Name
Abstract | ||
|---|---|---|
Daily activity recognition is essential to enable smart elderly care services and the recognition accuracy affects much the quality of the elderly care system. Although a lot of work has been done to recognize elderly people's activities of daily life (ADL), few systems have investigated if the location information can be deployed to improve the ADL recognition accuracy. In this paper, we intend to incorporate the location information in the activity recognition algorithm and see if it can help to improve the recognition accuracy. We propose two ways to bring the location information into the picture: one way is to bring location in the feature level, the other way is to utilize it to filter irrelevant sensor readings. Intensive experiments have been conducted to show that bringing location information into the activity recognition algorithm in both ways can help to improve the recognition rate by around 5% on average compared to the system neglecting the location information. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-30779-9_11 | ICOST |
Keywords | Field | DocType |
adl recognition accuracy,recognition accuracy,location information,smart elderly care service,elderly care system,recognition rate,elderly people,daily life,daily activity recognition,activity recognition algorithm | Activity recognition,Computer security,Computer science,Home automation,Human–computer interaction,Artificial intelligence | Conference |
Citations | PageRank | References |
4 | 0.45 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Chen | 1 | 2032 | 185.26 |
| Daqing Zhang | 2 | 4 | 0.45 |
| Lin Sun | 3 | 4 | 0.45 |
| Mossaab Hariz | 4 | 35 | 3.60 |
| Yang Yuan | 5 | 4 | 0.45 |