ESUM: This research is a part of our research project "ESUM-Analysing tradeoffs between the energy and social performance of urban morphologies," at the Chair of Information Architecture, ETH Zurich, Zurich, Switzerland and the Chair of Computer Science for Architecture, Bauhaus University Weimar, Germany.
We, a team of researchers at ETH Zurich, Switzerland and Bauhaus University Weimar, Germany, applied Machine Learning methods to investigating how humans perceive their urban environment and what features of urban environment influence the humans' physiological arousal states. For this purpose, we conducted a study, where participants took a leisure walk in an urban environment. Empirical measures of participants' physiological conditions and urban environment features were analyzed using Machine Learning methods.
The project main website containg results from the codes are available at:
http://www.esum.arch.ethz.ch/
The codes for animation (visuallization of data like rela-time walk) are available at: https://github.com/peterbus/Esum_Data_Visualisation
Main paper: https://www.sciencedirect.com/science/article/pii/S0020025518307734