Abstract
We discuss our experience with the design, implementation, deployment and evaluation of a Human Activity Detection application. This application relies on a software architecture for IoT-based monitoring in Ambient Assisted Living (AAL), based on a Semantic Message Oriented Middleware (SeMoM). Going beyond traditional sensor management systems, our architecture addresses the heterogeneity challenge in IoT healthcare systems and ensures semantic and technical interoperability. SeMoM is able to handle the data acquisition process for a variety of heterogeneous devices, and to provide a reasoning mechanism based on expert knowledge and logic through cognitive sensors. Sensor data and observations are annotated using an extended version of the Cognitive Semantic Sensor Network (CoSSN) ontology built on top of the Semantic Sensor Network (SSN) ontology. CoSSN provides a formal representation that supports a semantic detection of activities.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
