Caring Analytics for Adults With Special Needs

We propose a novel caring analytics system for assisting with the long-term care of adults with special needs. Our proposed system combines sensor network-driven activity analysis and online learning algorithms to analyze each resident's care. The analysis should result in a variety of reports and alerts on activities of interest (is the resident eating regularly?) as well as recommendations (try a different type of food). We do so in a complex environment: each home contains several residents, one or more caregivers, and visitors. Our system must extract the activity of each resident from this noisy environment. Moreover, the conditions of the residents vary widely, and the recommendation system must be robust even though the available information may be limited.