Scipediacontent: Scipediacontent moved page Draft Content 881635020 to Raubal et al 2016a

2021-02-03T16:58:37Z

Scipediacontent moved page Draft Content 881635020 to Raubal et al 2016a

Scipediacontent: Created page with " == Abstract == The large interest in analyzing one’s own fitness led to the development of more and more powerful smartphone applications. Most are capable of tracking a..."

2021-02-03T16:58:34Z

Created page with " == Abstract == The large interest in analyzing one’s own fitness led to the development of more and more powerful smartphone applications. Most are capable of tracking a..."

New page

== Abstract ==

The large interest in analyzing one’s own fitness led to the development of more and more powerful smartphone applications. Most are capable of tracking a user’s position and mode of locomotion, data that do not only reflect personal health, but also mobility choices. A large field of research is concerned with mobility analysis and planning for a variety of reasons, including sustainable transport. Collecting data on mobility behavior using fitness tracker apps is a tempting choice, because they include many of the desired functions, most people own a smartphone and installing a fitness tracker is quick and convenient. However, as their original focus is on measuring fitness behavior, there are a number of difficulties in their usage for mobility tracking. In this paper we denote the various challenges we faced when deploying GoEco! Tracker (an app using the Moves fitness tracker to collect mobility measurements), and provide an analysis on how to best overcome them. Finally, we summarize findings after one month of large scale testing with a few hundred users within the GoEco! living lab performed in Switzerland.

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.2991/ict4s-16.2016.11 http://dx.doi.org/10.2991/ict4s-16.2016.11] under the license https://creativecommons.org/licenses/by

* [https://download.atlantis-press.com/article/25860371.pdf https://download.atlantis-press.com/article/25860371.pdf]

* [https://repository.supsi.ch/7714 https://repository.supsi.ch/7714],
: [https://www.atlantis-press.com/proceedings/ict4s-16/25860371 https://www.atlantis-press.com/proceedings/ict4s-16/25860371],
: [https://academic.microsoft.com/#/detail/2530932436 https://academic.microsoft.com/#/detail/2530932436] under the license cc-by

← Older revision	Revision as of 16:58, 3 February 2021
(No difference)

Raubal et al 2016a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 881635020 to Raubal et al 2016a

Scipediacontent: Created page with " == Abstract == The large interest in analyzing one’s own fitness led to the development of more and more powerful smartphone applications. Most are capable of tracking a..."