Name
Title | ||
|---|---|---|
Interpreting presence sensor data and looking for similarities between homes using cluster analysis |
Abstract | ||
|---|---|---|
In order to model older people's behaviour in the home we must first understand it. In this paper we examine data from eight purpose-built aware homes over a six-month period, looking at presence in rooms to try to determine patterns amongst the older residents. We look for homes that have similar movement patterns using cluster analysis. We also examine how movement over days clusters within individual homes. Our analysis begins to show the possibilities of distinguishing between residents in their homes based on patterns of movement. |
Year | Venue | Keywords |
|---|---|---|
2011 | Pervasive Computing Technologies for Healthcare | behavioural sciences computing,geriatrics,home computing,pattern clustering,sensor fusion,statistical analysis,cluster analysis,older people behaviour model,presence sensor data interpretation,purpose-built aware homes,similar movement patterns,AAL,Cluster Analysis,Pervasive Sensor Data,Scatter Plot,Silhouette Coefficent |
Field | DocType | ISBN |
Data mining,Computer science,Pattern clustering,Computer network,Home computing,Scatter plot,Applied psychology,Statistical analysis | Conference | 978-1-61284-767-2 |
Citations | PageRank | References |
3 | 0.67 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Loane | 1 | 21 | 3.56 |
| Brian O'Mullane | 2 | 20 | 3.64 |
| Brennon Bortz | 3 | 28 | 5.37 |
| Benjamin Knapp | 4 | 162 | 26.80 |