NESL Technical Report #: 2008-10-4
Abstract: 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.
Publication Forum: to appear in ACM Transactions on Sensor Networks
Page (Count): 26
NESL Document?: Yes
Document category: Journal Paper