TY - GEN
T1 - Searching for temporal patterns in AmI sensor data
AU - Tavenard, Romain
AU - Salah, Albert A.
AU - Pauwels, Eric J.
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2008.
PY - 2008/1/1
Y1 - 2008/1/1
N2 - Anticipation is a key property of human-human communication, and it is highly desirable for ambient environments to have the means of anticipating events to create a feeling of responsiveness and intelligence in the user. In a home or work environment, a great number of low-cost sensors can be deployed to detect simple events: the passing of a person, the usage of an object, the opening of a door. The methods that try to discover re-usable and interpretable patterns in temporal event data have several shortcomings. Using a testbed that we have developed for this purpose, we first contrast current approaches to the problem. We then extend the best of these approaches, the T-Pattern algorithm, with Gaussian Mixture Models, to obtain a fast and robust algorithm to find patterns in temporal data. Our algorithm can be used to anticipate future events, as well as to detect unexpected events as they occur.
AB - Anticipation is a key property of human-human communication, and it is highly desirable for ambient environments to have the means of anticipating events to create a feeling of responsiveness and intelligence in the user. In a home or work environment, a great number of low-cost sensors can be deployed to detect simple events: the passing of a person, the usage of an object, the opening of a door. The methods that try to discover re-usable and interpretable patterns in temporal event data have several shortcomings. Using a testbed that we have developed for this purpose, we first contrast current approaches to the problem. We then extend the best of these approaches, the T-Pattern algorithm, with Gaussian Mixture Models, to obtain a fast and robust algorithm to find patterns in temporal data. Our algorithm can be used to anticipate future events, as well as to detect unexpected events as they occur.
UR - https://www.scopus.com/pages/publications/84924126939
U2 - 10.1007/978-3-540-85379-4_7
DO - 10.1007/978-3-540-85379-4_7
M3 - Conference contribution
AN - SCOPUS:84924126939
SN - 9783540853787
T3 - Communications in Computer and Information Science
SP - 53
EP - 62
BT - Constructing Ambient Intelligence - AmI 2007 Workshops, Revised Papers
A2 - Ruyter, Boris
A2 - Aarts, Emile
A2 - Tscheligi, Manfred
A2 - Dey, Anind
A2 - Gellersen, Hans
A2 - Schiele, Bernt
A2 - Buchmann, Alejandro
A2 - Muhlhauser, Max
A2 - Aitenbichler, Erwin
A2 - Wichert, Reiner
A2 - Ferscha, Alois
PB - Springer Verlag
T2 - European Conference on Ambient Intelligence, AmI 2007
Y2 - 7 November 2007 through 10 November 2007
ER -