期刊
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
卷 1, 期 1, 页码 57-63出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12652-009-0007-1
关键词
Smart environments; Passive sensors; Activity recognition; Multiple residents; Parallel activities
类别
资金
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [0852172] Funding Source: National Science Foundation
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [0914371] Funding Source: National Science Foundation
- NIBIB NIH HHS [R01 EB009675, R01 EB009675-01A1] Funding Source: Medline
- NIDA NIH HHS [R21 DA024294-03] Funding Source: Medline
The pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. A primary challenge that needs to be tackled to meet this need is the ability to recognize and track functional activities that people perform in their own homes and everyday settings. In this paper, we look at approaches to perform real-time recognition of Activities of Daily Living. We enhance other related research efforts to develop approaches that are effective when activities are interrupted and interleaved. To evaluate the accuracy of our recognition algorithms we assess them using real data collected from participants performing activities in our on-campus smart apartment testbed.
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