Using Mobile Phones to Determine Transportation Modes

In ACM Transactions on Sensor Networks , 26 pages , June 2009.

NESL Technical Report #: TR-UCLA-NESL-200810-04

As mobile phones advance in functionality and capability, they are being used for more than just communication. Increasingly, these devices are being employed as instruments for introspection into habits and situations of individuals and communities. Many of the applications enabled by this new use of mobile phones rely on knowing contextual information. The focus of this work is on one type of context, the transportation mode of an individual, with the goal of creating a convenient (no specific position and orientation setting or attachment procedure) classification system that uses a mobile phone with a GPS receiver and an accelerometer sensor. The transportation modes identified include whether an individual is stationary, walking, running, biking, or in motorized transport. The overall classification system consists of a decision tree followed by a first-order discrete Hidden Markov Model and achieves an accuracy level of 93.6% when tested on a dataset consisting of information from sixteen individuals.

• Sasank Reddy
• Min Mun
• Jeff Burke
• Deborah Estrin
• Mark Hansen
• Mani B Srivastava

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