Extracting Generalizable Spatial Features from Smart Phones Datasets

Kevin Bouchard, Lawrence B. Holder, Diane J. Cook

Abstract: This paper is part of the effort to develop assistive smart homes able to monitor the daily life activity of a resident and provide punctual assistance when necessary. One of the limitations of assistive smart homes is the fact that it cannot assist the resident when he is going out. Because of this, many researchers are working on wearable sensors to keep track of the activities outside the home. Our lab proposes to instead focus on smart phones which are a cheap alternative that many persons already carry in their daily life. While most algorithms used in the smart home can be exploited, smart phones generate spatial information from the GPS that do not scale very well. The goal of this paper is to initiate a discussion on spatial features and their exploitation for data mining of smart phones datasets.