ABSTRACT
This chapter presents overviews of activity recognition with emphasis on ontological-driven activity-recognition approaches. It explains self-management program and a previous ontology-driven self-management program. The chapter presents how a self-management program could interact with a smart environment. It presents an event model that can be used in the context of self-management of disease with a smart environment. The chapter argues that the application of semantic web technologies in conjunction with assistive technologies provide a unique opportunity to formally represent and reason over the context, events and responses in order to design personalized medication adherence self-management programs. Activity recognition can be described as a process of inferring an agent's ongoing tasks from the observed environmental changes triggered by the agent's behavior. Ontological-driven activity recognition can be carried out either using ontology reasoning or ontologies with rules.
