CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

id ecaade2012_142
authors Shin, Dongyoun; Arisona, Stefan Müller; Georgakopoulou, Sofia; Schmitt, Gerhard; Kim, Sungah
year 2012
title A Crowdsourcing Urban Simulation Platform on Smartphone Technology: Strategies for Urban Data Visualization and Transportation Mode Detection
source Achten, Henri; Pavlicek, Jiri; Hulin, Jaroslav; Matejovska, Dana (eds.), Digital Physicality - Proceedings of the 30th eCAADe Conference - Volume 2 / ISBN 978-9-4912070-3-7, Czech Technical University in Prague, Faculty of Architecture (Czech Republic) 12-14 September 2012, pp. 377-384
wos WOS:000330320600039
summary We propose a crowdsourcing simulation environment that brings human intention into the urban simulator. Our fundamental goal is to simulate urban sustainability by employing direct human interaction. In this paper we present a prototype mobile phone application that implements a novel transportation mode detection algorithm. The mobile phone application runs in the background and continuously collects data from the built-in acceleration and network location sensors. The collected data is analyzed by the transportation mode detection algorithm and automatically partitioned into activity segments. A key observation of our work is that walking activity can be robustly detected in the data stream and acts as a separator for partitioning the data stream into other activity segments. Each vehicle activity segment is then sub-classifi ed according to the type of used vehicle. Our approach yields high accuracy despite the low sampling interval and not requiring GPS data that bring minimized device power consumption. Ultimately, the collected information can be translated into real-time urban behavior and will indicate sustainability, both on the personal and the city level.
keywords Crowdsourcing simulation platform; transport mode detection; social sensing; urban sustainability; mobile application
series eCAADe
email shin@arch.ethz.ch
full text file.pdf (1,182,959 bytes)
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