Details

Autor(en) / Beteiligte

• Wan, Neng
• Lin, Ge

Titel

Classifying Human Activity Patterns from Smartphone Collected GPS data: A Fuzzy Classification and Aggregation Approach

Ist Teil von

• Transactions in GIS, 2016-12, Vol.20 (6), p.869-886

Ort / Verlag

Oxford: Blackwell Publishing Ltd

Erscheinungsjahr

2016

Link zum Volltext

Quelle

Business Source Ultimate

Beschreibungen/Notizen

• Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone‐measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone‐collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g. up to 96% in activity identification) using of this method. Two examples are provided in the Appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.