Abstract
Recognition of inhabitants' activities of daily living (ADLs) is an important task in smart homes to support assisted living for elderly people aging in place. However, uncertain information brings challenge to activity recognition which can be categorised into environmental uncertainties from sensor readings and user uncertainties of variations in the ways to carry out activities in different contexts, or by different users within the same environment. To address the challenges of these two types of uncertainty, in this paper, we introduce the innovative idea of incorporating activity duration into the framework of learning inhabitants' behaviour patterns on carrying out ADLs in smart home environment. A probabilistic learning algorithm is proposed with duration information in the context of multi-inhabitants in a single home environment. The prediction is for both inhabitant and ADL using the learned model representing what activity is carried out and who performed it. Experiments are designed for the evaluation of duration information in identifying activities and inhabitants. Real data have been collected in a smart kitchen laboratory, and realistic synthetic data are generated for evaluation. Evaluations show encouraging results for higher-level activity identification and improvement on inhabitant and activity prediction in the challenging situation of incomplete observation due to unreliable sensors compared to models that are derived with no duration information. The approach also provides a potential opportunity to identify inhabitants' concept drift in long-term monitoring and respond to a deteriorating situation at as early stage as possible.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | IEEE |
Pages | 1-8 |
Number of pages | 8 |
ISBN (Print) | 978-963-9799-89-9 |
DOIs | |
Publication status | Published (in print/issue) - 20 Mar 2010 |
Event | Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2010 4th International Conference on-NO PERMISSIONS - Munich Duration: 20 Mar 2010 → … |
Conference
Conference | Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2010 4th International Conference on-NO PERMISSIONS |
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Period | 20/03/10 → … |
Keywords
- home automation
- learning systems
- probability
- activity recognition
- daily living activities
- multi-inhabitants context
- probabilistic learning algorithm
- smart home environment
- smart kitchen laboratory
- Aging
- Dementia
- Home computing
- Intelligent sensors
- Monitoring
- Predictive models
- Senior citizens
- Sensor phenomena and characterization
- Smart homes
- Uncertainty
- ADL
- duration
- probabilistic learning
- reasoning
- smart home