Robustness in Context-Aware Mobile Computing

High level context recognition and situation detection are enabling technologies for unobtrusive mobile computing systems. Significant progress has been made in processing and managing context information, leading to sophisticated frameworks, middlewares, and algorithms. Despite great improvements, context aware systems still require a significantly increased recognition accuracy for high-level context information on uncertain sensor data to enable the robust execution of context-aware applications. Recently Adaptable Pervasive Work-flows (APF)s have been presented as innovative programming paradigm for mobile context-aware applications. We propose a novel Flow Context System (FlowCon) that builds upon APFs. FlowCon uses structural information from the APF to increase accuracy of uncertain high-level context information up to 49%. This way we make an important step to enable robust execution of mobile context-aware applications.