Processing and Segmenting Road Cycling Data for Visual Analysis

Submitted by Christian Bors on Mon, 09/24/2018 - 11:59
Problem

Automatically parsing sports movement data is a complex topic that requires extensive domain knowledge. Although smart sports watches and activity trackers are recording similar dimensions, the data is often pre-processed out of the box and tracks generated by different systems can rarely be directly compared.

It is necessary to develop a tool that allows interative adjustment of the processing workflow to account for differences in data sets

Aim

Develop a Java tool for processing tcx cycling (movement) data as a multivariate time series.

Topics
Time Series, data processing
Other information

The application is based on a machine learning framework that can be used for development. The prototype should be delivered as a standalone application.

More information can be found on the respective open source repositories:

https://github.com/TKnudsen/DMandML
https://github.com/TKnudsen/ComplexDataObject
https://github.com/TKnudsen/timeSeries

Scope
BA
PR
Assigned as
Project/Projektarbeit
Contact
Christian Bors, by appointment, bors [at] ifs.tuwien.ac.at
Area
Visual Analytics (VA)
Status
open