Predicting Personal Transportation Modes Using Uncertain Smartphone Sensor Data

Hae Jung Baek; Je Min Kim; Young Tack Park

doi:10.4028/www.scientific.net/AMM.764-765.1002

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 764-765Predicting Personal Transportation Modes Using...

Predicting Personal Transportation Modes Using Uncertain Smartphone Sensor Data

Abstract:

This paper describes a method for inferring user destinations and routes based on logs collected by smartphones. A challenging problem is coping with the uncertainty of smartphone sensor data. In this study, we represent a user transportation model with probabilistic models based on temporal smartphone sensor data, including GPS and accelerometer data. In our model, the travel behavior and spatio-temporal information of users are factors that affect route decisions. We propose hierarchical particle filters to enhance the performance and efficiency by sampling the route model based on hierarchical and semantic relationships.

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Periodical:

Applied Mechanics and Materials (Volumes 764-765)

Pages:

1002-1006

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.764-765.1002

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Cite this paper

Online since:

May 2015

Authors:

Hae Jung Baek*, Je Min Kim, Young Tack Park

Keywords:

Dynamic Bayesian Network, Particle Filter, Personal Route Prediction, Smartphone

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