Context Flow Graphs: Situation Modeling for Rule-Based Proactive Context-Aware Systems

Abstract

A proactive context-aware system automatically adapts its user interface to the user's situational needs. This is achieved by continuously capturing the environmental properties, reasoning upon the context, and detecting situations where unsolicited adjustments are helpful or notifications informative. If the characteristics of those situations are well known in advance, their occurrence can be detected at runtime by the rule-based processing of raw sensor data. However, rule-based context reasoning methods determine the user's situation mostly based on present sensor signals instead of considering the situation to be likewise the product of the past context. This article introduces a graph-based situation modeling formalism for the specification of system-relevant environmental circumstances as context flow graphs. A directed cyclic graph represents thereby the distinct contextual characteristics a user's situation is made of and the temporal order in which these appear and disappear during the evolution of the situation. Complex situations for rule-based proactive context-aware systems can then be expressed at a high level of abstraction and without the need to understand the underlying sensor-related signal processing mechanisms. The technical feasibility is demonstrated by a prototypical distributed proactive context-aware middleware that, in addition, comes up with a web-based user interface for the interactive graphical and logical modeling of situations as context flow graphs.

Keywords

• Context-aware Computing
• context modeling
• proactive context-aware services
• rule-based context reasoning
• situation modeling
• temporal context reasoning