@article{BullmannFetzerEbneretal., author = {Bullmann, Markus and Fetzer, Toni and Ebner, Frank and Ebner, Markus and Deinzer, Frank and Grzegorzek, Marcin}, title = {Comparison of 2.4 GHz WiFi FTM- and RSSI-Based Indoor Positioning Methods in Realistic Scenarios}, series = {Sensors}, volume = {20}, journal = {Sensors}, number = {16}, issn = {1424-8220}, doi = {10.3390/s20164515}, language = {en} } @article{KoeppingEbnerGrzegorzeketal.2014, author = {K{\"o}pping, Lukas and Ebner, Frank and Grzegorzek, Marcin and Deinzer, Frank}, title = {Indoor localization using step and turn detection together with floor map information}, series = {FHWS science journal}, volume = {2 (2014)}, journal = {FHWS science journal}, number = {1}, organization = {Hochschule f{\"u}r angewandte Wissenschaften W{\"u}rzburg-Schweinfurt}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-976}, pages = {40 -- 49}, year = {2014}, abstract = {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.}, language = {en} } @inproceedings{EbnerDeinzerKopingetal., author = {Ebner, Frank and Deinzer, Frank and Koping, Lukas and Grzegorzek, Marcin}, title = {Robust self-localization using Wi-Fi, step/turn-detection and recursive density estimation}, series = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2014)}, booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2014)}, doi = {10.1109/IPIN.2014.7275537}, pages = {627 -- 635}, language = {en} } @inproceedings{EbnerFetzerKoepingetal., author = {Ebner, Frank and Fetzer, Toni and K{\"o}ping, Lukas and Grzegorzek, Marcin and Deinzer, Frank}, title = {Multi Sensor 3D Indoor Localisation}, series = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015)}, booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015)}, pages = {1 -- 11}, language = {en} } @article{TorresSospedraJimenezKnauthetal., author = {Torres-Sospedra, Joaqu{\´i}n and Jim{\´e}nez, Antonio R. and Knauth, Stefan and Moreira, Adriano and Beer, Yair and Fetzer, Toni and Ta, Viet-Cuong and Montoliu, Raul and Seco, Fernando and Mendoza-Silva, Germ{\´a}n M. and Belmonte, Oscar and Koukofikis, Athanasios and Nicolau, Maria Jo{\~a}o and Costa, Ant{\´o}nio and Meneses, Filipe and Ebner, Frank and Deinzer, Frank and Vaufreydaz, Dominique and Dao, Trung-Kien and Castelli, Eric}, title = {The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work}, series = {Sensors}, volume = {17}, journal = {Sensors}, number = {3}, issn = {1424-8220}, doi = {10.3390/s17030557}, language = {en} } @article{EbnerFetzerDeinzeretal., author = {Ebner, Frank and Fetzer, Toni and Deinzer, Frank and Grzegorzek, Marcin}, title = {On Wi-Fi Model Optimizations for Smartphone-Based Indoor Localization}, series = {ISPRS International Journal of Geo-Information}, volume = {6}, journal = {ISPRS International Journal of Geo-Information}, number = {8}, issn = {2220-9964}, doi = {10.3390/ijgi6080233}, language = {en} } @article{FetzerEbnerDeinzeretal., author = {Fetzer, Toni and Ebner, Frank and Deinzer, Frank and Grzegorzek, Marcin}, title = {Using Barometer for Floor Assignation within Statistical Indoor Localization}, series = {Sensors}, volume = {23}, journal = {Sensors}, number = {1}, issn = {1424-8220}, doi = {10.3390/s23010080}, language = {en} } @inproceedings{BullmannFetzerEbneretal., author = {Bullmann, Markus and Fetzer, Toni and Ebner, Frank and Deinzer, Frank and Grzegorzek, Marcin}, title = {Fast Kernel Density Estimation Using Gaussian Filter Approximation}, series = {21st International Conference on Information Fusion, FUSION 2018, Cambridge, UK, July 10-13, 2018}, booktitle = {21st International Conference on Information Fusion, FUSION 2018, Cambridge, UK, July 10-13, 2018}, doi = {10.23919/ICIF.2018.8455686}, pages = {1233 -- 1240}, language = {en} } @article{FetzerEbnerBullmannetal., author = {Fetzer, Toni and Ebner, Frank and Bullmann, Markus and Deinzer, Frank and Grzegorzek, Marcin}, title = {Smartphone-Based Indoor Localization within a 13th Century Historic Building}, series = {Sensors}, volume = {18}, journal = {Sensors}, number = {12}, issn = {1424-8220}, doi = {10.3390/s18124095}, language = {en} } @article{EbnerSchneider2013, author = {Ebner, Frank and Schneider, Volker}, title = {Analysis of web data compression and its impact on traffic and energy consumption}, series = {FHWS Science Journal}, volume = {1}, journal = {FHWS Science Journal}, number = {2}, address = {W{\"u}rzburg}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-428}, pages = {7 -- 24}, year = {2013}, abstract = {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.}, language = {en} } @inproceedings{EbnerFetzerDeinzeretal., author = {Ebner, F. and Fetzer, T. and Deinzer, Frank and Grzegorzek, M.}, title = {On Prior Navigation Knowledge in Multi Sensor Indoor Localisation}, series = {International Conference on Information Fusion (FUSION 2016)}, booktitle = {International Conference on Information Fusion (FUSION 2016)}, language = {en} } @inproceedings{FetzerEbnerKoepingetal., author = {Fetzer, T. and Ebner, F. and K{\"o}ping, L. and Grzegorzek, M. and Deinzer, Frank}, title = {Recovering From Sample Impoverishment in Context of Indoor Localisation}, series = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2017)}, booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2017)}, pages = {1 -- 8}, language = {en} } @inproceedings{FetzerEbnerKoepingetal., author = {Fetzer, T. and Ebner, F. and K{\"o}ping, L. and Grzegorzek, M. and Deinzer, Frank}, title = {On Monte Carlo Smoothing in Multi Sensor Indoor Localisation}, series = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016)}, booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016)}, language = {en} } @inproceedings{BullmannFetzerEbneretal., author = {Bullmann, Markus and Fetzer, Toni and Ebner, Markus and Kastner, Steffen and Deinzer, Frank and Grzegorzek, Marcin}, title = {Data Driven Sensor Model for Wi-Fi Fine Timing Measurement}, series = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022)}, booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022)}, language = {en} } @inproceedings{EbnerFetzerBullmannetal., author = {Ebner, Markus and Fetzer, Toni and Bullmann, Markus and Kastner, Steffen and Deinzer, Frank and Grzegorzek, Marcin}, title = {PIPF: Proposal-Interpolating Particle Filter}, series = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022)}, booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022)}, language = {en} } @article{FetzerMaierEbneretal., author = {Fetzer, Toni and Maier, Julian and Ebner, Markus and Bullmann, Markus and Deinzer, Frank}, title = {Digitales Spaghetti-Diagramm zur Laufweganalyse}, series = {wt Werkstattstechnik online}, volume = {112}, journal = {wt Werkstattstechnik online}, number = {10/2022}, pages = {727 -- 731}, language = {de} } @inproceedings{FetzerBullmannEbneretal., author = {Fetzer, Toni and Bullmann, Markus and Ebner, Markus and Kastner, Steffen and Deinzer, Frank and Grzegorzek, Marcin}, title = {Interacting Multiple Model Particle Filter for Indoor Positioning Applications}, series = {Proceedings of the 2023 International Technical Meeting of The Institute of Navigation}, booktitle = {Proceedings of the 2023 International Technical Meeting of The Institute of Navigation}, language = {en} } @article{KastnerEbnerBullmannetal., author = {Kastner, Steffen and Ebner, Markus and Bullmann, Markus and Fetzer, Toni and Deinzer, Frank and Grzegorzek, Marcin}, title = {Magnetic Signature Sensor Model for Accurate Short-Distance Localization}, series = {2022 IEEE Sensors}, journal = {2022 IEEE Sensors}, doi = {10.1109/SENSORS52175.2022.9967176}, pages = {1 -- 4}, language = {en} } @book{Ebner, author = {Ebner, Frank}, title = {Smartphone-based 3D indoor localization and navigation}, publisher = {Logos Verlag}, address = {Berlin}, isbn = {9783832586232}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-19894}, publisher = {Hochschule f{\"u}r Angewandte Wissenschaften W{\"u}rzburg-Schweinfurt}, pages = {359}, abstract = {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.}, language = {en} } @article{EbnerFetzerBullmannetal., author = {Ebner, Markus and Fetzer, Toni and Bullmann, Markus and Deinzer, Frank and Grzegorzek, Marcin}, title = {Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand}, series = {Sensors}, volume = {20}, journal = {Sensors}, number = {22}, issn = {1424-8220}, doi = {10.3390/s20226559}, language = {en} }