Tag Archives: mobile app

Mood in the City – Urban Location-Based Mood Tracking

I am currently brainstorming around the topic of urban location-based mood tracking.

The starting point for this brainstorming was our work on collaborative mood tracking for the purpose of workplace learning in the context of the EU IP MIRROR (FP7). I followed up on this idea together with Anna Weber in a discussion paper that got accepted at the Smart City Learning WS @ ECTEL 2014 in Graz. Both our paper and the slides (presented by Jörg Simon as both Anna and myself were finally unavailable – thanks!) are available from the WS. site.

I repeat the abstract here, in the hope that it represents well the core idea and leads interested people to read the whole paper (only 4 pages after all…)

Abstract:
In the paper we discuss urban location-related mood self-tracking with respect to interaction design and benefits of use. The design of the interaction workflow in conjunction with software architecture needs to consider in which way mood data will be gathered, stored, shared and represented. Interaction and collected information could serve for single citizens to become aware of one’s own and others’ mood in relation to public spaces. From this viewpoint, the proposed system could serve citizens to learn about themselves in relation to a smart, in the sense of ‘technologically enhanced’, city. Additionally, collected information could be useful to trigger reflection on city-level in terms of viewing the city as socio-technical system. In this sense the proposed system could serve city government to learn about city design by collecting data from its most central constituent: the people visiting, living or working in a city.

“Home” and “Work” Semantic Place Detection in MyPlacesDiary App

Today we published the MyPlacesDiary App in the PlayStore: https://play.google.com/store/apps/details?id=at.knowcenter.healthcockpit – Download and enjoy!

There are loads of cool things about this App, from a functionality point of view that it automatically detects your “home” and “work” place. In addition, it is the result of a lot of really nice collaborations:

  • Elisabeth, Oliver, Jörg and I worked on and published a paper on semantic place detection: “Lex, E., Pimas, O., Simon, J., Pammer, V – Where am I? Using mobile sensor data to predict a user’s semantic place with a random forest algorithm
  • Anna Weber did a cool master project in which she used the winning features for the categories “home” and “work” to create a heuristics-based semantic place detection algorithm
  • My team “Ubiquitous Personal Computing” at the Know-Center collaborated with Joanneum Research in a joint R&D project – very nice collaboration: Thanks Alfred, Anna, Stefan, Patrick!