Abstract
Multimodal data based attention analysis, evaluation and visualization is currently predominant in various domains. The SmartHelm Project aims to present results from new kinds of data such as distraction from cargo bike riders in regular logistics processes. Because of regulatory and legal constraints there was no data collected in real traffic scenarios so far, therefore an alternative methodology is implemented in this work. ‘Pseudo distractions’ generated through four random numbers denoting the distraction type encoded with GPS information obtained from experiments are visualized on a map. To gain more knowledge about real distractions, the feedback gained from interviews with experts and riders in city logistics is visualized on a map to show hotspots in the city. SmartHelm test studies gathered first biophysical data based on Electroencephalography (EEG) and eye-tracking. This paper describes how this data is processed and how the related data management system will be used for the data obtained from forthcoming inner city studies. The outlook describes how we aim to publish biophysical data on an open data platform and to present the data analysis results on a dashboard.
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