Affiliations: Departamento de Ingeniería Telemática y Electrónica (DTE), Universidad Politécnica de Madrid, Carretera de Valencia km. 7, Madrid 28031, Spain. E-mails: [email protected], [email protected]
Abstract: Human activity detection within smart home (SH) is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of “activity” as the building block with which to construct applications such as healthcare monitoring or ambient assisted living. This paper presents a model for human activity representation. The model has been developed by using the NeON methodology. The proposed human activity model consists of a network of ontologies classified in three categories: user ontologies, SH context ontologies and ADL ontologies, supporting user modelling, SH context modelling and ADL modeling, respectively. Furthermore, the formal definition of the main concepts and properties as well as a proof-of-concept ontology evaluation with a specification scenario are presented. The adoption of DOLCE+DnS Ultralite (DUL) ontology as an upper ontology aims to achieve a high degree of reusability and interoperability within heterogeneous smart home applications.