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A Tool for Visualizing and Editing Multiple Parallel Tracks of Time Series Data from Sensor Logs

Title data

Maier, Marco ; Dorfmeister, Florian ; Schönfeld, Mirco ; Kessel, Moritz:
A Tool for Visualizing and Editing Multiple Parallel Tracks of Time Series Data from Sensor Logs.
In: Werner, Matthias ; Haustein, Mario (ed.): Ortsbezogene Anwendungen und Dienste : 9. Fachgespräch der GI/ITG-Fachgruppe Kommunikation und Verteilte Systeme. - Chemnitz : Universitätsverlag Chemnitz , 2013 . - pp. 99-108
ISBN 978-3-941003-77-4

Abstract in another language

In the last couple of years, the number of smartphone users has proliferated. As smartphones contain a lot of different sensors, research interest in algorithms combining data of several sensors to derive meaningful information about a user’s context, e.g. her location, is increasing. Ideas for reasonable algorithms often can be found by looking at examples of raw (or somehow pre-processed) sensor data. Still, the research community lacks a simple means to intuitively work with several parallel tracks of time series data. We present a tool which can be used to visualize and edit time dependent data from various sensors along with ground truth recordings like audio or video files. It is complemented by an optional application for logging all kinds of sensor data on Android devices. The tool has already been used to analyze a large data set containing hundreds of walking traces, intended to improve pedestrian dead reckoning algorithms.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Languages and Literature
Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung
Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 18 Nov 2021 14:13
Last Modified: 18 Nov 2021 14:13
URI: https://eref.uni-bayreuth.de/id/eprint/67901