Using GPS to Learn Significant Locations and Predict Movement across Multiple Users

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Using GPS to Learn Significant Locations and Predict Movement across Multiple Users (2003)

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by Daniel Ashbrook , Thad Starner

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@MISC{Ashbrook03usinggps,
    author = {Daniel Ashbrook and Thad Starner},
    title = {Using GPS to Learn Significant Locations and Predict Movement across Multiple Users},
    year = {2003}
}

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Abstract

Wearable computers have the potential to act as intelligent agents in everyday life and assist the user in a variety of tasks, using context to determine how to act. Location is the most common form of context used by these agents to determine the user's task. However, another potential use of location context is the creation of a predictive model of the user's future movements. We present a system that automatically clusters GPS data taken over an extended period of time into meaningful locations at multiple scales. These locations are then incorporated into a Markov model that can be consulted for use with a variety of applications in both single--user and collaborative scenarios. 1

Keyphrases

predict movement multiple user learn significant location everyday life potential use gps data collaborative scenario single user extended period meaningful location future movement predictive model wearable computer location context common form multiple scale intelligent agent markov model

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