An ontology-based framework for a Less Invasive Domestic Management System (LIDoMS)

Research in the fields of the Smart Home and Ambient Assisted Living has increased in the last decade. While some solutions are available to general public, there are still some concerns related to the design of smart solutions and their acceptance, especially when it comes to residents' monitoring and privacy. In this context, this paper introduces an ontology-based smart home framework, LIDoMS, aimed at focusing on inhabitants needs by providing a representation of their health conditions, while offering them customized services. End-users can interact with the system thanks to an adaptive and ubiquitous graphical interface. In this work, the ontological framework underlying LIDoMS is described; the system exploits the knowledge regarding the status of appliances and residents' location within the smart home to infer the activity they are involved in, and to provide customized adaptation of indoor comfort metrics, thus enabling a less invasive monitoring of the inhabitants. Two scenarios describe how different residents can interact with LIDoMS to personalize comfort metrics - pivotal for their health condition. Finally, a framework for the validation of LIDoMS is presented.