Semantic knowledge base in support of activity recognition in smart home environments

Activity recognition plays a major role in smart home technologies in providing services to users. One of the approaches to identify ac-tivity is through the use of knowledge-driven reasoning. This paper presents a framework of semantic activity recognition, which is used to support smart home systems to identify users’ activities based on the existing context. The framework consists of two main compo-nents: a semantic knowledge base and an activity recognition module. The knowledge base is represented using ontology and it is used to provide a semantic understanding of the environment in order to classify users’ patterns of activities. Experimental results show that the proposed approach can support the classification process and accurately infer users’ activities with the accuracy of 90.9%.

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