Abstract
This paper presents a method for recognition of Activities of Daily Living (ADLs) in smart homes. Recognition of activities of daily living and tracking them can provide unprecedented opportunities for health monitoring and assisted living applications, especially for elderly and people with memory deficits. We present ARoM (ADL Recognition Method) that discovers and monitors patterns of ADLs in sensor equipped smart homes. The ARoM is consists of two components: smart home management monitoring and ADL pattern monitoring. This paper studies on the ontology base and the reasoning that are main parts of ADL pattern monitoring. The ontology base supports the semantic discovery for location, device, environments domains in smart homes. The reasoning system discovers the activity for a person and the appropriate service for a present situation. On detection of significant changes of context, the reasoning is triggered. We design the ontology model for ARoM and implement the prototype system of ARoM by using Protege and Jess tools.
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