Abstract: Smart homes equipped with ambient wireless sensor networks provide new opportunities to help older adults age-in-place, improve their quality of life and help better manage their health and wellness. In this paper, we present a methodology that estimates occupants’ status as active, sedentary, in-bed, out-of-home and unobservable, their location in the house, and their daily activities related to overall health and wellness. The methodology is used to visualize and examine the daily patterns and activities of older adults living in their own homes and participating in a smart home research project. The proposed location and status estimation algorithm is highly accurate as validated by a mobile app that prompts participants with questions about the estimated time of their daily activities. A case study involving a significant health-related life event is presented where the participant’s account of changes in her patterns and activities through bi-weekly interviews are shown to confirm inferences based on the results of the proposed methodology.
Keywords: Health and wellness, age-in-place, rule-based algorithm, smart homes, wireless sensor networks