TY - JOUR A1 - Bullmann, Markus A1 - Fetzer, Toni A1 - Ebner, Frank A1 - Ebner, Markus A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Comparison of 2.4 GHz WiFi FTM- and RSSI-Based Indoor Positioning Methods in Realistic Scenarios JF - Sensors Y1 - 2020 U6 - https://doi.org/10.3390/s20164515 SN - 1424-8220 VL - 20 IS - 16 ER - TY - JOUR A1 - Köpping, Lukas A1 - Ebner, Frank A1 - Grzegorzek, Marcin A1 - Deinzer, Frank T1 - Indoor localization using step and turn detection together with floor map information JF - FHWS science journal N2 - In this work we present a method to estimate an indoor position with the help of smartphone sensors and without any knowledge of absolute positioning systems like Wi-Fi signals. Our system uses particle filtering to solve the recursive state estimation problem of finding the position of a pedestrian. We show how to integrate the information of the previous state into the weight update step and how the observation data can help within the state transition model. High positional accuracy can be achieved by only knowing that the pedestrian makes a foot step or changes her direction together with floor map information. KW - particle filter KW - step detection KW - turn detection Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-976 VL - 2 (2014) IS - 1 SP - 40 EP - 49 ER - TY - CHAP A1 - Ebner, Frank A1 - Deinzer, Frank A1 - Koping, Lukas A1 - Grzegorzek, Marcin T1 - Robust self-localization using Wi-Fi, step/turn-detection and recursive density estimation T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2014) Y1 - 2014 U6 - https://doi.org/10.1109/IPIN.2014.7275537 SP - 627 EP - 635 ER - TY - CHAP A1 - Ebner, Frank A1 - Fetzer, Toni A1 - Köping, Lukas A1 - Grzegorzek, Marcin A1 - Deinzer, Frank T1 - Multi Sensor 3D Indoor Localisation T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015) Y1 - 2015 UR - https://ieeexplore.ieee.org/iel7/7336693/7346746/07346772.pdf SP - 1 EP - 11 ER - TY - JOUR A1 - Torres-Sospedra, Joaquín A1 - Jiménez, Antonio R. A1 - Knauth, Stefan A1 - Moreira, Adriano A1 - Beer, Yair A1 - Fetzer, Toni A1 - Ta, Viet-Cuong A1 - Montoliu, Raul A1 - Seco, Fernando A1 - Mendoza-Silva, Germán M. A1 - Belmonte, Oscar A1 - Koukofikis, Athanasios A1 - Nicolau, Maria João A1 - Costa, António A1 - Meneses, Filipe A1 - Ebner, Frank A1 - Deinzer, Frank A1 - Vaufreydaz, Dominique A1 - Dao, Trung-Kien A1 - Castelli, Eric T1 - The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work JF - Sensors Y1 - 2017 U6 - https://doi.org/10.3390/s17030557 SN - 1424-8220 VL - 17 IS - 3 ER - TY - JOUR A1 - Ebner, Frank A1 - Fetzer, Toni A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - On Wi-Fi Model Optimizations for Smartphone-Based Indoor Localization JF - ISPRS International Journal of Geo-Information Y1 - 2017 U6 - https://doi.org/10.3390/ijgi6080233 SN - 2220-9964 VL - 6 IS - 8 ER - TY - JOUR A1 - Fetzer, Toni A1 - Ebner, Frank A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Using Barometer for Floor Assignation within Statistical Indoor Localization JF - Sensors Y1 - 2023 U6 - https://doi.org/10.3390/s23010080 SN - 1424-8220 VL - 23 IS - 1 ER - TY - CHAP A1 - Bullmann, Markus A1 - Fetzer, Toni A1 - Ebner, Frank A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Fast Kernel Density Estimation Using Gaussian Filter Approximation T2 - 21st International Conference on Information Fusion, FUSION 2018, Cambridge, UK, July 10-13, 2018 Y1 - 2018 U6 - https://doi.org/10.23919/ICIF.2018.8455686 SP - 1233 EP - 1240 ER - TY - JOUR A1 - Fetzer, Toni A1 - Ebner, Frank A1 - Bullmann, Markus A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Smartphone-Based Indoor Localization within a 13th Century Historic Building JF - Sensors Y1 - 2018 U6 - https://doi.org/10.3390/s18124095 SN - 1424-8220 VL - 18 IS - 12 ER - TY - JOUR A1 - Ebner, Frank A1 - Schneider, Volker T1 - Analysis of web data compression and its impact on traffic and energy consumption JF - FHWS Science Journal N2 - While connection speeds are increasing slowly, some ISPs mention plans about possible traffic limitations in the near future which would keep internet traffic expensive. In addition, Green IT became more important especially over the last few years. Besides on-demand content like video live streams, HTTP traffic plays an important role. Thinking of textual web content, compression quickly comes to mind as a possibility to reduce traffic. The current HTTP/1.1 standard only provides gzip as an option for content encoding. HTTP/2.0 is under heavy development and numerous new algorithms have been established over the last few years. This paper analyzes HTTP traffic composition on a production server and concludes that about 50% is compressible. It further examines the effectiveness of custom and existing algorithms with regards to compression ratio, speed, and energy consumption. Our results show that gzip is a sound choice for web traffic but alternatives like LZ4 are faster and provide competitive compression ratios. Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-428 VL - 1 IS - 2 SP - 7 EP - 24 CY - Würzburg ER - TY - CHAP A1 - Ebner, F. A1 - Fetzer, T. A1 - Deinzer, Frank A1 - Grzegorzek, M. T1 - On Prior Navigation Knowledge in Multi Sensor Indoor Localisation T2 - International Conference on Information Fusion (FUSION 2016) Y1 - 2016 UR - https://www.researchgate.net/profile/Toni-Fetzer/publication/306118756_On_Prior_Navigation_Knowledge_in_Multi_Sensor_Indoor_Localisation/links/57da7d8508aeea195932334f/On-Prior-Navigation-Knowledge-in-Multi-Sensor-Indoor-Localisation.pdf ER - TY - CHAP A1 - Fetzer, T. A1 - Ebner, F. A1 - Köping, L. A1 - Grzegorzek, M. A1 - Deinzer, Frank T1 - Recovering From Sample Impoverishment in Context of Indoor Localisation T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2017) Y1 - 2017 UR - https://ieeexplore.ieee.org/iel7/8106926/8115856/08115863.pdf SP - 1 EP - 8 ER - TY - CHAP A1 - Fetzer, T. A1 - Ebner, F. A1 - Köping, L. A1 - Grzegorzek, M. A1 - Deinzer, Frank T1 - On Monte Carlo Smoothing in Multi Sensor Indoor Localisation T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016) Y1 - 2016 UR - https://ieeexplore.ieee.org/iel7/7738315/7743575/07743670.pdf ER - TY - CHAP A1 - Bullmann, Markus A1 - Fetzer, Toni A1 - Ebner, Markus A1 - Kastner, Steffen A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Data Driven Sensor Model for Wi-Fi Fine Timing Measurement T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022) Y1 - 2022 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9918111 ER - TY - CHAP A1 - Ebner, Markus A1 - Fetzer, Toni A1 - Bullmann, Markus A1 - Kastner, Steffen A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - PIPF: Proposal-Interpolating Particle Filter T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022) Y1 - 2022 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9918102 ER - TY - JOUR A1 - Fetzer, Toni A1 - Maier, Julian A1 - Ebner, Markus A1 - Bullmann, Markus A1 - Deinzer, Frank T1 - Digitales Spaghetti-Diagramm zur Laufweganalyse JF - wt Werkstattstechnik online Y1 - 2022 VL - 112 IS - 10/2022 SP - 727 EP - 731 ER - TY - CHAP A1 - Fetzer, Toni A1 - Bullmann, Markus A1 - Ebner, Markus A1 - Kastner, Steffen A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Interacting Multiple Model Particle Filter for Indoor Positioning Applications T2 - Proceedings of the 2023 International Technical Meeting of The Institute of Navigation Y1 - 2023 UR - https://www.researchgate.net/profile/Toni-Fetzer/publication/368485764_Interacting_Multiple_Model_Particle_Filter_for_Indoor_Positioning_Applications/links/63fa3e960d98a97717b975ae/Interacting-Multiple-Model-Particle-Filter-for-Indoor-Positioning-Applications.pdf ER - TY - JOUR A1 - Kastner, Steffen A1 - Ebner, Markus A1 - Bullmann, Markus A1 - Fetzer, Toni A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Magnetic Signature Sensor Model for Accurate Short-Distance Localization JF - 2022 IEEE Sensors Y1 - 2022 U6 - https://doi.org/10.1109/SENSORS52175.2022.9967176 SP - 1 EP - 4 ER - TY - BOOK A1 - Ebner, Frank T1 - Smartphone-based 3D indoor localization and navigation N2 - With the steadily increasing need and wish to travel, people often have to reach locations they have never been to before. Modern means of transportation, like cars, ships and planes, thus come equipped with onboard navigation systems, assisting with this task, based on the global positioning system (GPS), or a derivative. However, the navigation task is not solely limited to outdoor environments. Reaching the correct gate within an airport, finding a ward in an unknown hospital, or the auditorium within a new university, represent navigation problems as well. With the GPS requiring a direct line of sight towards the sky, it is unavailable for absolute location estimation indoors. Therefore, the question for suitable indoor navigation techniques arises. Besides localization accuracy, additional factors should be met for such a new system to become a success. It should be easy to set up and maintain, limiting required working hours and costs. Likewise, hardware for the users themselves should be cheap, and readily available. Due to the ubiquity of smartphones, these devices represent a desirable platform for pedestrians, backed by the variety of sensors installed in these devices. Within this work, smartphone-based pedestrian indoor localization and navigation is discussed in detail. This covers examining the suitability of several available sensors: step-detection using readings from the accelerometer, relative turn-detection utilizing the turn rates of the gyroscope, absolute heading estimations based on the magnetometer’s indications, and altitude evaluation from the barometer. While all aforementioned sensors do not require any additional infrastructure, thus suitable for all sorts of buildings, they only allow for relative location estimations. Absolute localization can utilize Wi-Fi, as it is supported by all smartphones, and most public buildings already contain the required infrastructure. Due to the behavior of radio signals, the smartphone’s current location can be approximated by examining signal strengths of nearby transmitters. This aspect is often utilized by Wi-Fi fingerprinting, which, however, requires a time consuming setup process. Therefore, an alternative is developed that allows for significantly faster setup times. Additionally, the building’s 3D floorplan is included, modeling potential pedestrian movements, limiting impossible walks to improve estimation results, and to provide routing towards a desired destination. For this, two spatial floorplan representations are derived and examined. All aforementioned aspects are hereafter combined probabilistically, using recursive density estimation based on the particle filter. This allows for fusioning all sensor observations while respecting their individual uncertainties, and the building’s floorplan as additional constraints. To summarize, the system described within this work covers probabilistic 3D pedestrian indoor localization, using commodity smartphones, contained sensors, a building’s existing infrastructure and floorplan, all combined by the particle filter to derive an indoor localization and navigation system that is easy to set up and maintain. N2 - Mit dem stetig zunehmenden Reisewunsch finden sich Menschen immer häufiger vor der Aufgabe, bislang unbekannte Orte zu erreichen. Moderne Transportmittel, wie Autos, Schiffe und Flugzeuge sind deshalb mit GPS-basierten Navigationssystemen ausgestattet, die hierbei unterstützen. Allerdings ist der Navigationsaspekt selten nur auf den Außenbereich beschränkt. Das richtige Gate im Flughafen zu finden, eine Station im Krankenhaus, oder den Hörsaal in der neuen Universität, ist oft ähnlich anspruchsvoll. Da das GPS jedoch eine direkte Sichtverbindung benötigt, steht dieses innerhalb von Gebäuden nicht zur Verfügung. Hier stellt sich deshalb die Frage nach geeigneten Alternativen. Für Neuentwicklungen müssen neben der Positionsgenauigkeit auch andere Aspekte berücksichtigt werden. Das System sollte nicht nur wartbar, sondern auch kostengünstig ausrollbar sein. Auch für die Nutzer sollten die Anschaffungskosten so gering wie möglich ausfallen. Smartphones stellen aufgrund ihrer Allgegenwärtigkeit und Vielzahl von Sensoren deshalb eine ideale Zielplattform dar. In dieser Arbeit werden verfügbare Sensoren auf ihre Tauglichkeit untersucht: Schritterkennung mittels Beschleunigungssensor, Laufrichtungsschätzung via Magnetometer, Laufrichtungsänderungen gemessen durch das Gyroskop, und Höhenbestimmung per Barometer. Diese Sensoren stellen zwar keinerlei Anforderungen an das Zielgebäude, liefern jedoch lediglich relative Informationen bzgl. möglicher Aufenthaltsorte. Eine absolute Positionsbestimmung wird über Wi-Fi ermöglicht, welches von allen Smartphones unterstützt wird und in den meisten öffentlichen Gebäuden verfügbar ist. Basierend auf dem Verhalten von Funksignalen lässt sich der aktuelle Standort des Smartphones aus den Signalstärken der nahegelegenen Access Points ableiten. In der Literatur wird hierfür häufig auf Fingerprinting zurückgegriffen, welches zwar genau, aber aufwendig in der Einrichtung ist. Deshalb wird eine Alternative erarbeitet, die die Einrichtungszeit und Kosten stark reduziert. Zusätzlich wird ein 3D Gebäudeplan verwendet, der mögliche und unmögliche Bewegungen von Fußgängern bestimmen, und die kürzeste Route zu einem gewünschten Ziel berechnen kann. Beides dient der Verbesserung der Vorhersagen des Gesamtsystems. Hierfür werden zwei verschiedene Repräsentationen des Gebäudeplans erzeugt und untersucht. Alle vorherigen Komponenten werden schließlich über rekursive Dichte-Schätzung mittels Partikel-Filter zusammengeführt. Mit dieser lassen sich alle Sensor Messungen inklusive ihrer Unsicherheiten kombinieren, und auch der Gebäudeplan kann als zusätzliche Rahmenbedingung integriert werden, um unmögliche Bewegungen auszufiltern. Zusammenfassend beschreibt diese Arbeit ein auf Wahrscheinlichkeitsrechnung basierendes 3D Lokalisations- und Navigations-System für Fußgänger in Gebäuden, das alle Informationen mittels Partikel Filter kombiniert, einfach einzurichten und zu warten ist. Vorausgesetzt werden lediglich ein Smartphone, eine vorhandene WLAN-Infrastruktur und ein Gebäudeplan. KW - floorplan KW - probalistic sensor fusion Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-19894 UR - https://doi.org/10.30819/5232 SN - 9783832586232 PB - Logos Verlag CY - Berlin ER - TY - JOUR A1 - Ebner, Markus A1 - Fetzer, Toni A1 - Bullmann, Markus A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand JF - Sensors Y1 - 2020 U6 - https://doi.org/10.3390/s20226559 SN - 1424-8220 VL - 20 IS - 22 ER -