id |
caadria2017_113 |
authors |
Huang, Weixin, Lin, Yuming and Wu, Mingbo |
year |
2017 |
title |
Spatial-Temporal Behavior Analysis Using Big Data Acquired by Wi-Fi Indoor Positioning System |
doi |
https://doi.org/10.52842/conf.caadria.2017.745
|
source |
P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 745-754 |
summary |
Understanding of people's spatial behavior is fundamental to architectural and urban design. However, traditional investigation methods applied in environmental behavior studies is highly limited regarding the amount of samples and regions it covers, which is not sufficient for the exploration of complex dynamic human behaviors and social activities in architectural space. Only recently the developments in indoor positioning system (IPS) and big data analysis technique have made it possible to conduct a full-time, full-coverage study on human environmental behavior. Among the variety IPS systems, the Wi-Fi IPS system is increasingly widely used because it is easy to be applied with acceptable cost. In this paper, we analyzed a 60-days anonymized data set, collected by a Wi-Fi IPS system with 110 Wi-Fi access points. The analysis revealed interesting patterns on people's behavior besides temporal spatial distribution, ranging from the cyclical fluctuation in human flow to behavioral patterns of sub-regions, some of which are not easy to be identified and interpreted by the traditional field observation. Through this case study, behavioral data from IPS system has exhibited great potential in bringing about profound changes in the study of environmental behavior. |
keywords |
environmental behavior study; Wi-Fi; indoor positioning system; big data; spatial temporal behavior; ski resort |
series |
CAADRIA |
email |
|
full text |
file.pdf (4,942,118 bytes) |
references |
Content-type: text/plain
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last changed |
2022/06/07 07:50 |
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