A Reusable and Adaptable Information Model for Ambient Intelligence Systems

In Ambient Intelligence (AmI) systems, the contextual information (time, location, available resources, people behavior, etc.) usually needs to be monitored and analyzed in order to offer pro-active and context-aware functionalities to end users. Therefore, the contextual information should conform to an information model that is commonly devised to capture the specific features of a concrete AmI system. Hence, the incorporation of new functionalities to an AmI system usually involves the modification of the associated information model, which may lead to compatibility and maintainability difficulties. Moreover, the data integration and interoperability at information level between different AmI systems can be limited by the availability of shared concepts in their respective information models. To overcome those problems, this paper presents an information model that can be adapted to the specific data requirements of many different AmI systems, and reused across them. The benefits of the proposal have been validated through the development of a Mobile Forensic Workspace (MFW) for disaster scenarios.