Ontology-driven monitoring system for ambient assisted living

As the global population ages, effective home healthcare solutions become essential. Over a decade ago, ambient-assisted living (AAL) emerged as a promising solution, especially when combined with the potential of the Internet of Things (IoT) to revolutionize healthcare delivery. However, integrating diverse smart home devices with healthcare systems poses challenges regarding interoperability and real-time, context-aware responses. Addressing these challenges, this study introduces an ontology for AAL that seamlessly merges IoT and Smart Home ontologies with the established healthcare ontology, SNOMED CT. This ontology-centric approach facilitates semantic interoperability and knowledge sharing, paving the way for more personalized healthcare delivery. The core of this work lies in developing an AAL monitoring system grounded in this ontology. By incorporating Semantic Web Rule Language (SWRL) rules, the system can provide context-sensitive automated alerts and responses, taking into account patient-specific attributes, household features, and instantaneous sensor data. Empirical testing in the Halmstad Intelligent Home (HINT) highlights the system's viability for practical deployment. Preliminary results indicate that the proposed integrative ontology-driven strategy holds significant potential to enhance healthcare services in AAL environments, marking an essential step towards achieving personalized, patient-centric care.