Activity pattern mining using temporal relationships in a smart home

Author

Moutacalli, Mohamed Tarik ; Marmen, Vincent ; Bouzouane, Abdenour ; Bouchard, Bruno

Author_Institution

Dept. of Inf., UQAC, Chicoutimi, QC, Canada

fYear

2013

fDate

16-19 April 2013

Firstpage

83

Lastpage

87

Abstract

Allowing elders and people with cognitive dysfunction such as Alzheimers disease to stay in their home longer is rapidly becoming a priority for the health care system. The use of smart homes is a very promising solution because it can automatically offer real-time assistance to complete daily activities. Data mining techniques have been used to identify smart home occupant´s daily routines, but most of the time, only the sequence of the events is analyzed. We propose a new algorithm to discover frequent activities in a smart home history log using temporal relationships between sensor activations. Experiments on a real smart home sensor log showed promising results in the detection of all frequent activities.

Keywords

data mining; diseases; geriatrics; health care; medical disorders; Alzheimers disease; activity pattern mining; cognitive dysfunction; data mining techniques; health care system; real-time assistance; smart home history log; smart home sensor log; temporal relationships; Algorithm design and analysis; Clustering algorithms; Data mining; Databases; Medical services; Real-time systems; Smart homes;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Healthcare and e-health (CICARE), 2013 IEEE Symposium on

Conference_Location

Singapore

Print_ISBN

978-1-4673-5882-8

Type

conf

DOI

10.1109/CICARE.2013.6583073

Filename

6583073