Schlagwort-Archive: AGIT2016

Urban Emotions auf der AGIT 2016

Auf der diesjährigen AGIT2016 bzw. dem GI-Forum haben wir unsere neue Publikation präsentieren dürfen. Im Rahmen der Session „Urban Geoinformatics“ durfte ich im Namen meiner Co-Autoren Bernd Resch, Martin Loidl, Andreas Petutschnig und Linda Dörrzapf „Urban Emotions Bicycle Experience – enriching bicycle traffic planning with human sensor data“ vorstellen. Der Artikel ist GI_Forum Journal unter Open Access publiziert und kann GI_FORUM Journal abgerufen werden.

picture by Anita Graser via Twitter https://twitter.com/underdarkGIS/status/750676303133704192
picture by Anita Graser via Twitter https://twitter.com/underdarkGIS/status/750676303133704192

AGIT2016_Urban_Emotions01 AGIT2016_Urban_Emotions02

Hier ist der englische Abstract zur Publikation:

Even though much research has been conducted on the safety of cycling infrastructures, most previous approaches only make use of traditional and proven methods based upon datasets such as accident statistics, road infrastructure data, or questionnaires. Apart from typical surveys, which are known to face numerous limitations from a psychological and sociological viewpoints, the question of how perceived safety can best be assessed is still widely unexplored. Thus, this paper presents an approach for bio-physiological sensing to identify places in urban environments which are perceived as unsafe by cyclists. Specifically, a number of physiological parameters like ECG, skin conductance, skin temperature and heart rate variability are analysed to identify moments of stress. Together with data gathered through a People as Sensors app, these stress levels can be mapped to specific emotions. This method was tested in a pilot study in Cambridge, MA (USA), which is presented in this paper. Our findings show that our method can identify places with emotional peaks, particularly fear and anger. Although our results can be qualitatively interpreted and used in urban planning, more research is necessary to quantitatively and automatically generate recommendations from the measurements for urban planners.

Hier auch noch einige Twitterreaktionen aus der Session.