Identification of the User's Habits based on Activity Information
Nicholas Melo, Jaeryoung Lee, Ryo Suzuki
Abstract
This work proposes a system able to recognize the user habits based on his daily activities in a smart house. The habit estimation system uses the information provided by an activity recognition module, which provides the sequence and the duration of the activities performed by the user. Based on those parameters, the activities are represented as a signal by using Fourier series representation. Several output signals from different users are clustered into groups using the k-means method, where each cluster corresponds to a specific habit from a group of people. The proposed system was tested with dataset from the experiment that took place in an environment similar to a smart house. The users were asked to perform a set of 6 activities in any desired orders. In total, twenty-four subjects took part in the experiments. All activities were successfully recognized by the system and three different habits were found. The proposed system along with its habit representation can be potentially used to trace the relationships between the habits observed and some aspects of the user personality traits.
BibTeX
@inproceedings{iros2018_identificationof,
title = {Identification of the User's Habits based on Activity Information},
author = {Nicholas Melo and Jaeryoung Lee and Ryo Suzuki},
booktitle = {IROS 2018},
year = {2018}
}