ScheduleNanny: Using GPS to Learn the User's Significant Locations, Travel Times and Schedule

TL;DR

ScheduleNanny leverages GPS data from multiple devices to identify significant locations, estimate travel times, and model user schedules for intelligent alerts, enhancing context-aware computing.

Contribution

Introduces a multi-device GPS-based system that learns user locations, travel times, and schedules to improve context-aware notifications and assistance.

Findings

Effective clustering of GPS data into significant locations

Accurate estimation of travel times between locations

Probabilistic user schedule modeling improves alert relevance

Abstract

As computing technology becomes more pervasive, personal devices such as the PDA, cell-phone, and notebook should use context to determine how to act. Location is one form of context that can be used in many ways. We present a multiple-device system that collects and clusters GPS data into significant locations. These locations are then used to determine travel times and a probabilistic model of the user's schedule, which is used to intelligently alert the user. We evaluate our system and suggest how it should be integrated with a variety of applications.