthropomorphe Hand, um verschiedene Objekte abzusetzen. Das sind im konkreten Fall Sensorboxen, die diese Arbeit für die Instrumentierung des Bergwerks vorschlägt. Wichtig ist, dass das Absetzen autonom geschieht. Der Roboter trifft die Entscheidungen, wo er etwas platziert, welche Trajektorie sein Arm wählt und welchen Planungsalgorithmus er nutzt, vollkommen selbstständig. In dem Zusammenhang entwirft diese Dissertation eine variable Absetzroutine. Der mobile Manipulator baut dafür ein Kollisionsmodell der Umgebung auf, sucht eine geeignete Absetzposition, greift ein vordefiniertes Objekt und platziert dies im Bergwerk. Sicherheit und Robustheit stehen dabei an vorderster Stelle. Entsprechend schließt die Absetzroutine nach dem Absetzen nicht ab, sondern führt eine unabhängige Überprüfung durch. Dabei vergleicht der mobile Manipulator über Sensoren die wahrgenommene mit der angestrebten Objektposition. Hier kommen auf Deep Learning basierende Methoden zum Einsatz, die eine Überprüfung auch in vollkommener Dunkelheit erlauben. In insgesamt 60 Experimenten gelingt das Absetzen in 97% der Fälle mit einer Genauigkeit im Zentimeterbereich. Dabei beschränkt sich diese Evaluierung nicht auf das untertägige Bergwerk, sondern wertet auch Experimente in strukturierten und offenen Umgebungen aus. Diese Breite erlaubt eine qualitative Diskussion von Aspekten wie: Autonomie, Sicherheit und Einfluss der Umgebung auf das Verfahren. Das Ergebnis ist die Erkenntnis, dass der hier vorgestellte Roboter die Lücke zwischen Untertagerobotern und den mobilen Manipulatoren aus Industrieanwendungen schließt. Er steht in gefährlichen Situationen als Alternative zur Verfügung.:Inhaltsverzeichnis Abbildungsverzeichnis Tabellenverzeichnis Abkürzungsverzeichnis Notation Variablenverzeichnis 1. Einleitung 1.1. Motivation 1.2. Forschungsfrage und Beitrag der Arbeit 1.3. Aufbau der Arbeit 2. Forschungstrends bei mobilen Manipulatoren und Untertagerobotern 2.1. Mobile Manipulatoren in verschiedenen Einsatzszenarien 2.2. Wettbewerbe mobiler Manipulatoren und Trends im Forschungsgebiet 2.3. Hard- und Software Komponenten für mobile Manipulatoren 2.4. Zusammenfassung 3. Aufbau von Julius - dem Roboter für den Einsatz im Altbergbau 3.1. Umgebungsbedingungen im untertägigen Altbergbau 3.2. Physischer Aufbau des Roboters 3.3. Softwaretechnische Grundlagen für ein autonomes Handeln 3.4. Zusammenfassung 4. Entwurf der autonomen Absetzroutine für Julius 4.1. Planen von Armbewegungen 4.2. Umgebungsmodell detaillieren 4.3. Bodenfläche identifizieren 4.4. Absetzposition berechnen 4.5. SSB greifen 4.6. Absetzrotation festlegen 4.7. SSB absetzen 4.8. Absetzpose überprüfen 4.9. Zusammenfassung 5. Experimentelle Validierung von Julius und der Absetzroutine 5.1. Beschreibung des Experiments und der generellen Rahmenbedingungen 5.2. Referenzexperimente im Innenbereich 5.3. Experimente im Außenbereich 5.4. Experimente im Forschungs- und Lehrbergwerk 5.5. Diskussion 5.6. Zusammenfassung 6. Zusammenfassung 6.1. Erkenntnisse dieser Arbeit 6.2. Fazit 6.3. Ausblick Literatur Anhang A. Berechnung der Absetzrotation B. Übersicht technischer Daten C. Weiterführende Abbildungen D. Messdate

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