Occupancy and daily activity event modelling in smart homes for older adults with mild cognitiveiImpairment or dementia

Author(s)

Publication date

2018

Series/Report no

Linköping Electronic Conference Proceedings;153

Publisher

Linköping University Electronic Press

Document type

Abstract

In this paper we present event anticipation and prediction of sensor data in a smart home environment with a limited number of sensors. Data is collected from a real home with one resident. We apply two state-of-the-art Markov based prediction algorithms − Active LeZi and SPEED − and analyse their performance with respect to a number of parameters, including the size of the training and testing set, the size of the prediction window, and the number of sensors. The model is built based on a training dataset and subsequently tested on a separate test dataset. An accuracy of 75% is achieved when using SPEED while 53% is achieved when using Active LeZi.

Keywords

Version

acceptedVersion

Permanent URL (for citation purposes)

  • https://hdl.handle.net/10642/7194