Networked and Embedded Systems Laboratory

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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 speci&#64257;c position and orientation setting or attachment procedure) classi&#64257;cation system that 
uses a mobile phone with a GPS receiver and an accelerometer sensor. The transportation modes 
identi&#64257;ed include whether an individual is stationary, walking, running, biking, or in motorized 
transport. The overall classi&#64257;cation system consists of a decision tree followed by a &#64257;rst-order 
discrete Hidden Markov Model and achieves an accuracy level of 93.6% when tested on a dataset 
consisting of information from sixteen individuals.

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